6.1.1 ACGtk

• Name:
  Abstract Categorial Grammar Development Toolkit
• Keywords:
  Natural language processing, NLP, Syntactic analysis, Semantics
• Scientific Description:

  Abstract Categorial Grammars (ACG) are a grammatical formalism in which grammars are based on typed lambda-calculus. A grammar generates two languages: the abstract language (the language of parse structures), and the object language (the language of the surface forms, e.g., strings, or higher-order logical formulas), which is the realization of the abstract language.

  ACGtk provides two software tools to develop and to use ACGs: acgc, which is a grammar compiler, and acg, which is an interpreter of a command language that allows one, in particular, to parse and realize terms.

• Functional Description:
  ACGtk provides a piece of software for developing and using Abstract Categorial Grammars (ACG).
• Release Contributions:
  This version fixes some bugs and adds some commands to the scripting language. Some internal modifications also prepare ACGtk to add extensions of ACGs such as weighting.
• News of the Year:
  In addition to modifications to maintain the code (bug fixes, improvement of error messages, etc.), new functionalities have been added. The grammar of data files has been extended (in particular with UTF-8 symbols) and the command language to use ACGs has been redesigned. Documentation has been improved and a continuous integration workflow has been set up. Several optimizations (in particular regarding magic set rewriting) have been implemented.
• URL:
  http://­acg.­loria.­fr/
• Publications:
  hal-01242154, hal-01328702, tel-01412765, inria-00112956, inria-00100529
• Contact:
  Sylvain Pogodalla
• Participants:
  Philippe De Groote, Pierre Ludmann, Jiri Marsik, Sylvain Pogodalla, Vincent Tourneur

6.1.2 Grew

• Name:
  Graph Rewriting
• Keywords:
  Semantics, Syntactic analysis, NLP, Graph rewriting
• Functional Description:
  Grew is a Graph Rewriting tool dedicated to applications in NLP. Grew takes into account confluent and non-confluent graph rewriting and it includes several mechanisms that help to use graph rewriting in the context of NLP applications (built-in notion of feature structures, parametrization of rules with lexical information).
• News of the Year:

  In 2022, a few Grew software versions were released (1.10 is the latest one).

  The Grew-match tool (http://­match.­grew.­fr) is an online service available where a user can query different corpora with graph matching requests. All universal dependencies corpora (243 in 138 different languages in v2.11) are available and data from several other projects can also be queried. In 2022, 145,000 requests were received on the Grew-match server.

  A new Python binding for the grew library was started and is in active development (https://­github.­com/­grew-nlp/­grewpy)

  An article dedicated to the usage of Grew on semantic representation was published (https://­hal.­inria.­fr/­hal-03724068). Grew was a central tool in other publications (https://­hal.­inria.­fr/­hal-03724129, https://­hal.­inria.­fr/­hal-03846825)

  Grew is also used in the Arborator-Grew software (https://­arborator.­github.­io/­), the annotation platform of the Autogramm ANR project.

• URL:
  https://­grew.­fr/
• Publications:
  hal-03724068, hal-03177701, hal-01930591, hal-01814386, hal-03021720, hal-03724068, hal-03724129, hal-03846825
• Contact:
  Bruno Guillaume
• Participants:
  Bruno Guillaume, Guy Perrier, Guillaume Bonfante

6.1.3 SLODiM

• Name:
  SLODiM
• Keywords:
  NLP, Discourse, Dialogue, French
• Functional Description:
  SLODiM is a software package for the analysis of oral French. It is more particularly developed to allow the analysis of interviews with clinicians in order to identify language behaviours characteristic of mental pathologies.
• Release Contributions:

  The latest version integrates new treatments in particular at the level of the identification of the backchannels.

  A version without the graphical representations is available without an account. Its purpose is to make visible the treatments that are produced in the system.

• News of the Year:
  In 2022, Slodim was redesigned and splat in two parts in order to allow for thorough analyses, on the one hand, and a lean access that presents the computed data, without analyses, on the other hand. A transactional automatic analysis of dialogues was also implemented.
• URL:
  https://­academics.­slodim.­loria.­fr/
• Contact:
  Maxime Amblard
• Partners:
  Loria, Université de Lorraine, CNRS

7.1.1 Abstract Categorial Grammars

7.1.2 Lexical Semantics and Linguistic Knowledge

7.1.3 Entity-Mention Information Extraction

Priyansh Trivedi investigated whether multi-task learning for entity-mention level NLP tasks can be generalized across multiple domains. Entity-mentions are referring expressions used to refer to entities in text, such as pronouns, nouns, and noun phrases. The tasks of detecting these mentions (named entity recognition), detecting mentions of the same entity (coreference resolution), and detecting semantic relations between these entities (relation extraction) are some of the well-researched problems in the field of natural language processing, or more specifically, information extraction. Interestingly, recent research works have demonstrated that solving these tasks together in a multi-task setting is mutually beneficial  57, 56. However these advances assume the availability of aligned annotations, i.e., the same dataset to be annotated with labels from multiple tasks. In this work, we tried to find whether existing models can still be trained in a mutually beneficial manner when different datasets (domain adaptation) are annotated with different tasks (multi-task learning).

The preliminary findings indicate that existing models suffer from domain shift when trained in a multi-domain multi-task setting and generalize poorly when compared to models trained only in a multi-task setting. This negative result suggests that a future investigation on better domain adaptation techniques might be helpful, enabling these models to capitalize on a larger availability of samples from varied domains. Further analysis also provides further evidence to a previously known drawback of multi-task approaches to solving entity-mention level tasks, i.e., typically the annotation guidelines for selecting span boundaries differ across tasks. This problem is further compounded upon in a multi-domain setting. Ways to mitigate this challenge are currently explored, taking inspiration from word-level coreference models  49.

7.1.4 Graph-Based Semantics

We have been studying and comparing different existing semantic graph-based annotation frameworks (AMR, UCCA and DRS). The goal is to determine whether these frameworks are compatible and if they encode the same level of semantic information.

In 32, two of the currently popular semantic frameworks are considered: Abstract Meaning Representation (AMR)—a more abstract framework—and Universal Conceptual Cognitive Annotation (UCCA)—an anchored framework. A corpus-based approach was used to build two graph rewriting systems, a deterministic and a non-deterministic one, from the former to the latter framework. The graph rewriting systems were evaluated and ambiguities discovered when build the rules are reported.

In 13, we show how the online tool Grew-match can be used to make queries and visualize data from existing semantically annotated corpora. A dedicated syntax is available to construct simple to complex queries and execute them against a corpus. Such queries give transverse views of the annotated data, these views can help for checking the consistency of annotations in one corpus or across several corpora. Grew-match can then be seen as an error mining tool: when inconsistencies are detected, it helps find the sentences which should be fixed. Finally, Grew-match can also be used as a side tool to assist annotation tasks helping to find annotation examples in existing corpora to be compared to the data to be annotated.

7.1.5 Semantics of quantification

In a joint work with Harry Bunt, we keep on working on a project that aims at establishing an interoperable annotation scheme for quantification phenomena as part of the ISO suite of standards for semantic annotation, known as the Semantic Annotation Framework. After a break, caused by the Covid-19 pandemic, the project was relaunched in early 2022 with a second working draft, which deals with certain issues in the annotation of quantification in a more satisfactory way than the original working draft 18.

7.1.6 Semantics of questions

Natural language statements are composed not only of declarative sentences but also of interrogative ones. Moreover, sentences cannot be categorized into purely declarative or purely interrogative sentences. Typically, a declarative statement may contain an indirect interrogative clause:

• (a)
  I don't know where Mary is.

Conversely, a direct interrogative clause may contain a declarative subordinate:

• (b)
  Do you know that Mary is here ?

This interaction between declarative and interrogative clauses is particularly present in dialogues, where the logical notion of answerhood is as significant as the one of inference.

In order to tackle this issue from a formal standpoint, we investigated the properties and possible uses of inquisitive semantics, which is a formal semantic theory based on a logic that provides a uniform treatment of both declarative and interrogative expressions. Valentin Richard is currently working on a semantic model for embedded interrogatives, like (a). This kind of sentence exhibits de re/de dicto ambiguity due to the attitude matrix verb (here know). Some further investigation is required to understand the interactions between this ambiguity, the inquisitive content and the dynamic referential effect of the interrogative pronoun.

7.2.1 Dialogue Modeling

In 17, Maxime Amblard and Maria Boritchev present Dialogues in Games (DinG), a corpus of manual transcriptions of real-life, oral, spontaneous multi-party dialogues between French-speaking players of the board game Catan. The objective is to make available a quality resource for French, composed of long dialogues, to facilitate their studies in the style of  48. In a general dialogue setting, participants share personal information, which makes it impossible to disseminate the resource freely and openly. In DinG, the attention of the participants is focused on the game, which prevents them from talking about themselves. In addition, they are conducting a study on the nature of the questions in dialogue, through annotation, in order to develop more natural automatic dialogue systems.

Together with Chloé Braud (IRIT), Maxime Amblard and Chuyuan Li design tools to automatically retrieve characteristic features of dialogues. The results are presented in 28, with a special focus on depression. This serious mental illness impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work examines depression signals in dialogues, a less studied setting that suffers from data sparsity. It is hypothesized that depression and emotion can inform each other, and the influence of dialogue structure through topic and dialogue act prediction is explored. Using a Multi-Task Learning (MTL) approach, the tasks mentioned above are learned jointly with dialogue-tailored hierarchical modeling. Experiments are run on the DAIC and DailyDialog corpora (both contain dialogues in English) and show important improvements over state-of-the-art for depression detection (at best 70.6% F1). This demonstrates the correlation of depression with emotion and dialogue organization and the power of MTL to leverage information from different sources. A further extension of this work, currently under review, was worked on by Chuyuan Li during her sabbatical leave at the University of British Columbia in a collaboration with Gioseppe Carenini's group.

Maxime Amblard supervised the Master Thesis of Amandine Decker on topic shifts. Topics play an important role in coherence in dialogue, as what is currently being discussed constrains the possible contributions of the participants, and initiating a topic while the previous one is still under discussion may be confusing without appropriate signals. However, how to actually define the notion of topic is debated in linguistics and not sufficiently discussed in dialogue modeling. A precise description of topics and topic shifts in conversation would contribute to understanding what it is we perceive when we judge a sequence of utterances to be coherent. In order to understand the different mechanisms that license topic shifts in dialogue and the way participants acknowledge them, several pieces of conversation containing topic shifts were analyzed, with a focus on topic shifts based on extra-linguistic content and more unconventional topic shifts where speakers take advantage of word similarities to introduce a new topic with no semantic relation with the previous one.

Amandine Decker has been studying neural network learning on analogies for morphological issues. Analogical proportions are statements of the form "A is to B as C is to D". They support analogical inference and provide a logical framework to address learning, transfer, and explainability concerns. This logical framework finds useful applications in AI and natural language processing. It has been applied to solve morphological analogies using a retrieval approach named ANNr 30. This deep learning framework encodes structural properties of analogical proportions and relies on a specifically designed embedding model capturing morphological characteristics of words. It is demonstrated that ANNr outperforms the state of the art on 11 languages. ANNr results for Navajo and Georgian, languages on which the model performs worse and better, are analyzed to explore potential correlations between the errors of ANNr and linguistic properties.

7.2.2 Pathological Discourse Modeling

Michel Musiol has obtained was in full-time delegation in the Sémagramme team until 9 2022. This proximity made possible to set up a more active collaboration on the issue of pathological discourse modeling. He has worked on the development of the possibility of testing his conjectures on the cognitive and psychopathological profile of the interlocutors, in addition to information provided by the model of ruptures and incongruities in pathological discourse. This methodological system makes it possible to discuss, or even evaluate, the heuristic potential of the computational models developed on the basis of empirical facts.

In the context of the Inria Exploratory Action ODiM, Maxime Amblard and Michel Musiol have been working on this issue with the constitution of a corpus of pathological discourses and the extension of the tool SLoDIM. The theoretical work focused on the formal definition of transactions in dialogue. With Samuel Buchel and Amandine Lecomte, they introduced a dynamic definition of backchannel words which are used to classify the dialogue units. In 27 they focused on the organizations and functions of backchannel verbal behavior in clinical interaction with a patient suffering from schizophrenia. In this corpus study, they addressed the issue of supportive dialogic behavior in clinical interviews. They started from the analysis of language interactions, assuming that the specific framework of the verbal interaction of clinical type is the privileged place of expressing "supportive dialogic behavior". On the basis of an empirical exploration, they proposed the elaboration of a dynamic interlocutory model of what could be interpreted as a form of attentive, supportive listening, based in particular on specific lexical indicators that are the backchannels. They extracted the properties of discourse configurations in which the supportive behavior of one of the interlocutors (e.g., the psychologist) has the effect of leading the speaker (e.g., the patient) to modify their argumentative strategy. The empirical analyses cover the entire recording time of 10 interviews with patients suffering from schizophrenia (collected in psychiatric hospitals) and 10 interviews with control subjects.

Moreover, in 27 they have designed the beginnings of a methodology for the analysis of discourse disorders that will have the particularity of helping to select the discontinuous sequences that are most likely to be carriers of thought disorders. They anticipated the development of a modeling system based on principles of pragmatic linguistics and formal semantics, which, applied to carefully selected discontinuous discourse sequences, will have a good chance of revealing the nature of the underlying thought disorders. They compared conjectures with the results of a previous study on the discovery of four "proven" types of discontinuous sequences, and showed which of these sequences can thus be considered as carrying thought disorders. They also analyzed these sequences by testing some principles of semantic modeling in order to identify the nature of the disorders and thought operations underlying the relevant discontinuous sequences. They show that discourse thought disorders should not be considered simply as an expression of a dysexecutive syndrome but also as a device likely to affect more complex thought operations such as the inferences involved in the representation system of the conversational context, in the meaning calculus of the utterances and in the speaker's meaning calculus.

In the MePheSTO project (DFKI-Inria AI project), a multimodal perspective on these issues was proposed. A protocol of a clinical multicenter prospective study has been proposed 10.

7.2.3 Cognitive traces of side issues

It is by now widely believed that natural language communication operates at several levels. This means that information is distributed across several partially independent dimensions. For instance, a sentence like My stupid neighbor made noise again, simultaneously conveys that my neighbor made noise (the truth-conditional content), that the speaker considers he is stupid (an expressive, side issue 1) and that he had made noise before (the presupposition of again, side issue 2). While these phenomena have been extensively described from an empirical perspective, there is at present no unified framework for representing their differences and possible interactions under a formal, computational or cognitive point of view.

We examined the motor effects of presuppositions, using the convenient lexical material of factive verbs, that is, verbs which presuppose the truth of the complement clause. For example, Mary knows that Paul cheated on the exam presupposes that Paul cheated on the exam (side issue) and asserts (truth-conditional content) that she believes that. It has been shown that the oral presentation of movement-related verbs like jump or push elicits some activation in the motor cortex and finally results into an involuntary contraction of the thumb-index arc, which can be recorded by a special electromagnetic cell, called a grip force sensor.

We adapted this technique to the case of factive verbs on a series of sentences of the form Mary knows that Paul throws the ball, compared with high base-level sentences like Paul throws the ball and low base-level sentences like Paul does not throw the ball. Summarizing, our results indicate that the sentences with the factive verbs elicit a very similar response to that of high base-level ones, and, as expected, a different response from that of low base-level one. This suggests that, at least for factive verbs, the presupposed status leaves no trace of a special cognitive treatment, which would lead for instance, to a delayed or weaker motor response.

However, when applied to more complex negative sentences like Mary does not know that Paul throws the ball, there is no evidence of a motor trace. This is in agreement with observations in the literature suggesting that, under negation, presuppositions are more 'difficult' to process than in simple assertive sentences. More precisely, in the case of motor response, negation interacts with the presupposition, which suggests that truth-conditional content and side issue cognitive processing cannot be totally separated 7.

7.3.1 Universal Dependencies and Surface Syntactic Universal Dependencies

The Universal Dependencies project (UD) aims at building a syntactic dependency scheme which allows for similar analyses for several different languages. Bruno Guillaume and Guy Perrier are active in the UD community, and participate in the development and the improvement of the French data in this international initiative. In 2022, two new versions (2.10 and 2.11) of the UD data were released.

During 2022, they continued working, in collaboration with Sylvain Kahane, Kim Gerdes and their teams on the promotion of the Surface Syntactic Universal Dependencies (SUD) framework. SUD is an annotation scheme for syntactic dependency treebanks, that is almost isomorphic to UD (Universal Dependencies). Contrary to UD, it is based on syntactic criteria (favoring functional heads) and the relations are defined on distributional and functional bases. In 22, they bring to the fore some advantages to first develop a new treebank in Surface-Syntactic Universal Dependencies (SUD) annotation scheme, even if the goal is to obtain a UD treebank. Theoretical benefits of SUD are presented, as well as UD-compatible SUD innovations. The two-way UD, SUD conversion is explained, as well as the possibility to customize the conversion for a given language. The paper concludes by a practical guide for the development of a SUD treebank.

A website was built to present the framework (guidelines, data). The Sémagramme team is notably in charge of the Grew-based tools for conversion with the UD framework. These conversion tools are used both to produce the UD data for a few SUD native treebanks and to produce the SUD version of all UD available data.

Hee-Soo Choi, Bruno Guillaume and Karën Fort continued working on linguistic typology based on UD annotated data. They used Grew to enrich the UD annotations and studied the respective word order of verbs with their subjects and objects on 74 languages and compared with other linguistic works.1 They focused on four Greenberg's universal, providing results which constitute new typological information based on large amounts of data that can fill in gaps in the existing databases. The corpus-based approach allowed them to evaluate the consistency between corpora of the same language and showed a great variation according to the corpus types: oral language, written language in newspapers, tweets, poetry, novels, grammars, etc. This work was published at the Syntax Fest in 03 2022 19.

7.3.2 Induction of Descriptive Grammars

The ANR project Autogramm (Induction of descriptive grammar from annorated corpora) started in 01 2022. The goal of this project is to automate, as far as possible, the extraction of descriptive grammars and grammatical descriptions from annotated corpora for linguistic and typological studies. The project also promotes the development of treebanks for low-resourced languages, in order to extract quantitative descriptive grammars for these languages.

A new corpus was added to the SUD project in Beja, a Cushitic language spoken in Sudan. This is the first treebank for Beja in the UD/SUD project. It has been built from the conversion and enhancement of an Interlinear Glossed Text (IGT). The paper 26 presents this corpus and describes the choice to use a morph-based annotation and its consequences; the processing chain from an IGT to a morph-based dependency treebank and a word-based treebank; and several interesting constructions in Beja.

With Santiago Herrera and Sylvain Kahane, in 37, the first results regarding the extraction of rules from annotated corpora were presented.

7.3.3 Mapping Lexical Resources

Hee-Soo Choi started her PhD in 10 2021 on mapping French heterogeneous lexical resources. Lexical resources are essential for the development of tools and methods for the various tasks of NLP. These resources are heterogeneous in their size, their construction and their level of linguistic description. This variety opens the way to group or link/map these resources. In 34, she presents a state of the art on French lexical resources and discusses the different features of a lexical resource, the resources based on mapping and the approaches used for this purpose.

7.3.4 FENEC

Karën Fort worked with Alice Millour (Université Paris 8), Yoann Dupont (Université Paris 3) and Alexane Jouglar (former M1 student) on the creation of a balanced sample corpus for French named entity recognition. The created corpus, FENEC, is freely available and presented in a paper which was published at TALN 2022 39.

7.3.5 Sentence Semantic Similarity Corpus

In the context of the CODEINE ANR project and more specifically of Nicolas Hiebel's PhD thesis, Karën Fort worked with Aurélie Névéol (LISN-CNRS) and Olivier Ferret (CEA) on the creation of a sentence semantic similarity corpus for French on the clinical domain. A paper on the subject was presented at LREC 2022 25. An adaptation in French was subsequently presented at TALN 2022 38.

7.5.1 Ethics@Loria

Karën Fort originated a working group at LORIA for AI ethics (ethics@loria), involving researchers from various teams, including Maxime Amblard, Marc Anderson, Armelle Brun (BIRD), Mathieu d'Aquin (Orpailleur), Christophe Cerisara (Synalp), Anne Bonneau (Multispeech), Slim Ouni (Multispeech) and Abdessamad Imine (Pesto). Aurore Coince helped manage the group. Ethics@loria proposed the Doctoral training on Ethics "Write your dystopia".

7.5.2 Evaluating stereotypes in masked language models in many languages

Karën Fort led the creation of a French corpus of stereotyped/anti-stereotyped pairs of sentences (women cannot drive / men cannot drive) with Aurélie Névéol (LISN-CNRS), Yoann Dupont (Sorbonne Université) and Julien Bezançon (M2 student at Sorbonne). The corpus was created by translating and adapting an American corpus (CrowsPairs), then adding more specific French stereotypes (for example against Gypsies) obtained via a citizen science platform, LanguageArc. It was then used to evaluate the main masked models for French (including CamemBERT and FlauBERT). A paper on the subject was accepted at the A* conference in NLP ACL 2022 5. An adaptation in French was subsequently presented at TALN 2022 40. The usage of the citizen science platform LanguageArc was detailed in a paper presented at the LREC 2022 workshop on Novel Incentives in Data Collection from People 21.

Karën Fort contacted researchers interested in creating a CrowsPairs corpus for their language, in order to test the language models. The group got bigger and bigger and now includes: Margot Mieskes and Jonathan Baum for German, Claudia Borg for Maltese, Luciana Benotti and Laura Alonso Alemany for Argentinian Spanish, Wolfgang Sebastian Schmeisser Nieto for Spain Spanish, Sergio Zanotto and Matteo Radaelli for Italian, Francielle Vargas for Brazilian Portuguese, Yongjian Chen, with Karën Fort's M1 students Yuyan Qian and Shailynn Xie, for Chinese and the M1 students Sarah Saidi and Thiziri Saci for standard Arabic. The French CrowsPairs team joined the effort (Aurélie Névéol, Yoann Dupont and Julien Bezançon). The group has been working together since 07 2022, with different levels of progress. The corpora will be made freely available once they are ready, along with the code to test the language models and the guidelines we followed for the adaptation. It's important to notice that this work has been performed without any funding.

7.5.3 NLP for NLP and Ethics

Karën Fort worked with Yves Lepage (Waseda University, Japan), Gaël Lejeune (Sorbonne Université) and Fanny Ducel (M1 student at Sorbonne Université) on the evaluation of the application of the Bender's rule in NLP research papers. The Bender's rule states that NLP researchers should name the language they work on, but it is often not applied, especially when the language dealt with is English, giving the false impression that the research can apply to any language or that English is universal. A paper on a comparison between LREC and ACL proceedings was presented at LREC 2022 20. Another paper analyzing the situation concerning TALN and ACL was presented at TALN 2022 35.

Karën Fort originated a research group on the impact of the BigTech companies on NLP (industry presence, potential thematic shifts, participation in paper authorship). This group is composed of Aurélie Névéol (LISN), Saif Mohammad (National Research Council Canada), Mohamed Abdalla (University of Toronto), Terry Lima Ruas and Jan Philip Wahle (Wuppertal University) and Fanny Ducel (M2 student at Sorbonne University). The group regularly gathered from 09 to 12 2022 to perform both an automatic study on all the ACL Anthology papers and a manual one from the ACL 2022 papers. The results are being submitted at ACL 2023.

7.5.4 Ethics in AI Integration into Industry

The ongoing collaboration between Karën Fort and Marc Anderson resulted in the publication of two journal papers in 2022. One is about ethics by design for real in the industrial context of the AI-Proficient project 8. The other criticizes the "human in" (the loop/command, etc.) terminology and proposes a new grid of analysis of the interaction between the human and the system 1. They also presented their approach and insights relative to a specific logistics centered Use Case in the project 14 at SOHOMA’22. Marc Anderson presented his view on whether the future of AI ethics is interdisciplinary at the conference Where AI Ethics Should Go 41.

In the context of ethical issues in the AI-Proficient project, Marc Anderson authored a conference paper for IAIL 2022 on ethical issues around the EU AI Act 15. Marc Anderson also coauthored (with Fernandez et al.) AI-Proficient's Deliverable 4.1: Human-machine interaction and feedback mechanisms (Design and specification) which was publicly released in 06 2022, and has coauthored three other project deliverables scheduled for release in spring 2023.

8.1.1 C&S Group

Participants: Maxime Amblard, Philippe de Groote, Laurine Jeannot.

8.1.2 Yseop

Participants: Philippe de Groote, Maxime Guillaume, Sylvain Pogodalla.

9.1.1 Participation in other International Programs

9.1.2 International research visitors

9.2.1 H2020 projects

9.3.1 INRIA Exploratory Action: ODiM

Participants: Maxime Amblard, Vincent-Thomas Barrouillet, Samuel Buchel, Amandine Lecomte, Chuyuan Li, Michel Musiol.

• Title:
  Outils informatisés d’aide au Diagnostic des Maladies mentales
• Duration:
  2019–2022
• Coordinator:
  Maxime Amblard
• Partners:
  Inria, Université de Lorraine, Psychiatric hospital Montperrin (Aix-en-Provence)
• Participants:
  Maxime Amblard, Vincent-Thomas Barrouillet, Samuel Buchel, Amandine Lecomte, Chuyuan Li, Michel Musiol
• Abstract:
  ODiM is an interdisciplinary project, which mixed psychiatry-psychopathology, linguistics, formal semantics and digital sciences. The goal was to theoretically replace the paradigm of language and thought disorders (LTD) used in the Mental Health sector with a semantic-formal and cognitive model of Discourse disorders (SD). These disorders are translated into pathognomonic signs, making them complementary tools for diagnosing and screening vulnerable individuals before the onset of psychosis.

9.3.2 ANR Project: CoDeinE

Participants: Karën Fort, Bruno Guillaume.

• Title:
  artificial text COrpus DEsIgNed Ethically automatic synthesis of clinical documents
• Duration:
  03 2021–02 2025
• Coordinator:
  Aurélie Névéol (Limsi)
• Partners:
  CRC, CEA List, LISN, LORIA
• Participants:
  Bruno Guillaume, Karën Fort (local coordinator)
• Abstract:
  Machine learning methods have become prevalent in language technologies. They rely on annotated corpora to train models and evaluate algorithms. The CoDeinE project proposes to address the lack of shareable corpora in sensitive domains such as health or banking. The key idea of the project is to use confidential corpora to automatically generate synthetic texts that mimic the linguistic properties of real documents while preserving confidentiality. We will use clinical documents in electronic patient records as a case study. Furthermore, the project will rely on Games With A Purpose and crowd sourcing to validate and annotate the synthesized texts.

9.3.3 ANR Project: Autogramm

Participants: Bruno Guillaume, Karën Fort, Guy Perrier.

• Title:
  Induction of descriptive grammar from annotated corpora
• Duration:
  01 2022–12 2025
• Coordinator:
  Sylvain Kahane (Université Paris Nanterre)
• Partners:
  MoDyCo, LACITO, LISN, Inria Nancy - Grand Est
• Participants:
  Bruno Guillaume (local coordinator), Karën Fort, Guy Perrier
• Abstract:
  The goal of this project is to automate, as far as possible, the extraction of descriptive grammars and grammatical descriptions from annotated corpora for linguistic and typological studies. The project also promotes the development of treebanks for under-endowed languages, in order to extract quantitative descriptive grammars for these languages. The project uses the annotation scheme SUD (Surface-syntactic Universal Dependencies), the query tool Grew-match and the annotation tool ArboratorGrew.

10.1.1 Scientific events: organisation

10.1.2 Scientific events: selection

10.1.3 Journal

10.1.4 Invited talks

• Karën Fort: invited to present a state of the art on ethics in NLP at the joint GDR LIFT and TAL conference in Marseille, on 2022-11-14: "Éthique et TAL : ce dont on parle, ce dont on ne parle plus, ce dont on ne parle pas (un état de l’art)" 36.
• Jacques Jayez: invited talk at the Implicit Manipulation in Politics - Quantitatively Assessing the Tendentiousness of Speeches (IMPAQTS) conference ,2022-04-27 and 2022-04-28: "(Innocent?) Bias inside language".

10.1.5 Invited seminars

• Marc Anderson: 2022-12-15, Department ISET - CRAN, UL "Éthique dès la conception dans un projet d'informatique industrielle : l'exemple du projet AI-Proficient".
• Hee-Soo Choi: 2022-05-20, GRLMC, Universitat Rovira i Virgili, Spain "Investigating Dominant Word Order on Universal Dependencies with Graph Rewriting".
• Karën Fort: OFAI seminar (Austria) on 2022-10-12: "Ethics and NLP: What we Talk About, What we Don’t Talk About Anymore, What we Never Talked About".
• Karën Fort: IXXI seminar on 2022-06-10: "Éthique et TAL : ce dont on parle, ce dont on ne parle plus, ce dont on ne parle pas (un état de l’art)".
• Karën Fort: panel on teaching ethics at the ERCIM project meeting.

10.1.6 Leadership within the scientific community

• Maxime Amblard: Management Committee of the OLKI project (Lorraine Université d'Excellence project - PIA), co-leader of the workpackage 2 on NLP activities.
• Marc Anderson: Josiah Royce Society Board Member - Representative at Large (from 2020).
• Karën Fort: Co-chair of the ACL Ethics committee (2021–2026).
• Karën Fort: member of the ethics committee of the LIAvignon Chaire.
• Karën Fort: principal investigator of LIFT 2, a follow-up to the LIFT GDR (Linguistique Informatique, Formelle et de Terrain) to start on 2024.

10.1.7 Scientific expertise

• Maxime Amblard: evaluation for the Université Grenoble-Alpes (internal call for project proposals, allowing for PhD position funding).
• Karën Fort: evaluation for the Deutsche Forschungsgemeinschaft (German Research Foundation), evaluation for the Marie Sklodowska-Curie Actions COFUND / C2W (Université de Mons, Belgique).

10.1.8 Research administration

• Maxime Amblard:
  • Member of conseil d'administration of Université de Lorraine.
  • Member of conseil scientifique of Université de Lorraine.
  • Standing invitee at the pôle scientifique AM2I of Université de Lorraine.
  • Member of the Sénat Académique of Université de Lorraine.
  • Member of the grade promotion committee of Université de Lorraine.
  • Member of the administration council of the Institut des sciences du digital, management et cognition.
  • Head of the master in Natural Language Processing (master 1 and 2).
• Karën Fort
  • Member of CNU 27 (Computer Science): participation to qualifications, promotions and suivi de carrière.
• Bruno Guillaume
  • Head of the Natural Language Processing and Knowledge Discovery department of the LORIA laboratory.
  • Manager (with Alain Polguère) of the CPER (Contrat de Plan État-Région) "Langues, Connaissances et Humanités Numériques".
• Sylvain Pogodalla
  • Elected member of the comité de centre Inria Nancy – Grand Est.
  • In charge of the local commission IES (information et édition scientifique) of the Inria Nancy – Grand Est and LORIA.
  • Member of the national commission IES of Inria.

10.2.1 Teaching

• Licence:
  • Maxime Amblard, AI Introduction, 15h, L1, Université de Lorraine, France.
  • Maxime Amblard and Chuyuan Li NLP for beginners, 20h, L2, Université de Lorraine, France.
  • Maxime Amblard and Chuyuan Li Linguistic engineering, 20h, L3, Université de Lorraine, France.
  • Hee-Soo Choi, Corpus processing (introduction to Python), 24h, Université de Lorraine, France.
  • Karën Fort, Relational databases, 55h, L3, Sorbonne Université, France.
  • Pierre Ludmann, Informatics 2, 27h, Mines Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Databases, 114h, Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Java project, 16h, Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Year-long project, 20h, Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Mentoring, 40h, Polytech Nancy, Université de Lorraine, France.
  • Valentin Richard, Langages de Scripts, 50h, L3, Université de Lorraine, France.
• Master:
  • Maxime Amblard and Siyana Pavlova, Python Programming, 30h, M1 NLP (IDMC), Université de Lorraine, France.
  • Maxime Amblard and Siyana Pavlova, Methods for NLP, 36h, M1 NLP (IDMC), Université de Lorraine, France.
  • Maxime Amblard, NLP project, 20h, M1 NLP (IDMC), Université de Lorraine, France.
  • Maxime Amblard, Marie Cousin, and Amandine Decker, Formalisms and Syntax, 24h, M2 NLP (IDMC), Université de Lorraine, France.
  • Maxime Amblard and Valentin Richard, Discourse and Dialogue, 18h, M2 NLP (IDMC), Université de Lorraine, France.
  • Maxime Amblard, software project, 10h, M2 NLP (IDMC), Université de Lorraine, France.
  • Marie Cousin, Agile Method and Scrum, 4h, M2 NLP (IDMC), Université de Lorraine, France.
  • Amandine Decker, LaTeX/Shell, 6h, M1 NLP (IDMC), Université de Lorraine, France.
  • Philippe de Groote, Formal Logic, 22h, M1 NLP (IDMC), Université de Lorraine, France.
  • Philippe de Groote, Formal languages, 22h, M1 NLP (IDMC), Université de Lorraine, France.
  • Philippe de Groote, Computational Semantics, 18h, M2 NLP (IDMC), Université de Lorraine, France.
  • Philippe de Groote, Computational structures and logics for natural language modeling, 18h, M2 NLP (IDMC), Université Paris Diderot – Paris 7, France.
  • Karën Fort, Data Ethics, 18h, M1 ISF (Informatique et Statistique financières), Université Panthéon Assas, France.
  • Karën Fort, Ethics and NLP (English), 17h30, M2 NLP (IDMC), Université de Lorraine, France.
  • Karën Fort, Introduction to ethics, 5h, M2 CogSci (IDMC), Université de Lorraine, France.
  • Karën Fort, Formal Grammar, 39h, M1, Sorbonne Université, France.
  • Karën Fort, Corpora, resources and tools for linguistics, 39h, M1, Sorbonne Université, France.
  • Karën Fort, Ethics and NLP, 15h, M2, Sorbonne Université, France.
  • Karën Fort, Ethics and NLP (English), 12h, M1/M2, University of Malta, Malta.
  • Karën Fort, Collaborative annotation for NLP, 30h, M2, Sorbonne Université, France.
  • Karën Fort, Crowdsourcing for NLP, 3h, M2, Nanterre Université, France.
  • Bruno Guillaume, Written Corpora TAL (English), 45h, M1 NLP (IDMC), Université de Lorraine, France.
  • Chuyuan Li, Introduction to G5K (English), 4h, M1 NLP (IDMC), Université de Lorraine, France.
  • Pierre Ludmann, Software Engineering 2, 10h, Mines Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Compilation, 27.5h, Mines Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Department project, 5h, Mines Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Software Engineering, 42h, Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Web project, 6h, Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, End-of-study interships, 20h Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, End-of-study project, 20h Polytech Nancy, Université de Lorraine, France.
  • Pierre Ludmann, Mentoring, 48h, Polytech Nancy, Université de Lorraine, France.
  • Vincent Tourneur, UML beginners (English), 10h, M1 NLP (IDMC), Université de Lorraine, France.
  • Siyana Pavlova, Data Science, 9h, M1 NLP (IDMC), Université de Lorraine, France.
• Doctorate:
  • Karën Fort, Scientific integrity, 6h, École doctorale 5, Faculté des lettres, Sorbonne Université.
  • Karën Fort, Annotation Quality, 4h30, École d'été of the GDR LIFT, 05 2022, Banyuls-sur-Mer, France.
  • Karën Fort, Maxime Amblard, Marc Anderson, Ethics training: write your dystopia, 2 days, 2022-11-03 and 2022-11-04, École doctorale IAEM, Nancy, France.
• International Summer School:
  • Philippe de Groote with Yoad Winter, Introduction to natural language formal semantics, at the 32nd European Summer School in Logic, Language and Information (ESSLLI 2021).

10.2.2 Supervision

• HDR
  • Karën Fort, Myriadisation et éthique pour le traitement automatique des langues. Defended on 2022-11-23 45.
• PhD
  • William Babonnaud, Sémantique lexicale, compositionnalité et coercions. Fondements théoriques des types sémantiques. Defended on 2022-11-22 44.
• PhD in progress
   

  • Samuel Buchel, Linguistic, Semantic and Cognitive Modelling of Dialogical Incongruities and Discontinuities in The Interaction with The Schizophrenic Patients, since 12 2019. Supervision: Maxime Amblard and Michel Musiol.
  • Hee-Soo Choi, Lier des ressources lexicales du français en vue d’une interopérabilité entre niveaux linguistiques, since 10 2021. Supervision: Karën Fort and Mathieu Constant.
  • Marie Cousin, Modélisation de paraphrase dans les grammaires catégorielles abstraites, since 10 2022. Supervision: Philippe de Groote and Sylvain Pogodalla.
  • Amandine Decker, Modelling Topic-level Interaction in Pathological Conversations, since 10 2022. Supervision: Maxime Amblard and Ellen Breitholtz (University of Gothenburg, Sweden).
  • Maxime Guillaume, Structures de traits pour les Grammaires Catégorielles Abstraites, since 07 2021. Supervision: Philippe de Groote and Raphaël Salmon (Yseop).
  • Laurine Jeannot, Robust Semantic and Discourse Analysis of Natural Language System Specifications, from 01 2021 to 10 2022. Supervision: Maxime Amblard and Philippe de Groote.
  • Amandine Lecomte, Analyse longitudinale de prise en charge psychothérapeutique de patients psychiatriques et de patients atteints de maladies neurodégénératives : informatisation et modélisation dialogique des indices comportementaux associés à l’efficacité (vs échec) des stratégies de prise en charge tentées par les thérapeutes, since 10 2019. Supervision: Michel Musiol and Alexandra König.
  • Chuyuan Li, Formal and Statistical Modeling of Dialogue, since 10 2019. Supervision: Maxime Amblard and Chloé Braud (IRIT).
  • Pierre Ludmann, Dynamic Construction of Discursive Structures, since 09 2017. Supervision: Philippe de Groote and Sylvain Pogodalla.
  • Siyana Pavlova, Tools and Methods for Semantic Annotation, since 11 2020. Supervision: Maxime Amblard and Bruno Guillaume.
  • Valentin Richard, Aspects compositionnels et dynamiques de la sémantique inquisitrice, since 09 2021. Supervision: Philippe de Groote and Reinhart Muskens (Universiteit van Amsterdam, ILLC).
  • Priyansh Trivedi, Injecting Lexical and Semantic Knowledge into Word, Phrasal and Sentence Embeddings, since 11 2021. Supervision: Philippe de Groote and Pascal Denis.

10.2.3 Juries

• Karën Fort: member of the PhD jury of Anaëlle Baledent (examiner), "De la complexité de l’annotation manuelle : méthodologie, biais et recommandations", Université de Caen Normandie, 2022-12-1.
• Guy Perrier: reviewer of Rita Hijazi's PhD thesis, "Simplification syntaxique de textes à base de représentations sémantiques exprimées avec DMRS", Université d'Aix-Marseille, 2022-12-14.

10.3.1 Interventions

• Marie Cousin and Amandine Decker: 2022-11-17, presentation to high school students in the context of the "Chiche !" initiative (lycée Saint-Exupéry, Fameck, France).
• Karën Fort: 2022-09-30, Radio Campus France, Têtes Chercheuses podcast: interview on crowdsourcing.
• Karën Fort: 2022-09-30, Nuit européenne des Chercheurs in Nancy: impro lab with the Crache-Texte company "Le miroir virtuel : La société face aux algorithmes".
• Valentin Richard gave a talk 46 at LORIA's PhD Seminar on 2022-10-5.

International journals

• 8 articleM. M.Marc M Anderson and K.Karën Fort. From the Ground Up: Developing a Practical Ethical Methodology for Integrating AI into Industry. AI & Society: Knowledge, Culture and CommunicationJuly 2022
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• 9 articleM.Marc Anderson and K.Karën Fort. Human Where? A New Scale Defining Human Involvement in Technology Communities from an Ethical Standpoint.International Review of Information EthicsAugust 2022
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• 10 articleA.Alexandra König, P.Philipp Müller, J.Johannes Tröger, H.Hali Lindsay, J.Jan Alexandersson, J.Jonas Hinze, M.Matthias Riemenschneider, D.Danilo Postin, E.Eric Ettore, A.Amandine Lecomte, M.Michel Musiol, M.Maxime Amblard, R.Rene Hurlemann, F. F.Francois F Bremond and M.Michal Balazia. Multimodal phenotyping of psychiatric disorders from social interaction: Protocol of a clinical multicenter prospective study.Personalized Medicine in Psychiatry33-34July 2022, 100094
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• 11 articleM.Michel Musiol, M.Manuel Rebuschi, S.Samuel Buchel, A.Amandine Lecomte, P.Philippe de Groote and M.Maxime Amblard. The Issue of the Analysis of Thought Disorders in the Discourse of Schizophrenic Subjects: A Methodological Proposition.L'Évolution Psychiatrique872April 2022, 347-369
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• 12 articleR.Robert Reinecke, T. A.Tatjana A Nazir, S.Sarah Carvallo and J.Jacques Jayez. Factives at hand: When presupposition mode affects motor response.Journal of Experimental Psychology1519September 2022, 2173-2194
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International peer-reviewed conferences

• 13 inproceedingsM.Maxime Amblard, B.Bruno Guillaume, S.Siyana Pavlova and G.Guy Perrier. Graph Querying for Semantic Annotations.ISA 2022 : 18th Joint ACL - ISO Workshop on Interoperable Semantic AnnotationMarseille, FranceJune 2022
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• 14 inproceedingsM. M.Marc M Anderson and K.Karën Fort. Ethical Internal Logistics 4.0: Observations and Suggestions from a Working Internal Logistics Case.12th International Workshop on Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the FutureBucarest, RomaniaSeptember 2022
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• 15 inproceedingsBest paperM. M.Marc M Anderson. Some Ethical Reflections on the EU AI Act.CEUR Workshop ProceedingsIAIL 2022: 1st International Workshop on Imagining the AI Landscape After the AI Act3221Amsterdam, NetherlandsSeptember 2022
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• 16 inproceedingsT.Tatiana Anikina, N.Natalia Skachkova, J.Joseph Renner and P.Priyansh Trivedi. Anaphora Resolution in Dialogue: System Description (CODI-CRAC 2022 Shared Task).CODI-CRAC 2022Gyeongju, South KoreaOctober 2022
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• 17 inproceedingsM.Maria Boritchev and M.Maxime Amblard. A Multi-Party Dialogue Ressource in French.LREC 2022 - 13th Edition of Language Resources and Evaluation ConferenceMarseille, FranceJune 2022
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• 18 inproceedingsH.Harry Bunt, M.Maxime Amblard, J.Johan Bos, K.Karën Fort, P.Philippe de Groote, B.Bruno Guillaume, C.Chuyuan Li, P.Pierre Ludmann, M.Michel Musiol, S.Siyana Pavlova, G.Guy Perrier and S.Sylvain Pogodalla. Quantification Annotation in ISO 24617-12, Second Draft.Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022)Marseille, FranceEuropean Language Resources AssociationJune 2022, 3407--3416
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• 19 inproceedingsH.-S.Hee-Soo Choi, B.Bruno Guillaume and K.Karën Fort. Corpus-based Language Universals Analysis using Universal Dependencies.SyntaxFest Quasy 2021 - Quantitative SyntaxProceedings of the Second Workshop on Quantitative Syntax (Quasy, SyntaxFest 2021)Sofia, BulgariaMarch 2022
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• 20 inproceedingsF.Fanny Ducel, K.Karën Fort, G.Gaël Lejeune and Y.Yves Lepage. Do we Name the Languages we Study? The #BenderRule in LREC and ACL articles.LREC 2022 - International Conference on Language Resources and Evaluation (LREC)Marseille, FranceJune 2022
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• 21 inproceedingsK.Karën Fort, A.Aurélie Névéol, Y.Yoann Dupont and J.Julien Bezançon. Use of a Citizen Science Platform for the Creation of a Language Resource to Study Bias in Language Models for French: a case study.2nd LREC Workshop on Novel Incentives in Data Collection from PeopleMarseille, FranceJune 2022
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• 22 inproceedingsK.Kim Gerdes, B.Bruno Guillaume, S.Sylvain Kahane and G.Guy Perrier. Starting a new treebank? Go SUD! Theoretical and practical benefits of the Surface-Syntactic distributional approach.SyntaxFest Depling 2021 - 6th International Conference on Dependency LinguisticsSofia, BulgariaMarch 2022
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• 23 inproceedingsG.Giuseppe Greco, M.Michael Moortgat, V. D.Valentin D. Richard and A.Apostolos Tzimoulis. Lambek-Grishin Calculus: focusing, display and full polarization.Topology, Algebra, and Categories in Logic (TACL 2022)Coimbra, PortugalJune 2022, 79-81
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• 24 inproceedingsP.Philippe de Groote. Deriving formal semantic representations from dependency structures.Proceedings of the 19th International Workshop of Logic and Engineering of Natural Language Semantics 19 (LENLS19LENLS19 - Logic and Engineering of Natural Language Semantics 19Tokyo, JapanNovember 2022, 87-91
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• 25 inproceedingsN.Nicolas Hiebel, O.Olivier Ferret, K.Karën Fort and A.Aurélie Névéol. CLISTER: A corpus for semantic textual similarity in French clinical narratives.LREC 2022 - 13th Language Resources and Evaluation Conference2022LREC 2022 - Proceedings of the 13th Conference on Language Resources and EvaluationMarseille, FranceEuropean Language Resources Association2022, 4306‑4315
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• 26 inproceedingsS.Sylvain Kahane, M.Martine Vanhove, R.Rayan Ziane and B.Bruno Guillaume. A morph-based and a word-based treebank for Beja.SyntaxFestTLT 2021 - 20th International Workshop on Treebanks and Linguistic TheoriesSofia, Bulgaria2021
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• 27 inproceedingsA.Amandine Lecomte, S.Samuel Buchel, N.Nicolas Franck, C.Caroline Demily, M.Maxime Amblard and M.Michel Musiol. Organisations et fonctions du comportement verbal de type “backchannels” dans l’interaction clinique avec la personne souffrant de schizophrénie.8eme Congrès mondial de linguistique françaiseOrléans, FranceJuly 2022
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• 28 inproceedingsC.Chuyuan Li, C.Chloé Braud and M.Maxime Amblard. Multi-Task Learning for Depression Detection in Dialogs.à paraître23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2022)Edinbourg, United KingdomSeptember 2022, 1-8
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• 29 inproceedingsP.Pierre Ludmann, S.Sylvain Pogodalla and P.Philippe de Groote. Multityped Abstract Categorial Grammars and Their Composition.WoLLIC 2022 - 28th International Workshop on Logic, Language, Information, and Computation13468Lecture Notes in Computer ScienceIaşi, RomaniaSpringer International PublishingSeptember 2022, 105-122
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• 30 inproceedingsE.Esteban Marquer, S.Safa Alsaidi, A.Amandine Decker, P.-A.Pierre-Alexandre Murena and M.Miguel Couceiro. A Deep Learning Approach to Solving Morphological Analogies.Lecture Notes in Computer Science30th International Conference on Case-Based Reasoning (ICCBR2022)Nancy, FranceSpringerSeptember 2022, 159--174
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• 31 inproceedingsA.Aurélie Névéol, Y.Yoann Dupont, J.Julien Bezançon and K.Karën Fort. French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English.ACL 2022 - 60th Annual Meeting of the Association for Computational LinguisticsDublin, IrelandMay 2022
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• 32 inproceedings S.Siyana Pavlova, M.Maxime Amblard and B.Bruno Guillaume. How much of UCCA can be predicted from AMR? ISA 2022 : 18th Joint ACL - ISO Workshop on Interoperable Semantic Annotation Marseille, France June 2022
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• 33 inproceedingsV. D.Valentin D. Richard. Simulating Feature Structures with Simple Types.Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research WorkshopProceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research WorkshopHybrid: Seattle, United StatesAssociation for Computational LinguisticsJuly 2022, 113-122
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National peer-reviewed Conferences

• 34 inproceedingsH.-S.Hee-Soo Choi. State of the art : Linking French Lexical Resources.TALN + RECITAL 2022 - 29e Conférence sur le Traitement Automatique des Langues Naturelles. 24e Rencontres Etudiants Chercheurs en Informatique pour le pour le Traitement Automatique des Langues (RECITAL)Avignon, France2022, 55-68
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• 35 inproceedingsF.Fanny Ducel, K.Karën Fort, G.Gaël Lejeune and Y.Yves Lepage. Contrastive and diachronic study of unmentioned (by default ?) languages in TALN and ACL.Conférence sur le Traitement Automatique des Langues Naturelles (TALN)Avignon, FranceJune 2022
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• 36 inproceedingsK.Karën Fort. Éthique et TAL : ce dont on parle, ce dont on ne parle plus, ce dont on ne parle pas (un état de l'art).LIFT TAL 2022 - Journées Jointes des Groupements de Recherche « Linguistique Informatique, Formelle et de Terrain » et « Traitement Automatique des Langues »Marseille, FranceNovember 2022
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• 37 inproceedingsS.Santiago Herrera, S.Sylvain Kahane and B.Bruno Guillaume. Grammar rules extraction from treebanks : a tool and some first results.Actes des journées jointes des Groupements de Recherche Linguistique Informatique, Formelle et de Terrain (LIFT) et Traitement Automatique des Langues (TAL).Journées Jointes des Groupements de Recherche Linguistique Informatique, Formelle et de Terrain (LIFT) et Traitement Automatique des Langues (TAL)Marseille, FranceCNRS2022, 93-98
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• 38 inproceedingsN.Nicolas Hiebel, O.Olivier Ferret, K.Karën Fort and A.Aurélie Névéol. CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives.Conférence sur le Traitement Automatique des Langues Naturelles (TALN)Avignon, FranceJune 2022
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• 39 inproceedingsA.Alice Millour, Y.Yoann Dupont, A.Alexane Jouglar and K.Karën Fort. FENEC : a balanced sample corpus for French named entity recognition.Conférence sur le Traitement Automatique des Langues Naturelles (TALN)Avignon, FranceJune 2022
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• 40 inproceedingsA.Aurélie Névéol, Y.Yoann Dupont, J.Julien Bezançon and K.Karën Fort. French CrowS-Pairs : Extending a challenge dataset for measuring social bias in masked language models to a language other than English.Conférence sur le Traitement Automatique des Langues Naturelles (TALN)Avignon, FranceJune 2022
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Conferences without proceedings

• 41 inproceedings M. M.Marc M Anderson. Is the Future of AI Ethics Interdisciplinary? Where AI Ethics Should Go Tubingen, Germany June 2022
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• 42 inproceedingsP.Philippe de Groote. Ty2 revisited.HyLo 2022 — Workshop on Hybrid Logic and ApplicationsChania, GreeceApril 2022
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• 43 inproceedingsV. D.Valentin D. Richard. Introducing Proof Tree Automata and Proof Tree Graphs: Extended abstract.SLSS 2022 - 11th Scandinavian Logic SymposiumBergen, NorwayJune 2022, 10-12
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Doctoral dissertations and habilitation theses

• 44 thesisW.William Babonnaud. Lexical Semantics, compositionality and coercions. Theoretical foundations of semantic types.Université de LorraineNovember 2022
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• 45 thesisK.Karën Fort. Crowdsourcing and ethics for Natural Language Processing.ED n°77 : Informatique - Automatique - Électronique - Électrotechnique - Mathématiques de Lorraine (IAEM-Lorraine)November 2022
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Reports & preprints

• 46 miscV. D.Valentin D. Richard. Is Natural Language Processing (NLP) Going in the Right Direction?: Getting started with NLP ethics.October 2022
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Other scientific publications

• 47 thesisM.Marie Cousin. Text generation with abstract categorial grammars and the meaning-text theory.Grenoble INP EnsimagVandoeuvre-les -NancySeptember 2022, 69
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