6.1.1 ProvSQL

• Keywords:
  Databases, Provenance, Probability
• Functional Description:
  The goal of the ProvSQL project is to add support for (m-)semiring provenance and uncertainty management to PostgreSQL databases, in the form of a PostgreSQL extension/module/plugin.
• News of the Year:
  Revamp of the implementation of the circuit storage, now stored in memory-mapped files accessed through a single worked process. Addition of a local circuit cache within each PostgreSQL backend. Implementation of expected value computation. Implementation of union of intervals semiring. Support for provenance tracking of deletions. Drop support for PostgreSQL 9.6. Support for PostgreSQL 17. Mac OS and WSL continuous integration. Various optimizations, bug fixes, and robustness enhancements.
• URL:
  https://­github.­com/­PierreSenellart/­provsql
• Publications:
  hal-01672566, hal-01851538, hal-04561331
• Contact:
  Pierre Senellart
• Participant:
  Pierre Senellart

6.1.2 apxproof

• Keyword:
  LaTeX
• Functional Description:
  apxproof is a LaTeX package facilitating the typesetting of research articles with proofs in appendix, a common practice in database theory and theoretical computer science in general. The appendix material is written in the LaTeX code along with the main text which it naturally complements, and it is automatically deferred. The package can automatically send proofs to the appendix, can repeat in the appendix the theorem environments stated in the main text, can section the appendix automatically based on the sectioning of the main text, and supports a separate bibliography for the appendix material.
• Release Contributions:
  Support for lipcs's claimproof, support optional arguments in proofs
• News of the Year:
  Support for user-defined claimproof environment.
• URL:
  https://­github.­com/­PierreSenellart/­apxproof
• Contact:
  Pierre Senellart
• Participant:
  Pierre Senellart

6.1.3 dissem.in

• Name:
  Dissemin
• Keywords:
  Open Access, Publishing, HAL
• Functional Description:
  Dissemin is a web platform gathering metadata from many sources to analyze the open-access full text availability of publications of researchers. It has been designed to foster the use of repositories such as HAL (rather than preprints posted on personal homepages). It allows deposit on these repositories.
• News of the Year:
  Finalization of crossref ingestion.
• URL:
  https://­gitlab.­com/­dissemin/­dissemin
• Contact:
  Pierre Senellart
• Participant:
  Pierre Senellart
• Partner:
  CAPSH

Knowledge representation and knowledge bases

Ontology-based query answering is a problem that takes as input an ontology $ℛ$ (in our context, a set of existential rules), a set $ℱ$ of facts, and a Boolean conjunctive query (CQ) $q$, and asks whether $q$ follows from $(ℛ,ℱ)$ under standard first-order semantics. This problem is undecidable in general, and a widely investigated approach to tackle it in some cases is query rewriting: given a “rule query” $(ℛ,q)$, we compute a Boolean query $q^{\text{'}}$ such that, for any fact set $ℱ$, it holds that $q$ follows from $(ℛ,ℱ)$ if and only if $q^{\text{'}}$ follows from $ℱ$. Insofar, previous work has mostly focused on output queries $q^{\text{'}}$ expressed as union of Boolean conjunctive queries (UCQs), and an effective algorithm that computes such a query $q^{\text{'}}$ whenever it exists has been proposed in the literature. However, UCQ-rewritability is not a very general notion and many real-world interesting rule queries do no admit UCQ-rewritings. This raises the question whether such a generic algorithm can be designed for a more expressive target language, such as datalog. We solve this question in 20 by the negative, by studying the difference between datalog-expressibility and datalog-rewritability. More precisely, we show that query answering under datalog-expressible rule queries is undecidable.

Research on knowledge graph embeddings has recently evolved into knowledge base embeddings, where the goal is not only to map facts into vector spaces but also constrain the models so that they take into account the relevant conceptual knowledge available. 19 examines recent methods that have been proposed to embed knowledge bases in description logic into vector spaces through the lens of their geometric-based semantics. We identify several relevant theoretical properties, which we draw from the literature and sometimes generalize or unify. We then investigate how concrete embedding methods fit in this theoretical framework.

Consistent query answering

In 25, we consider the dichotomy conjecture for consistent query answering under primary key constraints. It states that, for every fixed Boolean conjunctive query $q$, testing whether $q$ is certain (i.e. whether it evaluates to true over all repairs of a given inconsistent database) is either PTime or CoNP-complete. This conjecture has been verified for self-join-free and path queries. We show that it also holds for queries with two atoms.

Other aspects of theoretical computer science

Our research occasionally touches other aspects of theoretical computer science not related to data management. In 11, we show how to efficiently solve problems involving a quantitative measure, here called energy, as well as a qualitative acceptance condition, expressed as a Büchi or Parity objective, in finite weighted automata and in one-clock weighted timed automata. Solving the former problem and extracting the corresponding witness is our main contribution and is handled by a modified version of the Bellman-Ford algorithm interleaved with Couvreur’s algorithm. The latter problem is handled via a reduction to the former relying on the corner-point abstraction.

Inconsistent knowledge bases

In 15, we explore a quantitative approach to querying inconsistent description logic knowledge bases. We consider weighted knowledge bases in which both axioms and assertions have (possibly infinite) weights, which are used to assign a cost to each interpretation based upon the axioms and assertions it violates. Two notions of certain and possible answer are defined by either considering interpretations whose cost does not exceed a given bound or restricting attention to optimal-cost interpretations. Our main contribution is a comprehensive analysis of the combined and data complexity of bounded cost satisfiability and certain and possible answer recognition, for description logics between $\mathrm{ℰℒ}\perp$ and $\mathrm{𝒜ℒ𝒞𝒪}$.

In 16, we present a novel approach to querying classical inconsistent description logic (DL) knowledge bases by adopting a paraconsistent semantics with the four “Belnapian” values: exactly true, exactly false, both, and neither. In contrast to prior studies on paraconsistent DLs, we allow truth value operators in the query language, which can be used to differentiate between answers having contradictory evidence and those having only positive evidence. We present a reduction to classical DL query answering that allows us to pinpoint the precise combined and data complexity of answering queries with values in paraconsistent $\mathrm{𝒜ℒ𝒞\mathscr{H}ℐ}$ and its sublogics. Notably, we show that tractable data complexity is retained for Horn DLs. We present a comparison with repair-based inconsistency-tolerant semantics, showing that the two approaches are incomparable.

Provenance management and probabilistic databases

In 26, we report on the impact that the theory of provenance semirings, developed by Val Tannen and his collaborators, has had on the design on a practical system for maintaining the provenance of query results over a relational database, namely ProvSQL.

Shapley values, originating in game theory and increasingly prominent in explainable AI, have been proposed to assess the contribution of facts in query answering over databases, along with other similar power indices such as Banzhaf values. In 12 we adapt these Shapley-like scores to probabilistic settings, the objective being to compute their expected value. We show that the computations of expected Shapley values and of the expected values of Boolean functions are interreducible in polynomial time, thus obtaining the same tractability landscape. We investigate the specific tractable case where Boolean functions are represented as deterministic decomposable circuits, designing a polynomial-time algorithm for this setting. We present applications to probabilistic databases through database provenance, and an effective implementation of this algorithm within the ProvSQL system, which experimentally validates its feasibility over a standard benchmark.

Mining time series

Anomaly detection is an important problem in data analytics with applications in many domains. In recent years, there has been an increasing interest in anomaly detection tasks applied to time series. In two tutorials at two separate conferences 13, 17, we take a holistic view of anomaly detection in time series, starting from the core definitions and taxonomies related to time series and anomaly types, to an extensive description of the anomaly detection methods proposed by different communities in the literature. We explore the literature and the proposed methods by demonstrating systems that help users understand the core computational steps of some methods and navigate benchmark results. Finally, we describe the problem of model selection for anomaly detection and discuss recent experimental results.

Despite increasing academic interest in anomaly detection over time series and the large number of methods proposed in the literature, recent benchmark and evaluation studies demonstrated that there exists no single best anomaly detection method when applied to heterogeneous time series datasets. Therefore, the only scalable and viable solution to solve anomaly detection over very different time series collected from diverse domains is to propose a model selection method that will choose, based on time series characteristics, the best anomaly detection method to run. 18 describes ADecimo, a modular and extensible web application that helps users understand the performance of time series classification algorithms used as model selection methods for time series anomaly detection. Overall, our system enables users to compare 17 different classifiers over 1980 time series, and decide on the most suitable time series classification method for their own time series and use cases.

Beyond anomaly detection, exploring and comparing non-stationary multivariate time series is an important problem in many domains and real-world applications. In work conducted before Paul Boniol 's arrival in Valda, we introduced $d_{\mathrm{symb}}$, a symbolic representation that transforms multivariate time series into interpretable symbolic sequences that come along with a compatible and efficient distance measure to compare the obtained symbolic sequences. We have shown how $d_{\mathrm{symb}}$ can handle the non-stationarity of multivariate physiological signals, how interpretable the symbolization is, and how suitable the distance measure is compared to Dynamic Time Warping (DTW) variants. We have also empirically shown that the computation time when using $d_{\mathrm{symb}}$ on a clustering time is significantly smaller than with DTW variants (typically 100 times faster). In 21, we present the $d_{\mathrm{symb}}$ playground, an interactive web-based tool to interpret and compare a large multivariate time series dataset quickly. We showcase the relevance of this tool in several scenarios based on real-world datasets.

Information extraction and structuring

22 describes Antoine Gauquier 's PhD project, which aims to study holistic methods for building, populating, and exploiting warehouses of heterogeneous content. Each warehouse is characterized by a specification of the types of content we search for; a set of websites in which to search for the content; a set of dedicated methods to analyze and understand the content, including to establish or find links that connect different pieces of content. AI and uncertainty are naturally involved in these steps. We present the overall thesis aims, as well as encouraging preliminary results for one use case: the acquisition of statistical data resources from French government websites, leveraging reinforcement learning.

23 explores first steps towards extracting information about theorems and proofs from scholarly documents to build a knowledge base of interlinked results. Specifically, we consider two main tasks: extractions of results and their proofs from the PDF of scientific articles; and establishing which results is used in the proof of which, across the scientific literature. We discuss the problem statement, methodologies, as well as preliminary findings employed in both phases of our approach, highlighting the challenges faced.

More specifically, in 24, 28 we address the extraction of mathematical statements and their proofs from scholarly PDF articles as a multimodal classification problem, utilizing text, font features, and bitmap image renderings of PDFs as distinct modalities. We propose a modular sequential multimodal machine learning approach specifically designed for extracting theorem-like environments and proofs. This is based on a cross-modal attention mechanism to generate multimodal paragraph embeddings, which are then fed into our novel multimodal sliding window transformer architecture to capture sequential information across paragraphs. Our approach demonstrates performance improvements obtained by transitioning from unimodality to multimodality, and finally by incorporating sequential modeling over paragraphs.

8.1.1 Participation in other International Programs

8.2.1 Visits of international scientists

8.2.2 Visits to international teams

8.3.1 ANR

Valda has been part of two national ANR projects in 2024:

• CQFD
  (2018–2024; 19 k€ for Valda, budget managed by Inria), with Inria Sophia (GraphIK, coordinator), LaBRI, LIG, Inria Saclay (Cedar), IRISA, Inria Lille (Spirals), and Télécom ParisTech, on complex ontological queries over federated and heterogeneous data.
• QUID
  (2018–2024; 49 k€ for Valda, budget managed by Inria), LIGM (coordinator), IRIF, and LaBRI, on incomplete and inconsistent data.

Camille Bourgaux has been participating in the AI Chair of Meghyn Bienvenu on INTENDED (Intelligent handling of imperfect data) since 2020.

Pierre Senellart held a chair within the PR[AI]RIE institute for artificial intelligence in Paris since 2019. He now holds a chair in the new PR[AI]RIE – Paris School of AI (PSAI) AI cluster approved for funding from 2024. Camille Bourgaux is also a Research Fellow of PSAI.

8.3.2 Others

• Dissemin
  (2021–2024; 124 k€ for Valda, budget managed by ENS), sole partner, on the development of the dissem.in platform for open science promotion. Funded by the Fonds National Science Ouverte.

9.1.1 Scientific events: organisation

9.1.2 Invited talks

• Camille Bourgaux , Querying inconsistent prioritized data, invited talk at DL 2024 (June 2024, Bergen, Norway) 14
• Pierre Senellart , Provenance, Probabilities, and Power Indices in Databases, department seminar at ENS Paris-Saclay (March 2024, Gif-sur-Yvette, France)
• Paul Boniol ,Anomaly Detection in Time Series, keynote for AALTD workshop at ECML/PKDD 2024 (September 2024, Vilnius, Lithuania)
• Camille Bourgaux , Querying inconsistent databases, department seminar at ENS Rennes (October 2024, Bruz, France)
• Paul Boniol , Time Series Anomaly Detection: Overview and New Trends, Keynote for ML4Jets International Conference (November 2024, Paris France)
• Pierre Senellart , Qu'est-ce que l'IA ?, keynote at Assemblée des partenaires de Hal (November 2024, Lyon, France)

9.1.3 Leadership within the scientific community

• Serge Abiteboul is a member of the French Academy of Sciences, of the Academia Europaea, and an ACM Fellow.
• Pierre Senellart is a junior member of the Institut Universitaire de France.

9.1.4 Research administration

• Serge Abiteboul was a member of the jury for prizes of the Académie des Sciences: Computer science (president), Lovelace-Babbage, Mines-Télécom
• Serge Abiteboul was a member of the commission of new member of Académie des Sciences
• Serge Abiteboul is a member of the scientific committe of the Programme Inria Quadrant (PIQ)
• Luc Segoufin is a member of the Formation Spécialisée de Site (FSS) of the Inria Paris research centre.
• Pierre Senellart is the president of section 6 of the National Committee for Scientific Research. As a representative of CoNRS, Pierre Senellart was in the Hcéres evaluation committee of the LMF research unit.
• Pierre Senellart is a member of the board of the conference of presidents of the national committee (CPCN) and as such a member of the coordination of managing parties of the national committee (C3N).
• Pierre Senellart is deputy director of the DI ENS laboratory, joint between ENS, CNRS, and Inria.
• Pierre Senellart is the scientific resource person for Scientific information & edition of the Inria Paris centre
• We participated in the following hiring and promotion juries within universities:
  • Serge Abiteboul , Professeur, CNAM
  • Camille Bourgaux , Maître de conférences, IUT d'Orsay
  • Pierre Senellart , Repyramidage Professeur des Universités, Université Paris-Cité
  • Michaël Thomazo , Maître de conférences, Université de Bordeaux
  • Michaël Thomazo , Maître de conférences, CentraleSupélec

9.2.1 Teaching

• Licence: Algorithms, L1, CPES, PSL – Antoine Gauquier
• Licence: Differential calculus, L2, CPES, PSL – Antoine Gauquier
• Licence: Practical Computing, L3, École normale supérieure – Pierre Senellart
• Licence: Formal Languages, Computability, Complexity, L3, École normale supérieure – Michaël Thomazo , Lucas Larroque

• Licence: Databases, L3, École normale supérieure – Pierre Senellart , Lucas Larroque

• Master: Logiques de description, M1, DCI – Camille Bourgaux
• Master: Data Acquisition, Extraction, and Storage, M2, IASD – Pierre Senellart
• Master: NoSQL Databases, M2, IASD – Paul Boniol
• Master: Knowledge graphs, description logics, and reasoning on data, M2, IASD – Camille Bourgaux , Michaël Thomazo

• Master: Description logics and reasoning on data, M2, LMFI – Camille Bourgaux , Michaël Thomazo

• Professional training: Web Security, PESTO (Corps des Mines professional training) – Pierre Senellart

As a professor at ENS, Pierre Senellart holds various teaching responsibilities (M1 projects, M2 administration, entrance competition) at ENS. Pierre Senellart is the academic director of the graduate program of PSL.

As an adjunct professor at PSL, Michaël Thomazo is in charge of PhD committees within DI ENS and co-responsible of the international entrance competition at ENS.

We also gave invited courses in summer schools:

• Paul Boniol , Time Series Anomaly Detection, International Summer School on Internet of Things - ISSIOT, Salerno, Italy
• Paul Boniol , Time Series Anomaly Detection, diiP Summer School 2024 – dSDS, Paris, France
• Michaël Thomazo , Summer School of Palacky University, Olomouc, Czechia

Most permanent members of the group are also involved in tutoring ENS students, advising them on their curriculum, their internships, etc. They are also occasionally involved with reviewing internship reports, supervising student projects, etc.

9.2.2 Supervision

• PhD defended: Shrey Mishra , Multimodal extraction of proofs and theorems from the scientific literature, 2021–2024, Pierre Senellart27
• PhD in progress: Anatole Dahan, Logical foundations of the polynomial hierarchy, started in October 2020, Arnaud Durand (Université Paris-Cité) & Luc Segoufin
• PhD in progress: Antoine Gauquier , Intelligent construction of a multimodal and heterogeneous data warehouse, with data traceability, started in September 2023, Pierre Senellart & Ioana Manolescu (Inria Cedar)
• PhD in progress: Lucas Larroque , Extension of rewriting procedures for reasoning using existential rules, started in September 2023, Michaël Thomazo
• PhD in progress: Robin Jean , Integration of preferences and domain knowledge in inconsistency-tolerant ontology-based data access, started in October 2023, Meghyn Bienvenu (CNRS LaBRI) & Camille Bourgaux
• PhD in progress: Aryak Sen , Scalability of a data provenance and probability management system, started in February 2024, Silviu Maniu (Université Grenoble Alpes) & Pierre Senellart
• PhD in progress: Emmanouil Sylligardos , Accuracy and execution time trade-off in ensembling and model selection for time series analytics., started in February 2024, Paul Boniol & Pierre Senellart
• PhD in progress: Felix Chavelli , Graph representations for multivariate time series analytics, started in October 2024, Paul Boniol & Michaël Thomazo
• PhD in progress: Pratik Karmakar, Quality, uncertainty, and lineage of data, Stéphane Bressan (NUS) & Pierre Senellart (as he is based in Singapore, he is not considered a Valda member)
• M2 internship: Atefe Khodadaditaghanaki , Camille Bourgaux
• M2 internship: Haoming Lin , Paul Boniol & Michaël Thomazo
• M2 internship: Marijan Soric , Cécile Gracianne (BRGM), Ioana Manolescu (Inria Cedar) & Pierre Senellart
• L2 internship: Leo Boullot , Antoine Gauquier & Pierre Senellart
• L2 internship: Paul Sevestre , Antoine Gauquier & Pierre Senellart
• L2 internship: Julie Zhan , Michaël Thomazo

9.2.3 Juries

• PhD: Edwige Cyffers [president], Université de Lille, Pierre Senellart
• PhD: Florent Martin-Lafay, Université Paris 1 Panthéon-Sorbonne, Serge Abiteboul
• PhD: Alexandra Rogova, Université Paris-Cité, Michaël Thomazo
• HdR: Pierre Bourhis [president & examiner], Université de Lille, Pierre Senellart & Serge Abiteboul
• HdR: Charles Paperman [reviewer], Université de Lille, Pierre Senellart

9.3.1 Specific official responsibilities in science outreach structures

• Serge Abiteboul is the president of the scientific council of the direction of public finances (DGFIP)
• Serge Abiteboul is a member of the board of the Inria Foundation, of the Sopra Steria Foundation, of the Blaise Pascal Foundation
• Serge Abiteboul is a member of the scientific council of La Main à la Pâte, Cigref (on responsible digitalization); he was a member of the scientific council of the exhibition on IA “Double Je” in Toulouse in February 2024
• Pierre Senellart is a scientific expert advising the Scientific and Ethical Committee of Parcoursup and MonMaster, the platforms for the selection of higher-education students at the first-year level and the Master's level. As such, he contributed to the 6th yearly report of the committee to the French parliament

9.3.2 Productions (articles, videos, podcasts, serious games, ...)

• Serge Abiteboul is an editor of the binaire blog
• Serge Abiteboul is the co-author (with François Bancilhon) of a popularization book on digital commons: Vive les communs numériques, Odile Jacob, février 2024

9.3.3 Participation in Live events

• Serge Abiteboul is one of the author of the “Qui a hacké Garoutzia” play, which was staged at various occasions througout France in 2024, and which has had regular performance in Paris at La Scène parisienne since September 2024
• Serge Abiteboul participated in numerous (several dozens) scientific outreach activities: lectures, round tables, interviews (notably with the Académie des sciences; on the radio or on TV; and in many other settings)
• Camille Bourgaux participated to the RJMI (Rendez-Vous des Jeunes Mathématiciennes et Informaticiennes), an invent to promote mathematics and computer science to high-school female students

International journals

• 11 articleS.Sven Dziadek, U.Uli Fahrenberg and P.Philipp Schlehuber. ω-Regular Energy Problems.Formal Aspects of ComputingJuly 2024. In press. HALDOIback to text
• 12 articleP.Pratik Karmakar, M.Mikaël Monet, P.Pierre Senellart and S.Stéphane Bressan. Expected Shapley-Like Scores of Boolean Functions: Complexity and Applications to Probabilistic Databases.Proceedings of the ACM on Management of Data22 (PODS)January 2024HALDOIback to text
• 13 articleQ.Qinghua Liu, P.Paul Boniol, T.Themis Palpanas and J.John Paparrizos. Time-Series Anomaly Detection: Overview and New Trends.Proceedings of the VLDB Endowment (PVLDB)17122024, 4229-4232HALDOIback to text

Invited conferences

• 14 inproceedingsC.Camille Bourgaux. Querying Inconsistent Prioritized Data.DL 2024 - 37th International Workshop on Description LogicsBergen, NorwayJune 2024HALback to text

International peer-reviewed conferences

• 15 inproceedingsM.Meghyn Bienvenu, C.Camille Bourgaux and R.Robin Jean. Cost-Based Semantics for Querying Inconsistent Weighted Knowledge Bases.Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningKR 2024 - 21st International Conference on Principles of Knowledge Representation and ReasoningHanoi, VietnamNovember 2024HALback to text
• 16 inproceedingsM.Meghyn Bienvenu, C.Camille Bourgaux and D.Daniil Kozhemiachenko. Queries With Exact Truth Values in Paraconsistent Description Logics.Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningKR 2024 - 21st International Conference on Principles of Knowledge Representation and ReasoningHanoi, VietnamNovember 2024HALback to text
• 17 inproceedingsP.Paul Boniol, J.John Paparrizos and T.Themis Palpanas. An Interactive Dive into Time-Series Anomaly Detection.ICDE 2024 - 40th International Conference on Data EngineeringUtrecht, NetherlandsMay 2024HALback to text
• 18 inproceedingsP.Paul Boniol, E.Emmanouil Sylligardos, J.John Paparrizos, P.Panos Trahanias and T.Themis Palpanas. ADecimo: Model Selection for Time Series Anomaly Detection.ICDE 2024 - IEEE 40th International Conference on Data EngineeringUtrecht, NetherlandsMay 2024HALback to textback to text
• 19 inproceedingsC.Camille Bourgaux, R.Ricardo Guimarães, R.Raoul Koudijs, V.Victor Lacerda and A.Ana Ozaki. Knowledge Base Embeddings: Semantics and Theoretical Properties.Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningKR 2024 - 21st International Conference on Principles of Knowledge Representation and ReasoningHanoi, VietnamNovember 2024HALback to text
• 20 inproceedingsD.David Carral, L.Lucas Larroque and M.Michaël Thomazo. Ontology-Based Query Answering over Datalog-Expressible Rule Sets is Undecidable.KR 2024 - 21st International Conference on Principles of Knowledge Representation and ReasoningHanoi, VietnamNovember 2024HALback to text
• 21 inproceedingsS. W.Sylvain W Combettes, P.Paul Boniol, C.Charles Truong and L.Laurent Oudre. d_symb playground: an interactive tool to explore large multivariate time series datasets.ICDE 2024 IEEE 40th International Conference on Data EngineeringUtrecht, NetherlandsMay 2024HALback to text
• 22 inproceedingsA.Antoine Gauquier. Towards Efficient Construction of a Traceable, Multimodal, and Heterogeneous Data Warehouse.CEUR Workshop ProceedingsVLDB 2024 PhD Workshop - The 50th International Conference on Very Large Data BasesGuangzhou, ChinaAugust 2024HALback to text
• 23 inproceedingsS.Shrey Mishra, Y.Yacine Brihmouche, T.Theo Delemazure, A.Antoine Gauquier and P.Pierre Senellart. First Steps in Building a Knowledge Base of Mathematical Results.SDP Fourth Workshop on Scholarly Document Processing at ACL 2024Bangkok, ThailandAugust 2024HALback to text
• 24 inproceedingsS.Shrey Mishra, A.Antoine Gauquier and P.Pierre Senellart. Modular Multimodal Machine Learning for Extraction of Theorems and Proofs in Long Scientific Documents.JCDL 2024 - ACM/IEEE-CS Joint Conference on Digital LibrariesHong Kong, ChinaDecember 2024HALDOIback to text
• 25 inproceedingsA.Anantha Padmanabha, L.Luc Segoufin and C.Cristina Sirangelo. A Dichotomy in the Complexity of Consistent Query Answering for Two Atom Queries With Self-Join.PODS'24 - ACM Conference on Principle of Database Systems22Santiago, ChileMay 2024, 1-15HALDOIback to text

Scientific book chapters

• 26 inbookP.Pierre Senellart. On the Impact of Provenance Semiring Theory on the Design of a Provenance-Aware Database System.The Provenance of Elegance in Computation — Essays Dedicated to Val TannenOpenAccess Series in InformaticsSchloss Dagstuhl2024HALDOIback to text

Doctoral dissertations and habilitation theses

• 27 thesisS.Shrey Mishra. Multimodal Extraction of Proofs and Theorems from the Scientific Literature.Université Paris Sciences & LettresJuly 2024HALback to text

Reports & preprints

• 28 miscS.Shrey Mishra, A.Antoine Gauquier and P.Pierre Senellart. Modular Multimodal Machine Learning for Extraction of Theorems and Proofs in Long Scientific Documents (Extended Version).November 2024HALback to text