Category: Main result The main results of the team: they get shown on the first page under ‘Main recent results’.
EMNLP 2023: Evaluating the Factual Faithfulness of Graph-to-Text Generation
The paper “FactSpotter: Evaluating the Factual Faithfulness of Graph-to-Text Generation” by Kun Zhang, Oana Balalau, Ioana Manolescu has been accepted for publication in Findings of EMNLP 2023.
EDBT 2024: “Computing Generic Abstractions from Application Datasets”
The paper “Computing Generic Abstractions from Application Datasets” by Nelly Barret,
Ioana Manolescu and Prajna Upadhyay has been accepted for publication in EDBT 2024.
WWW 2023: “On Detecting Policy-Related Political Ads: An Exploratory Analysis of Meta Ads in 2022 French Election”
The paper “On Detecting Policy-Related Political Ads: An Exploratory Analysis of Meta Ads in 2022 French Election” by Vera Sosnovik, Romaissa Kessi, Maximin Coavoux and Oana Goga has been accepted for publication at the Web Conference (WWW) 2023.
IEEE ICDE 2023: “Integrating Connection Search in Graph Queries”
The paper “Integrating Connection Search in Graph Queries” by Angelos Anadiotis, Ioana Manolescu and Madhulika Mohanty has been accepted for publication at ICDE 2023.
TTO 2022: “Fact-checking Multidimensional Statistic Claims in French”
The paper “Fact-checking Multidimensional Statistic Claims in French” by Oana Balalau, Simon Ebel, Théo Galizzi, Ioana Manolescu, Quentin Massonnat (CEDAR), Antoine Deiana, Emilie Gautreau, Antoine Krempf, Thomas Pointillon, Gérald Roux, Joanna Yakin (Radio France) has been accepted for publication at the conference Truth and Trust Online (TTO) 2022.
CIKM 2022: “Statistical Claim Checking: StatCheck in Action” and “Abstra: Toward Generic Abstractions for Data of Any Model”
The demonstrations: “Statistical Claim Checking: StatCheck in Action” by Oana Balalau, Simon Ebel, Théo Galizzi, Ioana Manolescu, Quentin Massonnat (CEDAR), Antoine Deiana, Emilie Gautreau, Antoine Krempf, Thomas Pointillon, Gérald Roux, Joanna Yakin (Radio France) and “Abstra: Toward Generic Abstractions for Data of Any Model” by Nelly Barret, Ioana Manolescu, Prajna …
VLDB 2022: “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing”
The paper “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing” by Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, and our Alibaba collaborators: Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, and Jingren Zhou has been accepted in PVLDB and will appear at …
Sci-K 2022: “GraphCite: Citation Intent Classification in Scientific Publications via Graph Embedding”
The paper “GraphCite: Citation Intent Classification in Scientific Publications via Graph Embedding” by Dan Berrebbi, Nicolas Huynh and Oana Balalau has been accepted at the workshop Sci-K 2022, collocated with The Web Conf 2022.
PVDLB 2021: “Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series”
The paper “Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series” by Vincent Jacob, Fei Song, Arnaud Stiegler, Bijan Rad, Yanlei Diao and Nesime Tatbul has been accepted for publication in the research track of PVLDB 2021 (Experiments, Analysis & Benchmark).
The main results of the team: they get shown on the first page under ‘Main recent results’.
EMNLP 2023: Evaluating the Factual Faithfulness of Graph-to-Text Generation
The paper “FactSpotter: Evaluating the Factual Faithfulness of Graph-to-Text Generation” by Kun Zhang, Oana Balalau, Ioana Manolescu has been accepted for publication in Findings of EMNLP 2023.
EDBT 2024: “Computing Generic Abstractions from Application Datasets”
The paper “Computing Generic Abstractions from Application Datasets” by Nelly Barret,
Ioana Manolescu and Prajna Upadhyay has been accepted for publication in EDBT 2024.
WWW 2023: “On Detecting Policy-Related Political Ads: An Exploratory Analysis of Meta Ads in 2022 French Election”
The paper “On Detecting Policy-Related Political Ads: An Exploratory Analysis of Meta Ads in 2022 French Election” by Vera Sosnovik, Romaissa Kessi, Maximin Coavoux and Oana Goga has been accepted for publication at the Web Conference (WWW) 2023.
IEEE ICDE 2023: “Integrating Connection Search in Graph Queries”
The paper “Integrating Connection Search in Graph Queries” by Angelos Anadiotis, Ioana Manolescu and Madhulika Mohanty has been accepted for publication at ICDE 2023.
TTO 2022: “Fact-checking Multidimensional Statistic Claims in French”
The paper “Fact-checking Multidimensional Statistic Claims in French” by Oana Balalau, Simon Ebel, Théo Galizzi, Ioana Manolescu, Quentin Massonnat (CEDAR), Antoine Deiana, Emilie Gautreau, Antoine Krempf, Thomas Pointillon, Gérald Roux, Joanna Yakin (Radio France) has been accepted for publication at the conference Truth and Trust Online (TTO) 2022.
CIKM 2022: “Statistical Claim Checking: StatCheck in Action” and “Abstra: Toward Generic Abstractions for Data of Any Model”
The demonstrations: “Statistical Claim Checking: StatCheck in Action” by Oana Balalau, Simon Ebel, Théo Galizzi, Ioana Manolescu, Quentin Massonnat (CEDAR), Antoine Deiana, Emilie Gautreau, Antoine Krempf, Thomas Pointillon, Gérald Roux, Joanna Yakin (Radio France) and “Abstra: Toward Generic Abstractions for Data of Any Model” by Nelly Barret, Ioana Manolescu, Prajna …
VLDB 2022: “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing”
The paper “Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing” by Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, and our Alibaba collaborators: Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, and Jingren Zhou has been accepted in PVLDB and will appear at …
Sci-K 2022: “GraphCite: Citation Intent Classification in Scientific Publications via Graph Embedding”
The paper “GraphCite: Citation Intent Classification in Scientific Publications via Graph Embedding” by Dan Berrebbi, Nicolas Huynh and Oana Balalau has been accepted at the workshop Sci-K 2022, collocated with The Web Conf 2022.
PVDLB 2021: “Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series”
The paper “Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series” by Vincent Jacob, Fei Song, Arnaud Stiegler, Bijan Rad, Yanlei Diao and Nesime Tatbul has been accepted for publication in the research track of PVLDB 2021 (Experiments, Analysis & Benchmark).