4 citations · 8 across the 19 of their papers we have counts for
21 papers
How Robust Is Multimodal Claim Verification to LLM Rewriting?
Yun-Ang Wu, Xanh Ho, Andre Greiner-Petter +4
LLMs are known to introduce stylistic changes into generated text, yet how these stylistic shifts affect model decisions on scientific tasks remains underexplored. In this paper, w…
Encoded but Not Routed: Explaining the Table-Chart Gap in Scientific Claim Verification
Sunisth Kumar, Xanh Ho, Tim Schopf +3
Multimodal LLMs are increasingly used to assist scientific peer review, where a core requirement is verifying whether claims in a paper are supported by its evidence. Prior work ha…
EarlySciRev: A Dataset of Early-Stage Scientific Revisions Extracted from LaTeX Writing Traces
Léane Jourdan, Julien Aubert-Béduchaud, Yannis Chupin +2
Scientific writing is an iterative process that generates rich revision traces, yet publicly available resources typically expose only final or near-final versions of papers. This…
SciClaimEval: Cross-modal Claim Verification in Scientific Papers
Xanh Ho, Yun-Ang Wu, Sunisth Kumar +4
We present SciClaimEval, a new scientific dataset for the claim verification task. Unlike existing resources, SciClaimEval features authentic claims, including refuted ones, direct…
FC-CONAN: An Exhaustively Paired Dataset for Robust Evaluation of Retrieval Systems
Juan Junqueras, Florian Boudin, May-Myo Zin +5
Hate speech (HS) is a critical issue in online discourse, and one promising strategy to counter it is through the use of counter-narratives (CNs). Datasets linking HS with CNs are…
Format Matters: The Robustness of Multimodal LLMs in Reviewing Evidence from Tables and Charts
Xanh Ho, Yun-Ang Wu, Sunisth Kumar +3
With the growing number of submitted scientific papers, there is an increasing demand for systems that can assist reviewers in evaluating research claims. Experimental results are…
Repurposing Annotation Guidelines to Instruct LLM Annotators: A Case Study
Kon Woo Kim, Rezarta Islamaj, Jin-Dong Kim +2
This study investigates how existing annotation guidelines can be repurposed to instruct large language model (LLM) annotators for text annotation tasks. Traditional guidelines are…
An Analysis of Datasets, Metrics and Models in Keyphrase Generation
Florian Boudin, Akiko Aizawa
Keyphrase generation refers to the task of producing a set of words or phrases that summarises the content of a document. Continuous efforts have been dedicated to this task over t…
No Stupid Questions: An Analysis of Question Query Generation for Citation Recommendation
Brian D. Zimmerman, Julien Aubert-Béduchaud, Florian Boudin +2
Existing techniques for citation recommendation are constrained by their adherence to article contents and metadata. We leverage GPT-4o-mini's latent expertise as an inquisitive as…
Preface to the Special Issue of the TAL Journal on Scholarly Document Processing
Florian Boudin, Akiko Aizawa
The rapid growth of scholarly literature makes it increasingly difficult for researchers to keep up with new knowledge. Automated tools are now more essential than ever to help nav…
Automatically Suggesting Diverse Example Sentences for L2 Japanese Learners Using Pre-Trained Language Models
Enrico Benedetti, Akiko Aizawa, Florian Boudin
Providing example sentences that are diverse and aligned with learners' proficiency levels is essential for fostering effective language acquisition. This study examines the use of…
Table-Text Alignment: Explaining Claim Verification Against Tables in Scientific Papers
Xanh Ho, Sunisth Kumar, Yun-Ang Wu +3
Scientific claim verification against tables typically requires predicting whether a claim is supported or refuted given a table. However, we argue that predicting the final label…
Identifying Reliable Evaluation Metrics for Scientific Text Revision
Léane Jourdan, Florian Boudin, Richard Dufour +1
Evaluating text revision in scientific writing remains a challenge, as traditional metrics such as ROUGE and BERTScore primarily focus on similarity rather than capturing meaningfu…
Reassessing Extractive QA Datasets at Scale: LLM-as-a-Judge and In-Depth Analyses
Xanh Ho, Jiahao Huang, Florian Boudin +1
Extractive QA tasks are commonly evaluated using Exact Match (EM) and F1-score, but these metrics often fail to reflect true model performance. Recent studies have proposed using l…
ACL-rlg: A Dataset for Reading List Generation
Julien Aubert-Béduchaud, Florian Boudin, Béatrice Daille +1
Familiarizing oneself with a new scientific field and its existing literature can be daunting due to the large amount of available articles. Curated lists of academic references, o…
ParaRev: Building a dataset for Scientific Paragraph Revision annotated with revision instruction
Léane Jourdan, Nicolas Hernandez, Richard Dufour +2
Revision is a crucial step in scientific writing, where authors refine their work to improve clarity, structure, and academic quality. Existing approaches to automated writing assi…
Self-Compositional Data Augmentation for Scientific Keyphrase Generation
Mael Houbre, Florian Boudin, Beatrice Daille +1
State-of-the-art models for keyphrase generation require large amounts of training data to achieve good performance. However, obtaining keyphrase-labeled documents can be challengi…
Unsupervised Domain Adaptation for Keyphrase Generation using Citation Contexts
Florian Boudin, Akiko Aizawa
Adapting keyphrase generation models to new domains typically involves few-shot fine-tuning with in-domain labeled data. However, annotating documents with keyphrases is often proh…
MoreHopQA: More Than Multi-hop Reasoning
Julian Schnitzler, Xanh Ho, Jiahao Huang +3
Most existing multi-hop datasets are extractive answer datasets, where the answers to the questions can be extracted directly from the provided context. This often leads models to…
CASIMIR: A Corpus of Scientific Articles enhanced with Multiple Author-Integrated Revisions
Leane Jourdan, Florian Boudin, Nicolas Hernandez +1
Writing a scientific article is a challenging task as it is a highly codified and specific genre, consequently proficiency in written communication is essential for effectively con…
A Survey of Pre-trained Language Models for Processing Scientific Text
Xanh Ho, Anh Khoa Duong Nguyen, An Tuan Dao +6
The number of Language Models (LMs) dedicated to processing scientific text is on the rise. Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task…