2 citations · 4 across the 14 of their papers we have counts for
12 papers · 1 filter
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…
Refining and Reusing Annotation Guidelines for LLM Annotation
Kon Woo Kim, Jin-Dong Kim, Akiko Aizawa
While Large Language Models (LLMs) demonstrate remarkable performance on zero-shot annotation tasks, they often struggle with the specialized conventions of gold-standard benchmark…
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…
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…
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…
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…