8 papers · 1 filter
PetQA: Benchmarking Veterinary Knowledge and Clinical Reasoning
Taegyun Kim, Youngwook Ham, Jungwook Rhim +3
We introduce PetQA, a Korean long-form question-answering (QA) benchmark for evaluating veterinary knowledge and clinical reasoning in large language models (LLMs) and large vision…
Is a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity
Jaeyoon Jung, Yejun Yoon, Kunwoo Park
Automated fact-checking is a crucial task that supports a responsible information ecosystem. While recent research has progressed from text-only to multimodal fact-checking, a prev…
VILLAIN at AVerImaTeC: Verifying Image-Text Claims via Multi-Agent Collaboration
Jaeyoon Jung, Yejun Yoon, Kunwoo Park
This paper describes VILLAIN, a multimodal fact-checking system that verifies image-text claims through prompt-based multi-agent collaboration. For the AVerImaTeC shared task, VILL…
Team HUMANE at AVeriTeC 2025: HerO 2 for Efficient Fact Verification
Yejun Yoon, Jaeyoon Jung, Seunghyun Yoon +1
This paper presents HerO 2, Team HUMANE's system for the AVeriTeC shared task at the FEVER-25 workshop. HerO 2 is an enhanced version of HerO, the best-performing open-source model…
Hypothetical Documents or Knowledge Leakage? Rethinking LLM-based Query Expansion
Yejun Yoon, Jaeyoon Jung, Seunghyun Yoon +1
Query expansion methods powered by large language models (LLMs) have demonstrated effectiveness in zero-shot retrieval tasks. These methods assume that LLMs can generate hypothetic…
HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims
Yejun Yoon, Jaeyoon Jung, Seunghyun Yoon +1
To tackle the AVeriTeC shared task hosted by the FEVER-24, we introduce a system that only employs publicly available large language models (LLMs) for each step of automated fact-c…
ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?
Fan Huang, Haewoon Kwak, Kunwoo Park +1
As AI becomes more integral in our lives, the need for transparency and responsibility grows. While natural language explanations (NLEs) are vital for clarifying the reasoning behi…
Assessing News Thumbnail Representativeness: Counterfactual text can enhance the cross-modal matching ability
Yejun Yoon, Seunghyun Yoon, Kunwoo Park
This paper addresses the critical challenge of assessing the representativeness of news thumbnail images, which often serve as the first visual engagement for readers when an artic…