Papers by Jirayu Burapacheep

2 papers
Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Models (2025.emnlp-main)

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Challenge: a new study examines the accuracy of Wikipedia's factual inconsistencies . a corpus-level inconsistent detection system can help editors identify inconsistances .
Approach: They propose a corpus-level inconsistency detection system that combines LLM reasoning with retrieval to detect and contextualize potential contradictions for human review.
Outcome: The proposed system can detect inconsistencies in Wikipedia and human review.
ColorSwap: A Color and Word Order Dataset for Multimodal Evaluation (2024.findings-acl)

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Challenge: Recent work reveals that vision and language models struggle to comprehend fine grained distinctions in images.
Approach: They propose a dataset to assess multimodal models' ability to match objects with their colors.
Outcome: The proposed model performs well in visual questionanswering, text-to-image generation and word-order understanding tasks.

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