Papers by Daechul Ahn

2 papers
Becoming Experienced Judges: Selective Test-Time Learning for Evaluators (2026.eacl-short)

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Challenge: Large language models and visionlanguage models are increasingly used as automatic evaluators.
Approach: They propose a framework that allows evaluators to improve *sequentially* at inference time without additional training or external signals.
Outcome: The proposed framework outperforms strong baselines in two pairwise comparisons.
Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback (2024.acl-long)

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Challenge: Recent advances in large language models have influenced the development of video large multimodal models (VLMMs).
Approach: They propose a method that integrates video descriptions as context into a multimodal AI system to enrich the understanding of video content.
Outcome: Empirical evaluations show that the proposed approach outperforms existing approaches for video large multimodal models (VLMMs)

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