Papers by Sangkyu Lee

2 papers
Aligning Large Language Models by On-Policy Self-Judgment (2024.acl-long)

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Challenge: Existing approaches for aligning large language models with human preferences face a trade-off that requires a separate reward model for on-policy learning.
Approach: They propose a new alignment framework that does on-policy learning and is parameter efficient . they propose Judge-augmented Supervised Fine-Tuning to train a single model to act as a policy and a judge.
Outcome: The proposed framework outperforms baselines in preference benchmarks and rejecting sampling by itself improves performance without additional evaluator.
Speaking Beyond Language: A Large-Scale Multimodal Dataset for Learning Nonverbal Cues from Video-Grounded Dialogues (2025.acl-long)

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Challenge: Existing large language models fail to incorporate nonverbal elements into conversational experiences.
Approach: They propose a multimodal language model that generates nonverbal cues alongside text . their dataset is annotated with time-aligned text, facial expressions, and body language .
Outcome: The proposed model generates nonverbal languages and text, corresponding to conversational input.

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