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Author

Hung-yi Lee

2 papers indexed here

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AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning

AdaSearch is proposed, a simple two-stage, outcome-driven RL framework that disentangles problem-solving from the decision to search, making the decision process explicit and interpretable and significantly improves search-decision quality and reduces unnecessary search calls.

Tzu-Han Lin, Wei-Lin Chen, Chen-An Li et al. · 5 citations

Hearing the Order: Investigating Selection Bias in Large Audio-Language Models

This work demonstrates that no model is immune to this bias through extensive experiments on six LALMs across three widely used benchmarks and their spoken counterparts, and study permutation-based strategies and show that they can mitigate bias in most cases.

Yu-Xiang Lin, Chen-An Li, Sheng-Lun Wei et al. · 6 citations

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