Author

Hung-yi Lee

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Preprint Aug 2026

INSPIRE: A Benchmark for Instruction-Aware Speech Retrieval

Existing speech retrieval systems rely on fixed similarity matching and cannot adapt to diverse user intents. We introduce INSPIRE, the first benchmark for instruction-aware speech retrieval, in which natural-language instructions dynamically specify relevance criteria, including semantic content, speaker identity, spe...

Chen-An Li, Hung-Yi Lee · 0 citations

#natural language process... Dec 2025

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. · arXiv.org · 5 citations

#natural language process... Oct 2025

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. · arXiv.org · 6 citations