collaborators

9 papers

cs.CL2026

On Calibration of Large Language Models: From Response To Capability

Sin-Han Yang, Cheng-Kuang Wu, Chieh-Yen Lin +3

Large language models (LLMs) are widely deployed as general-purpose problem solvers, making accurate confidence estimation critical for reliable use. Prior work on LLM calibration…

cs.CL2025

MedVoiceBias: A Controlled Study of Audio LLM Behavior in Clinical Decision-Making

Zhi Rui Tam, Yun-Nung Chen

As large language models transition from text-based interfaces to audio interactions in clinical settings, they might introduce new vulnerabilities through paralinguistic cues in a…

cs.SD2025

Investigating Safety Vulnerabilities of Large Audio-Language Models Under Speaker Emotional Variations

Bo-Han Feng, Chien-Feng Liu, Yu-Hsuan Li Liang +9

Large audio-language models (LALMs) extend text-based LLMs with auditory understanding, offering new opportunities for multimodal applications. While their perception, reasoning, a…

cs.SD2025

SAKE: Towards Editing Auditory Attribute Knowledge of Large Audio-Language Models

Chih-Kai Yang, Yen-Ting Piao, Tzu-Wen Hsu +8

Knowledge editing enables targeted updates without retraining, but prior work focuses on textual or visual facts, leaving abstract auditory perceptual knowledge underexplored. We i…

cs.CL2025

Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models?

Zhi Rui Tam, Cheng-Kuang Wu, Yu Ying Chiu +3

Large reasoning models (LRMs) have demonstrated impressive performance across a range of reasoning tasks, yet little is known about their internal reasoning processes in multilingu…

cs.CY2025

None of the Above, Less of the Right: Parallel Patterns between Humans and LLMs on Multi-Choice Questions Answering

Zhi Rui Tam, Cheng-Kuang Wu, Chieh-Yen Lin +1

Multiple-choice exam questions with "None of the above" (NA) options have been extensively studied in educational testing, in which existing research suggests that they better asse…