9 citations · 11 across the 9 of their papers we have counts for
13 papers
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…
Expected Harm: Rethinking Safety Evaluation of (Mis)Aligned LLMs
Yen-Shan Chen, Zhi Rui Tam, Cheng-Kuang Wu +1
Current evaluations of LLM safety predominantly rely on severity-based taxonomies to assess the harmfulness of malicious queries. We argue that this formulation requires re-examina…
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…
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…
Answer, Refuse, or Guess? Investigating Risk-Aware Decision Making in Language Models
Cheng-Kuang Wu, Zhi Rui Tam, Chieh-Yen Lin +2
Language models (LMs) are increasingly used to build agents that can act autonomously to achieve goals. During this automatic process, agents need to take a series of actions, some…
Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models
Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai +3
Structured generation, the process of producing content in standardized formats like JSON and XML, is widely utilized in real-world applications to extract key output information f…