5 papers
How Do Answer Tokens Read Reasoning Traces? Self-Reading Patterns in Thinking LLMs for Quantitative Reasoning
Haoyang Chen, Yi Liu, Jianzhi Shao +3
Thinking LLMs produce reasoning traces before answering. Prior activation steering work mainly targets on shaping these traces. It remains less understood how answer tokens actuall…
Multi-TW: Benchmarking Multimodal Models on Traditional Chinese Question Answering in Taiwan
Jui-Ming Yao, Bing-Cheng Xie, Sheng-Wei Peng +5
Multimodal Large Language Models (MLLMs) process visual, acoustic, and textual inputs, addressing the limitations of single-modality LLMs. However, existing benchmarks often overlo…
Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models
Jui-Ming Yao, Hao-Yuan Chen, Zi-Xian Tang +4
Large Language Models (LLMs) have demonstrated impressive performance on multiple-choice question answering (MCQA) benchmarks, yet they remain highly vulnerable to minor input pert…
Verbal Process Supervision Elicits Better Coding Agents
Hao-Yuan Chen, Cheng-Pong Huang, Jui-Ming Yao
The emergence of large language models and their applications as AI agents have significantly advanced state-of-the-art code generation benchmarks, transforming modern software eng…
Delta -- Contrastive Decoding Mitigates Text Hallucinations in Large Language Models
Cheng Peng Huang, Hao-Yuan Chen
Large language models (LLMs) demonstrate strong capabilities in natural language processing but remain prone to hallucinations, generating factually incorrect or fabricated content…