4 papers
Smarter by the Moment: Environment-Driven Dynamic Policies for Continual LLM Improvement
Ting-Wei Chang, Po-Chun Chen, Hen-Hsen Huang +1
Large Language Models (LLMs) have achieved remarkable progress across diverse domains, but continual adaptation to evolving tasks and environments remains a key challenge. Existing…
Strategy-Induct: Task-Level Strategy Induction for Instruction Generation
Po-Chun Chen, Hen-Hsen Huang, Hsin-Hsi Chen
Designing effective task-level prompts is crucial for improving the performance of Large Language Models (LLMs). While prior work on instruction induction demonstrates that LLMs ca…
Diverge to Induce Prompting: Multi-Rationale Induction for Zero-Shot Reasoning
Po-Chun Chen, Hen-Hsen Huang, Hsin-Hsi Chen
To address the instability of unguided reasoning paths in standard Chain-of-Thought prompting, recent methods guide large language models (LLMs) by first eliciting a single reasoni…
Hearing the Order: Investigating Position Bias in Large Audio-Language Models
Yu-Xiang Lin, Chen-An Li, Sheng-Lun Wei +3
Large audio-language models (LALMs) are often used in tasks that involve reasoning over ordered options. An open question is whether their predictions are influenced by the order o…