8 papers
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…
No One Fits All: From Fixed Prompting to Learned Routing in Multilingual LLMs
Wei-Chi Wu, Sheng-Lun Wei, Hen-Hsen Huang +1
Translation-based prompting is widely used in multilingual LLMs, yet its effectiveness varies across languages and tasks. We evaluate prompting strategies across ten languages of d…
Personalized Graph-Empowered Large Language Model for Proactive Information Access
Chia Cheng Chang, An-Zi Yen, Hen-Hsen Huang +1
Since individuals may struggle to recall all life details and often confuse events, establishing a system to assist users in recalling forgotten experiences is essential. While num…
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…
Bias in the Ear of the Listener: Assessing Sensitivity in Audio Language Models Across Linguistic, Demographic, and Positional Variations
Sheng-Lun Wei, Yu-Ling Liao, Yen-Hua Chang +2
This work presents the first systematic investigation of speech bias in multilingual MLLMs. We construct and release the BiasInEar dataset, a speech-augmented benchmark based on Gl…
Visual Lifelog Retrieval through Captioning-Enhanced Interpretation
Yu-Fei Shih, An-Zi Yen, Hen-Hsen Huang +1
People often struggle to remember specific details of past experiences, which can lead to the need to revisit these memories. Consequently, lifelog retrieval has emerged as a cruci…