4 citations · 7 across the 10 of their papers we have counts for
11 papers
AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning
Tzu-Han Lin, Wei-Lin Chen, Chen-An Li +3
Equipping large language models (LLMs) with search engines via reinforcement learning (RL) promises effective search agents. However, adaptively balancing internal parametric knowl…
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…
When Silence Matters: The Impact of Irrelevant Audio on Text Reasoning in Large Audio-Language Models
Chen-An Li, Tzu-Han Lin, Hung-yi Lee
Large audio-language models (LALMs) unify speech and text processing, but their robustness in noisy real-world settings remains underexplored. We investigate how irrelevant audio,…
Transferring Textual Preferences to Vision-Language Understanding through Model Merging
Chen-An Li, Tzu-Han Lin, Yun-Nung Chen +1
Large vision-language models (LVLMs) perform outstandingly across various multimodal tasks. However, their ability to evaluate generated content remains limited, and training visio…
DogeRM: Equipping Reward Models with Domain Knowledge through Model Merging
Tzu-Han Lin, Chen-An Li, Hung-yi Lee +1
Reinforcement learning from human feedback (RLHF) is a popular strategy for aligning large language models (LLMs) with desired behaviors. Reward modeling is a crucial step in RLHF.…
Examining Forgetting in Continual Pre-training of Aligned Large Language Models
Chen-An Li, Hung-Yi Lee
Recent advances in Large Language Models (LLMs) have exhibited remarkable proficiency across various tasks. Given the potent applications of LLMs in numerous fields, there has been…
CONVERSER: Few-Shot Conversational Dense Retrieval with Synthetic Data Generation
Chao-Wei Huang, Chen-Yu Hsu, Tsu-Yuan Hsu +2
Conversational search provides a natural interface for information retrieval (IR). Recent approaches have demonstrated promising results in applying dense retrieval to conversation…
Improving Cascaded Unsupervised Speech Translation with Denoising Back-translation
Yu-Kuan Fu, Liang-Hsuan Tseng, Jiatong Shi +4
Most of the speech translation models heavily rely on parallel data, which is hard to collect especially for low-resource languages. To tackle this issue, we propose to build a cas…
Model Extraction Attack against Self-supervised Speech Models
Tsu-Yuan Hsu, Chen-An Li, Tung-Yu Wu +1
Self-supervised learning (SSL) speech models generate meaningful representations of given clips and achieve incredible performance across various downstream tasks. Model extraction…
On the Utility of Self-supervised Models for Prosody-related Tasks
Guan-Ting Lin, Chi-Luen Feng, Wei-Ping Huang +5
Self-Supervised Learning (SSL) from speech data has produced models that have achieved remarkable performance in many tasks, and that are known to implicitly represent many aspects…
The Efficacy of Self-Supervised Speech Models for Audio Representations
Tung-Yu Wu, Chen-An Li, Tzu-Han Lin +2
Self-supervised learning (SSL) speech models, which can serve as powerful upstream models to extract meaningful speech representations, have achieved unprecedented success in speec…