5 citations · 6 across the 7 of their papers we have counts for
5 papers · 1 filter
Entropy-based Coarse and Compressed Semantic Speech Representation Learning
Jialong Zuo, Guangyan Zhang, Minghui Fang +5
Discrete speech representation learning has recently attracted increasing interest in both acoustic and semantic modeling. Existing approaches typically encode 16 kHz waveforms int…
Add-One-In: Incremental Sample Selection for Large Language Models via a Choice-Based Greedy Paradigm
Zhuo Li, Yuhao Du, Xiaoqi Jiao +5
Selecting high-quality and diverse training samples from extensive datasets plays a crucial role in reducing training overhead and enhancing the performance of Large Language Model…
VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models
Wenqian Cui, Xiaoqi Jiao, Ziqiao Meng +1
With the rising need for speech-based interaction models, end-to-end Spoken Language Models (SLMs) have emerged as a promising solution. While these models require comprehensive wo…
Recent Advances in Speech Language Models: A Survey
Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao +5
Large Language Models (LLMs) have recently garnered significant attention, primarily for their capabilities in text-based interactions. However, natural human interaction often rel…
Direct Alignment of Language Models via Quality-Aware Self-Refinement
Runsheng Yu, Yong Wang, Xiaoqi Jiao +2
Reinforcement Learning from Human Feedback (RLHF) has been commonly used to align the behaviors of Large Language Models (LLMs) with human preferences. Recently, a popular alternat…