1 citations · 2 across the 7 of their papers we have counts for
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PART: Progressive Alignment Representation Training for Multilingual Speech-To-Text with LLMs
Pei Zhang, Andong Chen, Xi Chen +3
Large language models (LLMs) have expanded from text to speech, giving rise to Speech Large Models (SLMs) that support recognition, translation, and synthesis. A key challenge is a…
Large Language Model for Multi-Domain Translation: Benchmarking and Domain CoT Fine-tuning
Tianxiang Hu, Pei Zhang, Baosong Yang +3
Achieving consistent high-quality machine translation (MT) across diverse domains remains a significant challenge, primarily due to the limited and imbalanced parallel training dat…
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
Yiming Wang, Pei Zhang, Baosong Yang +2
LLM self-evaluation relies on the LLM's own ability to estimate response correctness, which can greatly improve its deployment reliability. In this research track, we propose the C…
Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning
Yiming Wang, Pei Zhang, Baosong Yang +3
Real-world data deviating from the independent and identically distributed (i.i.d.) assumption of in-distribution training data poses security threats to deep networks, thus advanc…