5 papers
MOSS-Speech: Towards True Speech-to-Speech Models Without Text Guidance
Xingjian Zhao, Zhe Xu, Qinyuan Cheng +20
Spoken dialogue systems often rely on cascaded pipelines that transcribe, process, and resynthesize speech. While effective, this design discards paralinguistic cues and limits exp…
Decoupled Proxy Alignment: Mitigating Language Prior Conflict for Multimodal Alignment in MLLM
Chenkun Tan, Pengyu Wang, Shaojun Zhou +6
Multimodal large language models (MLLMs) have gained significant attention due to their impressive ability to integrate vision and language modalities. Recent advancements in MLLMs…
MetaAlign: Align Large Language Models with Diverse Preferences during Inference Time
Mozhi Zhang, Pengyu Wang, Chenkun Tan +4
Large Language Models (LLMs) acquire extensive knowledge and remarkable abilities from extensive text corpora, making them powerful tools for various applications. To make LLMs mor…
IntrinsicVoice: Empowering LLMs with Intrinsic Real-time Voice Interaction Abilities
Xin Zhang, Xiang Lyu, Zhihao Du +10
Current methods of building LLMs with voice interaction capabilities rely heavily on explicit text autoregressive generation before or during speech response generation to maintain…
Calibrating the Confidence of Large Language Models by Eliciting Fidelity
Mozhi Zhang, Mianqiu Huang, Rundong Shi +5
Large language models optimized with techniques like RLHF have achieved good alignment in being helpful and harmless. However, post-alignment, these language models often exhibit o…