5 citations · 7 across the 5 of their papers we have counts for
5 papers
UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language Model
Zhaowei Li, Wei Wang, YiQing Cai +7
Significant advancements has recently been achieved in the field of multi-modal large language models (MLLMs), demonstrating their remarkable capabilities in understanding and reas…
SpeechAlign: Aligning Speech Generation to Human Preferences
Dong Zhang, Zhaowei Li, Shimin Li +4
Speech language models have significantly advanced in generating realistic speech, with neural codec language models standing out. However, the integration of human feedback to ali…
InferAligner: Inference-Time Alignment for Harmlessness through Cross-Model Guidance
Pengyu Wang, Dong Zhang, Linyang Li +5
With the rapid development of large language models (LLMs), they are not only used as general-purpose AI assistants but are also customized through further fine-tuning to meet the…
SpeechAgents: Human-Communication Simulation with Multi-Modal Multi-Agent Systems
Dong Zhang, Zhaowei Li, Pengyu Wang +3
Human communication is a complex and diverse process that not only involves multiple factors such as language, commonsense, and cultural backgrounds but also requires the participa…
SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities
Dong Zhang, Shimin Li, Xin Zhang +4
Multi-modal large language models are regarded as a crucial step towards Artificial General Intelligence (AGI) and have garnered significant interest with the emergence of ChatGPT.…