4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.CV2024
EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions
Kai Chen, Yunhao Gou, Runhui Huang +28
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language…
cs.CV2023★ 2 cited
Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
Ming Nie, Renyuan Peng, Chunwei Wang +4
Large vision-language models (VLMs) have garnered increasing interest in autonomous driving areas, due to their advanced capabilities in complex reasoning tasks essential for highl…
cs.CL2023★ 4 cited
Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis
Kai Chen, Chunwei Wang, Kuo Yang +11
The rapid development of large language models (LLMs) has not only provided numerous opportunities but also presented significant challenges. This becomes particularly evident when…