3 papers
cs.AI2026
FadeMem: Biologically-Inspired Forgetting for Efficient Agent Memory
Lei Wei, Xiao Peng, Xu Dong +2
Large language models deployed as autonomous agents face critical memory limitations, lacking selective forgetting mechanisms that lead to either catastrophic forgetting at context…
cs.CV2025
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.CV2025
FCoT-VL:Advancing Text-oriented Large Vision-Language Models with Efficient Visual Token Compression
Jianjian Li, Junquan Fan, Feng Tang +6
The rapid success of Vision Large Language Models (VLLMs) often depends on the high-resolution images with abundant visual tokens, which hinders training and deployment efficiency.…