3 papers
cs.AI2026
Agent Learning via Early Experience
Kai Zhang, Xiangchao Chen, Bo Liu +27
A long-term goal of language agents is to learn and improve through their own experience, ultimately outperforming humans in complex, real-world tasks. However, training agents fro…
cs.CV2025
Lemon: A Unified and Scalable 3D Multimodal Model for Universal Spatial Understanding
Yongyuan Liang, Xiyao Wang, Yuanchen Ju +2
Scaling large multimodal models (LMMs) to 3D understanding poses unique challenges: point cloud data is sparse and irregular, existing models rely on fragmented architectures with…
cs.CV2025
LLaVA-Critic-R1: Your Critic Model is Secretly a Strong Policy Model
Xiyao Wang, Chunyuan Li, Jianwei Yang +4
In vision-language modeling, critic models are typically trained to evaluate outputs -- assigning scalar scores or pairwise preferences -- rather than to generate responses. This s…