2 papers
cs.CV2026
Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions
Junhao Su, Yuanliang Wan, Junwei Yang +4
Tool-augmented large language models (LLMs) are usually trained with supervised imitation or coarse-grained reinforcement learning that optimizes single tool calls. Current self-re…
cs.CV2026
MAN++: Scaling Momentum Auxiliary Network for Supervised Local Learning in Vision Tasks
Junhao Su, Feiyu Zhu, Hengyu Shi +5
Deep learning typically relies on end-to-end backpropagation for training, a method that inherently suffers from issues such as update locking during parameter optimization, high G…