5 papers
Stop Unnecessary Reflection: Training LRMs for Efficient Reasoning with Adaptive Reflection and Length Coordinated Penalty
Zewei Yu, Lirong Gao, Yuke Zhu +4
Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex reasoning tasks by employing test-time scaling. However, they often generate over-long chains-of-t…
Learning from the Irrecoverable: Error-Localized Policy Optimization for Tool-Integrated LLM Reasoning
Qiao Liang, Yuke Zhu, Chao Ge +4
Tool-integrated reasoning (TIR) enables LLM agents to solve tasks through planning, tool use, and iterative revision, but outcome-only reinforcement learning in this setting suffer…
FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression
Yuke Zhu, Chi Xie, Shuang Liang +2
Recent advances on Multi-modal Large Language Models have demonstrated that high-resolution image input is crucial for model capabilities, especially for fine-grained tasks. Howeve…
Edge Wasserstein Distance Loss for Oriented Object Detection
Yuke Zhu, Yumeng Ruan, Zihua Xiong +1
Regression loss design is an essential topic for oriented object detection. Due to the periodicity of the angle and the ambiguity of width and height definition, traditional L1-dis…
RotaTR: Detection Transformer for Dense and Rotated Object
Zhu Yuke, Ruan Yumeng, Yang Lei +1
Detecting the objects in dense and rotated scenes is a challenging task. Recent works on this topic are mostly based on Faster RCNN or Retinanet. As they are highly dependent on th…