2 papers
cs.CL2026
DiARC: Distinguishing Positive and Negative Samples Helps Improving ARC-like Reasoning Ability of Large Language Models
Yuxuan Yang, Feiyang Li, Yile Wang
The Abstraction and Reasoning Corpus (ARC) contains tasks that require summarizing patterns from limited grid samples and predicting output grids. Recently, many large language mod…
cs.RO2026
Potential-Guided Flow Matching for Vision-Language-Action Policy Improvement
Yunpeng Mei, Jiakai He, Hongjie Cao +12
Large vision-language-action (VLA) policies are increasingly trained as conditional generative models over action chunks. Yet deployment produces mixed-quality experience-successfu…