3 papers
cs.AI2026
Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization
Bin Hong, Jiayu Liu, Kai Zhang +3
Recent advances in Large Reasoning Models (LRMs) have demonstrated strong performance on complex tasks through long Chain-of-Thought (CoT) reasoning. However, their lengthy outputs…
cs.CV2026
CausalVAD: De-confounding End-to-End Autonomous Driving via Causal Intervention
Jiacheng Tang, Zhiyuan Zhou, Zhuolin He +3
Planning-oriented end-to-end driving models show great promise, yet they fundamentally learn statistical correlations instead of true causal relationships. This vulnerability leads…
cs.CL2026
Reward Prediction with Factorized World States
Yijun Shen, Delong Chen, Xianming Hu +4
Agents must infer action outcomes and select actions that maximize a reward signal indicating how close the goal is to being reached. Supervised learning of reward models could int…