2 papers
cs.LG2026
Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance
Kai Yan, Alexander G. Schwing, Yu-Xiong Wang
Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought rollouts for many tasks such as ma…
cs.AI2026
The Geometry of Forgetting: Temporal Knowledge Drift as an Independent Axis in LLM Representations
Rania Elbadry, Ahmed Heakl, Fan Zhang +4
Large language models confidently produce outdated answers, and no existing method can detect them. We show this is not an engineering failure but a structural one: temporal drift,…