10 citations · 11 across the 4 of their papers we have counts for
4 papers
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…
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Large language models confidently produce outdated answers, and no existing method can detect them.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,…
Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
Andy Zhou, Jindong Wang, Yu-Xiong Wang +1
We propose a conceptually simple and lightweight framework for improving the robustness of vision models through the combination of knowledge distillation and data augmentation. We…
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman +2
While language models (LMs) have shown potential across a range of decision-making tasks, their reliance on simple acting processes limits their broad deployment as autonomous agen…