4 papers
Train Less, Learn More: Adaptive Efficient Rollout Optimization for Group-Based Reinforcement Learning
Zhi Zhang, Zhen Han, Costas Mavromatis +9
Reinforcement learning (RL) plays a central role in large language model (LLM) post-training. Among existing approaches, Group Relative Policy Optimization (GRPO) is widely used, e…
When Do Symbolic Solvers Enhance Reasoning in Large Language Models?
Zhiyuan He, Dingmin Wang
Large Reasoning Models (LRMs) achieve strong performance on complex reasoning tasks by generating long Chains of Thought (CoTs). However, this paradigm might incur substantial toke…
CRABS: A syntactic-semantic pincer strategy for bounding LLM interpretation of Python notebooks
Meng Li, Timothy M. McPhillips, Dingmin Wang +2
Recognizing the information flows and operations comprising data science and machine learning Python notebooks is critical for evaluating, reusing, and adapting notebooks for new t…
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
Yeyuan Chen, Dingmin Wang
As a powerful framework for graph representation learning, Graph Neural Networks (GNNs) have garnered significant attention in recent years. However, to the best of our knowledge,…