3 papers
cs.LG2025
ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
Weiqin Chen, Nhan Huu Pham, Michael Robert Glass +4
Reinforcement learning (RL) has demonstrated significant promise in enhancing the reasoning capabilities of Text2SQL LLMs, especially with advanced algorithms such as GRPO and DAPO…
cs.LG2025
Filtering Learning Histories Enhances In-Context Reinforcement Learning
Weiqin Chen, Xinjie Zhang, Dharmashankar Subramanian +1
Transformer models (TMs) have exhibited remarkable in-context reinforcement learning (ICRL) capabilities, allowing them to generalize to and improve in previously unseen environmen…
cs.LG2024
Random Policy Enables In-Context Reinforcement Learning within Trust Horizons
Weiqin Chen, Santiago Paternain
Pretrained foundation models have exhibited extraordinary in-context learning performance, allowing zero-shot generalization to new tasks not encountered during pretraining. In the…