Jingtong Gao

SampleLLM: Optimizing Tabular Data Synthesis in Recommendations

2025

Tabular data synthesis is crucial in machine learning, yet existing general methods-primarily based on statistical or deep learning models-are highly data-dependent and often fall short in recommender systems. This limitation arises from their difficulty in …

Navigate the Unknown: Enhancing LLM Reasoning with Intrinsic Motivation Guided Exploration

2025 · arXiv (Cornell University)

Reinforcement Learning (RL) has become a key approach for enhancing the reasoning capabilities of large language models. However, prevalent RL approaches like proximal policy optimization and group relative policy optimization suffer from sparse, outcome-based rewards …