1 citations · 1 across the 7 of their papers we have counts for
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TIC-GRPO: Provable and Efficient Optimization for Reinforcement Learning from Human Feedback
Lei Pang, Jun Luo, Ruinan Jin
Group Relative Policy Optimization (GRPO) trains language models without a value critic using rewards centered within sampled response groups. We study how importance weighting, cl…
NaviAgent: Graph-Driven Bilevel Planning for Scalable Tool Orchestration
Yan Jiang, Hao Zhou, Lizhong GU +4
Large Language Models (LLMs) increasingly act as function-call agents that invoke external tools to tackle tasks beyond their static knowledge. However, they typically invoke tools…
Convergence Analysis of the Last Iterate in Distributed Stochastic Gradient Descent with Momentum
Difei Cheng, Ruinan Jin, Hong Qiao +1
Distributed stochastic gradient methods are widely used to preserve data privacy and ensure scalability in large-scale learning tasks. While existing theory on distributed momentum…
Stochastic Gradient Descent in Non-Convex Problems: Asymptotic Convergence with Relaxed Step-Size via Stopping Time Methods
Ruinan Jin, Difei Cheng, Hong Qiao +3
Stochastic Gradient Descent (SGD) is widely used in machine learning research. Previous convergence analyses of SGD under the vanishing step-size setting typically require Robbins-…