2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Data-Centric Interpretability for LLM-based Multi-Agent Reinforcement Learning
John Yan, Michael Yu, Yuqi Sun +3
Large language models (LLMs) are increasingly trained in complex Reinforcement Learning, multi-agent environments, making it difficult to understand how behavior changes over train…
cs.DC2025
SmartSwap: Swap-Based Memory Optimization for LLM Training under Varying Operator Sequences
Zibo Wang, Yuhang Zhou, Zhibin Wang +13
The increasing size of large language models (LLMs) has led to a surge in memory requirements during training, often exceeding the capacity of high-bandwidth memory (HBM). Swap-bas…
cs.HC2025★ 2 cited
SRLAgent: Enhancing Self-Regulated Learning Skills through Gamification and LLM Assistance
Wentao Ge, Yuqing Sun, Ziyan Wang +5
Self-regulated learning (SRL) is crucial for college students navigating increased academic demands and independence. Insufficient SRL skills can lead to disorganized study habits,…