2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2026
TED: Training-Free Experience Distillation for Multimodal Reasoning
Shuozhi Yuan, Jinqing Wang, Zihao Liu +5
Knowledge distillation is typically realized by transferring a teacher model's knowledge into a student's parameters through supervised or reinforcement-based optimization. While e…
cs.AI2025
SkyRL-Agent: Efficient RL Training for Multi-turn LLM Agent
Shiyi Cao, Dacheng Li, Fangzhou Zhao +12
We introduce SkyRL-Agent, a framework for efficient, multi-turn, long-horizon agent training and evaluation. It provides efficient asynchronous dispatching, lightweight tool integr…
cs.AI2025★ 2 cited
Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First
Shu Liu, Soujanya Ponnapalli, Shreya Shankar +12
Large Language Model (LLM) agents, acting on their users' behalf to manipulate and analyze data, are likely to become the dominant workload for data systems in the future. When wor…