7 citations · 14 across the 6 of their papers we have counts for
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cs.LG2025
Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model
Jing Liang, Hongyao Tang, Yi Ma +5
Reinforcement Learning (RL) has demonstrated its potential to improve the reasoning ability of Large Language Models (LLMs). One major limitation of most existing Reinforcement Fin…
cs.CY2025★ 7 cited
LLM Agents for Education: Advances and Applications
Zhendong Chu, Shen Wang, Jian Xie +8
Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present…