2 papers
cs.CL2025
RLSR: Reinforcement Learning with Supervised Reward Outperforms SFT in Instruction Following
Zhichao Wang, Andy Wong, Ruslan Belkin
After the pretraining stage of LLMs, techniques such as SFT, RLHF, RLVR, and RFT are applied to enhance instruction-following ability, mitigate undesired responses, improve reasoni…
cs.CL2025
Facilitating Long Context Understanding via Supervised Chain-of-Thought Reasoning
Jingyang Lin, Andy Wong, Tian Xia +4
Recent advances in Large Language Models (LLMs) have enabled them to process increasingly longer sequences, ranging from 2K to 2M tokens and even beyond. However, simply extending…