3 papers
cs.AI2026
Scaling In-Context Online Learning Capability of LLMs via Cross-Episode Meta-RL
Xiaofeng Lin, Sirou Zhu, Yilei Chen +6
Large language models (LLMs) achieve strong performance when all task-relevant information is available upfront, as in static prediction and instruction-following problems. However…
cs.LG2025
Debunk the Myth of SFT Generalization
Xiaofeng Lin, Hejian Sang, Zhipeng Wang +1
A prevailing view holds that supervised fine-tuning (SFT) memorizes training data and fails to generalize, whereas reinforcement learning (RL) attains broader robustness. We revisi…
stat.ML2024
Efficient Reinforcement Learning in Probabilistic Reward Machines
Xiaofeng Lin, Xuezhou Zhang
In this paper, we study reinforcement learning in Markov Decision Processes with Probabilistic Reward Machines (PRMs), a form of non-Markovian reward commonly found in robotics tas…