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cs.LG2026
Save Your Saturated Data: Learning Beyond Reward Saturation in Group-Based RL
Ziyuan Yang, Yike Wang, Shangbin Feng +1
Group-relative reinforcement learning (RL) relies on reward variation among sampled responses to estimate informative relative advantages. As language models become increasingly ca…
cs.LG2025
Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment
Yizhuo Zhang, Heng Wang, Shangbin Feng +3
Previous research has sought to enhance the graph reasoning capabilities of LLMs by supervised fine-tuning on synthetic graph data. While these led to specialized LLMs better at so…