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cs.AI2026
Offline Policy Optimization with Posterior Sampling
Hongqiang Lin, Dongxu Zhang, Yiding Sun +3
A fundamental challenge in model-based offline reinforcement learning (RL) lies in the trade-off between generalization and robustness against exploitation errors in out-of-distrib…
cs.AI2026
Token-Importance Guided Direct Preference Optimization
Ning Yang, Hai Lin, Yibo Liu +3
Aligning Large Language Models (LLMs) with human preferences is crucial for safe and effective AI interactions. While popular methods like Direct Preference Optimization (DPO) have…