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Distributionally Robust and Safe Imitation Learning
分布鲁棒性与安全性结合，提升模仿学习在不确定环境下的表现
arXiv:2607.13436v1 Announce Type: new Abstract: Imitation learning (IL) has achieved remarkable success in complex decision-making tasks. However, its…
2
Beyond the Performance Illusion: Structure-Aware Stratified Partitioning and Curriculum Distributionally Robust Optimization for Spatially Correlated Domains
直击空间相关数据建模的“性能幻觉”，用结构感知分层分区与课程式分布鲁棒优化，为泛化性提供新解。
arXiv:2607.02055v1 Announce Type: cross Abstract: Performance evaluation in AI systems commonly assumes that random dataset splits produce independent…
3
Distributionally Robust Listwise Preference Optimization
针对列表级偏好优化提出分布鲁棒方法，提升对齐稳定性与泛化能力。
arXiv:2607.01715v1 Announce Type: new Abstract: Existing robust preference optimization for language-model alignment mainly studies pairwise supervisi…
4
Distributionally Robust Reinforcement Learning with Human Feedback
直击偏好分布偏移痛点，用分布鲁棒优化为RLHF提供更可靠的对齐方案
arXiv:2503.00539v2 Announce Type: replace Abstract: Reinforcement learning from human feedback (RLHF) has evolved to be one of the main methods for fi…
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LLMs Can Better Capture Human Judgments--With the Right Prompts
简单提示策略就能让大模型更准确捕捉人类判断，突破其分布偏差与措辞敏感局限
arXiv:2606.12754v1 Announce Type: cross Abstract: Are large language models (LLMs) bad at capturing human judgment? Two commonly stated limitations ar…
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When Answers Stray from Questions: Hallucination Detection via Question-Answer Orthogonal Decomposition
新方法通过正交分解问答表征，实现高效幻觉检测，兼顾准确率与分布迁移鲁棒性。
arXiv:2605.14449v1 Announce Type: cross Abstract: Hallucination detection in large language models (LLMs) requires balancing accu racy, efficiency, an…