collaborators

18 papers

cs.LG2026

ReOrder-OPD:Reliability-Aware Prompt Ordering for On-Policy Distillation

Ximo Zhu, Ruiqi Liu, Rong Wang +8

On-policy distillation (OPD) applies token-level teacher supervision to student-generated trajectories, but this supervision is not always reliable. Existing methods use local conf…

cs.RO2026

HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies

Zhiying Du, Bei Liu, Yaobo Liang +7

Generalist vision--language--action (VLA) policies are typically trained on heterogeneous mixtures of robot demonstrations spanning diverse embodiments, action spaces, and observat…

cs.LG2026

Constitutional On-Policy Safe Distillation

Ming Wen, Yuxuan Liu, Kun Yang +9

On-policy self-distillation (OPSD) has emerged as an efficient post-training paradigm by using a teacher conditioned on privileged information to provide dense token-level supervis…

cs.CY2026

When Medical Safety Alignment Fails: A Benchmark for Evaluating LLMs on High-Risk Medical Queries

Yige Li, Jun Sun, Wei Zhao +5

Large language models (LLMs) are increasingly used for medical and health-related questions, yet their safety in high-risk medical scenarios remains poorly understood. We introduce…

cs.CL2026

ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking

Yutao Wu, Xiao Liu, Yinghui Li +5

Knowledge poisoning poses a critical threat to Retrieval-Augmented Generation (RAG) systems by injecting adversarial content into knowledge bases, tricking Large Language Models (L…

cs.CR2026

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Xingjun Ma, Yifeng Gao, Yixu Wang +45

The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…