activity
20242026
collaborators

13 papers

cs.RO2026

Vision-Language-Action Safety: Threats, Challenges, Evaluations, and Mechanisms

Qi Li, Bo Yin, Weiqi Huang +6

Vision-Language-Action (VLA) models are emerging as a unified substrate for embodied intelligence. This shift raises a new class of safety challenges, stemming from the embodied na…

cs.CV2026

NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors

Lingfeng Ren, Weihao Yu, Runpeng Yu +1

Object hallucination is a critical issue in Large Vision-Language Models (LVLMs), where outputs include objects that do not appear in the input image. A natural question arises fro…

cs.LG2026

Refinement Provenance Inference: Detecting LLM-Refined Training Prompts from Model Behavior

Bo Yin, Qi Li, Runpeng Yu +1

Instruction tuning increasingly relies on LLM-based prompt refinement, where prompts in the training corpus are selectively rewritten by an external refiner to improve clarity and…

cs.CL2025

Every Step Counts: Decoding Trajectories as Authorship Fingerprints of dLLMs

Qi Li, Runpeng Yu, Haiquan Lu +1

Discrete Diffusion Large Language Models (dLLMs) have recently emerged as a competitive paradigm for non-autoregressive language modeling. Their distinctive decoding mechanism enab…

cs.LG2025

Discrete Diffusion in Large Language and Multimodal Models: A Survey

Runpeng Yu, Qi Li, Xinchao Wang

In this work, we provide a systematic survey of Discrete Diffusion Language Models (dLLMs) and Discrete Diffusion Multimodal Language Models (dMLLMs). Unlike autoregressive (AR) mo…

cs.CV2025

Vid-SME: Membership Inference Attacks against Large Video Understanding Models

Qi Li, Runpeng Yu, Xinchao Wang

Multimodal large language models (MLLMs) demonstrate remarkable capabilities in handling complex multimodal tasks and are increasingly adopted in video understanding applications.…