works on

From the 1 of 16 linked papers with an AI index.

activity
20242026
collaborators

16 papers

cs.CV2026

SafeGen: Goal-Conditioned Video Diffusion of Safety-Critical Scenarios for VLM-Based Autonomous Driving

Jiangfan Liu, Zexuan Cui, Tianyuan Zhang +7

VLMs are increasingly deployed in AD systems, creating an urgent need for rigorous safety evaluation under rare yet safety-critical scenarios. Among these, interactions with vulner…

cs.CV2026

Technical Report on the CVPR 2026@AdvML Workshop Challenge

Tianyuan Zhang, Zonglei Jing, Jiangfan Liu +47

The paper reports on the CVPR 2026@AdvML Workshop Challenge, which evaluated adversarial attacks on multimodal vision‑language agents for autonomous driving using multi‑view visual…

cs.AI2026

StainFlow: Entity-Stain Tracking and Evidence Linking for Process Rewards in GUI Agents

Haojie Hao, Longkun Hao, Yihang Lou +8

Reinforcement Learning (RL) has become a promising approach for improving GUI Agents in long-horizon, stochastic digital environments, but trajectory-level success feedback is too…

cs.AI2026

GuardAD: Safeguarding Autonomous Driving MLLMs via Markovian Safety Logic

Tianyuan Zhang, Peng Yue, Zihao Peng +8

Multimodal large language models (MLLMs) are increasingly integrated into autonomous driving (AD) systems; however, they remain vulnerable to diverse safety threats, particularly i…

cs.CR2026

Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw

Zonghao Ying, Xiao Yang, Siyang Wu +7

The rapid evolution of Large Language Models (LLMs) into autonomous, tool-calling agents has fundamentally altered the cybersecurity landscape. Frameworks like OpenClaw grant AI sy…

cs.LG2025

First-Order Error Matters: Accurate Compensation for Quantized Large Language Models

Xingyu Zheng, Haotong Qin, Yuye Li +5

Post-training quantization (PTQ) offers an efficient approach to compressing large language models (LLMs), significantly reducing memory access and computational costs. Existing co…