activity
20202026
most citedFace It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logs

25 citations · 29 across the 40 of their papers we have counts for

collaborators

50 papers

cs.AI2026

LongRCA Bench: Diagnosing Responsible Roles and Root Causes in Long-Horizon Agent Failures

Yunfei Zhang, Boyu Feng, Changhua Pei +14

When a long-horizon agent execution fails, outcome-level evaluation reveals the unsuccessful result but not where the decisive error entered the trajectory. Developers must then in…

cs.SE2026

Towards Risk-free AI Agent Deployment

Yintong Huo, Rangeet Pan, Abhik Roychoudhury

LLM-based agents are rapidly moving from research prototypes into the core business processes of organizations, but these agents pose deployment risks to security, compliance, and…

cs.SE2026

Does It Render Everywhere? A Study of Cross-Environment Compatibility in MLLM-Generated Webpages

Ziyun Guo, Jingyu Xiao, Yuqiang Sun +1

Multimodal Large Language Models (MLLMs) have been increasingly adopted to automate webpage generation from visual designs (e.g., screenshots). However, existing evaluations are li…

cs.CV2026

CodeShrink: Adaptive Visual Compression for Efficient Multimodal Code Understanding

Wenxin Tang, Jingyu Xiao, Zhenyu Liu +6

Rendering source code as images offers a promising way to reduce the input costs of Multimodal Large Language Models (MLLMs). Adjusting image resolution can trade visual token cost…

cs.CR2026

Graph Is the Verifier: Agentic Reinforcement Learning for Interprocedural Vulnerability Detection

Yikun Li, Ting Zhang, Jiakun Liu +9

Real-world vulnerabilities often span multiple functions, yet most learning-based detectors classify each function in isolation: on a sample of real CVEs, we find that 71.7% of vul…

cs.SE2026

VisualRepair: Dynamic Tool Calling and Region Focusing for Visual Software Issue Repair

Jingyu Xiao, Zhongyi Zhang, Haoran Hou +4

Automated Program Repair (APR) has witnessed significant progress with the advent of Large Language Models (LLMs). However, as modern software systems increasingly expose rich grap…