2 citations · 2 across the 4 of their papers we have counts for
8 papers
MMAligner: Safeguarding Multimodal Large Language Models through Representation Calibration
Shenyi Zhang, Keyan Guo, Zihao Wang +5
Multimodal large language models (MLLMs) often refuse unsafe text prompts yet generate harmful responses to semantically equivalent multimodal inputs. Existing defenses either rely…
SoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forward
Rupam Patir, Keyan Guo, Haipeng Cai +1
The increasing use of AI systems for code generation raises a central security question: what can today's models and coding agents actually do to produce secure code, where do they…
DualGauge: Automated Joint Security-Functionality Benchmarking of Specification-Only Code Generation by LLMs and Coding Agents
Rupam Patir, Keyan Guo, Suvadra Barua +5
Large language models (LLMs) and LLM-based coding agents are now used to generate code from natural-language specifications, yet ensuring such code is both functionally correct and…
Moderating Illicit Online Image Promotion for Unsafe User-Generated Content Games Using Large Vision-Language Models
Keyan Guo, Ayush Utkarsh, Wenbo Ding +5
Online user generated content games (UGCGs) are increasingly popular among children and adolescents for social interaction and more creative online entertainment. However, they pos…
ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning
Safayat Bin Hakim, Keyan Guo, Wenkai Tan +3
LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operator schemas, preconditions, an…
AgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purification
Tian Zhang, Yiwei Xu, Juan Wang +8
Large language model (LLM) agents increasingly rely on external tools and retrieval systems to autonomously complete complex tasks. However, this design exposes agents to indirect…