activity
20132026
most citedVulnerability Detection with Code Language Models: How Far Are We?

13 citations · 24 across the 20 of their papers we have counts for

collaborators

26 papers

cs.AI2026

RAC: A Relational Agent Contract for Constraint-Governed Engineering Tasks

Kaiyuan Zheng, Fengqing Jiang, Yichen Feng +6

Engineering agents must produce artifacts that satisfy exact, coupled constraints. Existing solutions often require agents to make semantic decisions and also derive consequences s…

cs.CV2026

TAPDreamer: Transferable Adversarial Patches for World Action Models

Xuanyu Lu, Fengqing Jiang, Kaiyuan Zheng +8

World models learn to predict how their environment will evolve, making them an important foundation for general-purpose robotic control. Yet world action models depend on camera i…

cs.CR2026

Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens

Peizhi Niu, Wenjie Qu, Shangding Gu +14

Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services. They take on system-level responsibilities…

cs.CL2026

GradShield: Alignment Preserving Finetuning

Zhanhao Hu, Xiao Huang, Patrick Mendoza +4

Large Language Models (LLMs) pose a significant risk of safety misalignment after finetuning, as models can be compromised by both explicitly and implicitly harmful data. Even some…

cs.AI2026

JobBench: Aligning Agent Work With Human Will

Yuetai Li, Yichen Feng, Zhangchen Xu +21

Current benchmarks for occupational AI agents are scoped primarily by economic values, telling a replacement story. We introduce JobBench, which evaluates AI agents on the workflow…

cs.LG2026

Polyhedral Instability Governs Regret in Online Learning

Yuetai Li, Fengqing Jiang, Yichen Feng +6

Many online decision problems over combinatorial actions are addressed via convex relaxations, leading to online convex optimization with piecewise linear objectives and induced po…

cs.LG2026

The WidthWall: A Strict Expressivity Hierarchy for Hypergraph Neural Networks

Fengqing Jiang, Yuetai Li, Yichen Feng +6

Hypergraphs provide a natural framework to model higher-order interactions in scientific, social, and biological systems. Hypergraph neural networks (HGNNs) aim to learn from such…

cs.CV2026

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

Yichen Feng, Yuetai Li, Chunjiang Liu +14

Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of these applications require an expl…

cs.CR2025

SeedAIchemy: LLM-Driven Seed Corpus Generation for Fuzzing

Aidan Wen, Norah A. Alzahrani, Jingzhi Jiang +5

We introduce SeedAIchemy, an automated LLM-driven corpus generation tool that makes it easier for developers to implement fuzzing effectively. SeedAIchemy consists of five modules…

cs.CR2025

Defending Against Prompt Injection with DataFilter

Yizhu Wang, Sizhe Chen, Raghad Alkhudair +2

When large language model (LLM) agents are increasingly deployed to automate tasks and interact with untrusted external data, prompt injection emerges as a significant security thr…

cs.CR2025

BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers?

Fengqing Jiang, Yichen Feng, Yuetai Li +3

The convergence of LLM-powered research assistants and AI-based peer review systems creates a critical vulnerability: fully automated publication loops where AI-generated research…

cs.CR2025

Preventing Prompt Injection with Type-Directed Privilege Separation

Dennis Jacob, Emad Alghamdi, Zhanhao Hu +2

Modern language models have enabled the development of agentic systems that achieve strong performance on reasoning-intensive tasks. Unfortunately, this has come with a security co…

cs.CR2025

PromptArmor: Simple yet Effective Prompt Injection Defenses

Tianneng Shi, Kaijie Zhu, Zhun Wang +13

Despite their potential, recent research has demonstrated that LLM agents are vulnerable to prompt injection attacks, where malicious prompts are injected into the agent's input, c…

cs.CR2025

JailbreaksOverTime: Detecting Jailbreak Attacks Under Distribution Shift

Julien Piet, Xiao Huang, Dennis Jacob +7

Safety and security remain critical concerns in AI deployment. Despite safety training through reinforcement learning with human feedback (RLHF) [ 32], language models remain vulne…

cs.CR2025★ 1 cited

PromptShield: Deployable Detection for Prompt Injection Attacks

Dennis Jacob, Hend Alzahrani, Zhanhao Hu +2

Application designers have moved to integrate large language models (LLMs) into their products. However, many LLM-integrated applications are vulnerable to prompt injections. While…

cs.CL2025

Can LLMs Ask Good Questions?

Yueheng Zhang, Xiaoyuan Liu, Yiyou Sun +5

We evaluate questions generated by large language models (LLMs) from context, comparing them to human-authored questions across six dimensions: question type, question length, cont…

cs.SE2024★ 13 cited

Vulnerability Detection with Code Language Models: How Far Are We?

Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim +6

In the context of the rising interest in code language models (code LMs) and vulnerability detection, we study the effectiveness of code LMs for detecting vulnerabilities. Our anal…

cs.CR2024

Jatmo: Prompt Injection Defense by Task-Specific Finetuning

Julien Piet, Maha Alrashed, Chawin Sitawarin +5

Large Language Models (LLMs) are attracting significant research attention due to their instruction-following abilities, allowing users and developers to leverage LLMs for a variet…

eess.SY2017

On the Structure and Computation of Random Walk Times in Finite Graphs

Andrew Clark, Basel Alomair, Linda Bushnell +1

We consider random walks in which the walk originates in one set of nodes and then continues until it reaches one or more nodes in a target set. The time required for the walk to r…

eess.SY2017

Combinatorial Algorithms for Control of Biological Regulatory Networks

Andrew Clark, Phillip Lee, Basel Alomair +2

Biological processes, including cell differentiation, organism development, and disease progression, can be interpreted as attractors (fixed points or limit cycles) of an underlyin…

eess.SY2016

Submodularity in Input Node Selection for Networked Systems

Andrew Clark, Basel Alomair, Linda Bushnell +1

Networked systems are systems of interconnected components, in which the dynamics of each component are influenced by the behavior of neighboring components. Examples of networked…

cs.IT2016★ 6 cited

Secret-Key Agreement with Public Discussion subject to an Amplitude Constraint

Marwen Zorgui, Zouheir Rezki, Basel Alomair +1

This paper considers the problem of secret-key agreement with public discussion subject to a peak power constraint on the channel input. The optimal input distribution is prove…

eess.SY2016

Adaptive Mitigation of Multi-Virus Propagation: A Passivity-Based Approach

Phillip Lee, Andrew Clark, Basel Alomair +2

Malware propagation poses a growing threat to networked systems such as computer networks and cyber-physical systems. Current approaches to defending against malware propagation ar…

math.OC2014

Input Selection for Performance and Controllability of Structured Linear Descriptor Systems

Andrew Clark, Basel Alomair, Linda Bushnell +1

A common approach to controlling complex networks is to directly control a subset of input nodes, which then controls the remaining nodes via network interactions. While techniques…