activity
20242026
most citedMellivora Capensis: A Backdoor-Free Training Framework on the Poisoned Dataset without Auxiliary Data

1 citations · 2 across the 24 of their papers we have counts for

collaborators
Showing 2026Show all

14 papers · 1 filter

cs.SE2026

StateWise: Diagnosing and Repairing Persistent Operational State Before Agent Actions

Yongyuan Peng, Zhou Feng, Tongying Wu +5

LLM agents combine reasoning, tool use, and persistent memory to support work across tasks by reusing stored operational records as premises for later actions. However, environment…

cs.CR2026

A Finger on the Scale: Covert Policy Steering through Agentic Skills

Jiarui Li, Jiahao Chen, Chunyi Zhou +5

Reusable agent skills extend large language model (LLM) agents with task procedures, tool-use guidance, and output constraints. Yet these skills also act as externalized behavioral…

cs.CR2026

The Shape of Ownership: Verifying LLM Provenance through Semantic Structures

Zhongrui Sun, Jiahao Chen, Oubo Ma +4

As large language models (LLMs) are increasingly redistributed, adapted, and served behind opaque APIs, model ownership can no longer be established reliably by inspecting model in…

cs.CR2026

Beyond Over-Refusal: Defending Indirect Prompt Injection via Latent Instruction Manifolds

Jiahao Chen, Rui Yin, Xinfeng Li +6

Large Language Models (LLMs) have been integrated into complex ecosystems (e.g., Code Agents), while Indirect Prompt Injection (IPI) attacks have emerged as critical barriers to th…

cs.CR2026

The Boy Who Cried Wolf: Adversarial Misclassification of Safe Inputs as Unsafe in Multimodal Guardrails

Shuo Shi, Rui Yin, Naen Xu +7

Multimodal guard models have emerged as critical safety components for screening content in vision-language systems. While adversarial research has extensively studied jailbreaking…

cs.CR2026

Lilith: Backdoor Generalization under Training-Inference Trigger Shift

Zhou Feng, Jiahao Chen, Chunyi Zhou +6

Machine-learning services increasingly rely on public data, third-party providers, and outsourced training, creating opportunities for data-poisoning attacks that implant persisten…

cs.CR2026

Flipping Minds by Flipping Bits: Decision-Level Cognitive Hijacking of Large Language Models

Yu Yan, Jiahao Chen, Siqi Lu +6

Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly relying on their outputs. Howe…

cs.CR2026

Customization under Fire: Plugin Poisoning in Text-to-Image Ecosystem

Jiahao Chen, Xing He, Yong Yang +6

The prosperity of text-to-image (T2I) models has fostered a vibrant share-and-play ecosystem centered on Low-Rank Adaptation (LoRA) plugins, which allow users to customize and shar…

cs.CV2026

Order within Chaos: Capturing Intrinsic Energy Anomalies for AI-Manipulated Image Forgery Localization

Yiming Wang, Baiqi Wu, Qingming Li +3

Recent advancements in generative AI have led to image editing models capable of producing realistic forgeries that evade traditional image forgery localization methods, as these a…

cs.LG2026

Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning

Oubo Ma, Ruixiao Lin, Yang Dai +4

Extensive research has highlighted the severe threats posed by backdoor attacks to deep reinforcement learning (DRL). However, prior studies primarily focus on vanilla scenarios, w…

cs.CR2026

Profiling for Pennies: Unveiling the Privacy Iceberg of LLM Agents

Jiahao Chen, Qi Zhang, Ruixiao Lin +7

Large Language Models (LLMs) have revolutionized how information are collected, aggregated, and reasoned. However, this enables a novel and accessible vector of privacy intrusion:…

cs.CR2026

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

Oubo Ma, Ruixiao Lin, Jiahao Chen +3

LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer review to commercial chatbots. This concern…

cs.CR2026

Unveiling the Security Risks of Federated Learning in the Wild: From Research to Practice

Jiahao Chen, Zhiming Zhao, Yuwen Pu +4

Federated learning (FL) has attracted substantial attention in both academia and industry, yet its practical security posture remains poorly understood. In particular, a large body…

cs.LG2026

Contextual and Seasonal LSTMs for Time Series Anomaly Detection

Lingpei Zhang, Qingming Li, Yong Yang +4

Univariate time series (UTS), where each timestamp records a single variable, serve as crucial indicators in web systems and cloud servers. Anomaly detection in UTS plays an essent…