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Xiaofeng Wang

7 papers hereh-index 597 citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4
  • last author2

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.HC1
  • cs.LG1
  • cs.SD1
same name
  • Xiaofeng Wang — 63 papers, h 35
  • Xiaofeng Wang — 28 papers
  • Xiaofeng Wang — 22 papers, h 12
  • Xiaofeng Wang — 20 papers, h 39
  • Xiaofeng Wang — 15 papers, h 61
  • Xiaofeng Wang — 15 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedA-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory

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

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2026

The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis

Peiran Wang, Xinfeng Li, Chong Xiang +5

The evolution of Large Language Models (LLMs) has resulted in a paradigm shift towards autonomous agents, necessitating robust security against Prompt Injection (PI) vulnerabilitie…

cs.CR2025

EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations

Xinyun Zhou, Xinfeng Li, Yinan Peng +9

Retrieval-Augmented Generation (RAG) systems are increasingly central to robust AI, enhancing large language model (LLM) faithfulness by incorporating external knowledge. However,…

cs.CR2025★ 1 cited

A-MemGuard: A Proactive Defense Framework for LLM-Based Agent Memory

Qianshan Wei, Tengchao Yang, Yaochen Wang +7

Large Language Model (LLM) agents use memory to learn from past interactions, enabling autonomous planning and decision-making in complex environments. However, this reliance on me…

cs.CR2025

The Man Behind the Sound: Demystifying Audio Private Attribute Profiling via Multimodal Large Language Model Agents

Lixu Wang, Kaixiang Yao, Xinfeng Li +4

Our research uncovers a novel privacy risk associated with multimodal large language models (MLLMs): the ability to infer sensitive personal attributes from audio data -- a techniq…

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