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Home/Authors/Fei Huang

Fei Huang

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×2Crypto×2ML×1NLP×1

Frequent co-authors

Zhongyu He1×
Yuanfan Li1×
Tianyu Chen1×
Siyuan Chen1×
Xingyang Li1×
Meng Hsuan Yu1×

Research Timeline

2026
From Incomplete Architecture to Quantified Risk: Multimodal LLM-Driven Security Assessment for Cyber-Physical Systems

The paper introduces ASTRAL, a multimodal LLM-driven framework that reconstructs and analyzes fragmented cyber-physical system architectures to enable comprehensive and quantitative security risk assessment.

MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents

MemPrivacy introduces a novel framework that protects sensitive user data in edge-cloud memory systems by replacing private spans with semantically structured placeholders, thereby minimizing data exposure without sacrificing memory utility.

SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training

SIRI introduces a self-internalizing reinforcement learning framework that allows LLM agents to autonomously discover and integrate reusable skills directly into their core policy, significantly improving performance on complex tasks without external skill generators.

Highlighted terms show continued research focus across papers

Papers

cs.AIcs.LGRecentJun 1, 2026

SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training

Zhongyu He, Yuanfan Li, Fei Huang, Tianyu Chen +8 more

SIRI introduces a self-internalizing reinforcement learning framework that allows LLM agents to autonomously discover and integrate reusable skills directly into their core policy, significantly impro…

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cs.CRcs.CLRecentMay 10, 2026

MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents

Yining Chen, Jihao Zhao, Bo Tang, Haofen Wang +4 more

MemPrivacy introduces a novel framework that protects sensitive user data in edge-cloud memory systems by replacing private spans with semantically structured placeholders, thereby minimizing data exp…

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cs.CRcs.AIRecentApr 7, 2026

From Incomplete Architecture to Quantified Risk: Multimodal LLM-Driven Security Assessment for Cyber-Physical Systems

Shaofei Huang, Christopher M. Poskitt, Lwin Khin Shar

The paper introduces ASTRAL, a multimodal LLM-driven framework that reconstructs and analyzes fragmented cyber-physical system architectures to enable comprehensive and quantitative security risk asse…

View →