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Home/Authors/Hengxu Li

Hengxu Li

3 indexed papers

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

Publications per year

3
26

Top categories

AI×2Crypto×2NLP×1

Frequent co-authors

Chengzhengxu Li2×
Zhaohan Zhang2×
Guoxin Ma1×
Yibing Liu1×
Yu Liang1×
Yan Wang1×

Research Timeline

2026
MGTEVAL: An Interactive Platform for Systemtic Evaluation of Machine-Generated Text Detectors

The paper introduces MGTEVAL, a comprehensive and extensible platform designed to systematically evaluate the performance, robustness, and efficiency of machine-generated text detectors.

FragBench: Cross-Session Attacks Hidden in Benign-Looking Fragments

The paper introduces FragBench, a novel benchmark designed to detect malicious LLM attacks that are split across multiple, seemingly benign sessions, showing that cross-session graph modeling is necessary for effective defense.

Thinking as Compression: Your Reasoning Model is Secretly a Context Compressor

The paper introduces Thinking as Compression (TaC), a novel paradigm showing that the inherent reasoning process of a large language model can naturally compress long context inputs, outperforming dedicated compression methods.

Highlighted terms show continued research focus across papers

Papers

cs.AIRecentMay 27, 2026

Thinking as Compression: Your Reasoning Model is Secretly a Context Compressor

Guoxin Ma, Yibing Liu, Chengzhengxu Li, Yu Liang +6 more

The paper introduces Thinking as Compression (TaC), a novel paradigm showing that the inherent reasoning process of a large language model can naturally compress long context inputs, outperforming ded…

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cs.CRcs.AIRecentMay 10, 2026

FragBench: Cross-Session Attacks Hidden in Benign-Looking Fragments

Astha Mehta, Niruthiha Selvanayagam, Cedric Lam, Hengxu Li +9 more

The paper introduces FragBench, a novel benchmark designed to detect malicious LLM attacks that are split across multiple, seemingly benign sessions, showing that cross-session graph modeling is neces…

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cs.CRcs.CLRecentApr 28, 2026

MGTEVAL: An Interactive Platform for Systemtic Evaluation of Machine-Generated Text Detectors

Yuanfan Li, Qi Zhou, Chengzhengxu Li, Zhaohan Zhang +4 more

The paper introduces MGTEVAL, a comprehensive and extensible platform designed to systematically evaluate the performance, robustness, and efficiency of machine-generated text detectors.

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