Author

Lijun Li

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Preprint Sep 2026

CyberPersistBench: Evaluating LLM-Based Cyber Attackers on Installation and Persistence

While LLM-based attackers exhibit growing proficiency in vulnerability exploitation, most existing cybersecurity benchmarks suffer from single-stage truncation, prematurely terminating evaluation upon initial access. In practice, initial footholds are exceptionally fragile across operational disruptions such as service...

Su-Jin Chen, Lijun Li, Xu-Hong Wang et al. · 0 citations

Jul 2026

Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions

MisKnow-Agent is introduced, a controlled evaluation framework that constructs task-specific documents supporting manually audited false conclusions with controlled authority cues and source styles that evaluates DeerFlow and WebThinker with three backbone LLMs using a report-level false-conclusion adoption rate that c...

Peng-Yu Zhu, Lijun Li, Long-Ping Yang et al. · arXiv.org · 4 citations

#artificial intelligence Preprint May 2026

UniACE: A Unified Framework for Evaluating LLM Agentic Capabilities

This work presents UniACE, a unified framework for model-centric evaluation under an explicit, common execution condition, and reports agent benchmark outcomes as properties of an explicit evaluation configuration, enabling more interpretable and reproducible cross-benchmark comparisons.

Peng-Yu Zhu, Lijun Li, Yaxing Lyu et al. · 3 citations