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Peng-Fei Li

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#artificial intelligence Preprint Oct 2026

KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts'intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks, and do not directly measure LLMs'ability to generate executable commands for real-world cy...

Peng-Fei Li, Naufal Suryanto, Si-Cheng Zhang et al. · 0 citations

Preprint Sep 2026

CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising

CAP is proposed, a single-stage humanoid locomotion policy that recovers this signal with a perceptive world-model encoder trained as a learned denoiser to reconstruct clean depth from a corrupted input, together with a co-active proprioceptive variational encoder that supplies depth-free body-state information.

Hong-Jin Chen, Zi-Jun Xu, Shi-Hao Ma et al. · 0 citations

#artificial intelligence Preprint Sep 2026

SAFIRE: Safety-Critical Benchmark for Fine-grained Fire and Smoke Understanding in Multimodal LLMs

SAFIRE is introduced, a large-scale benchmark for fire-smoke understanding in MLLMs, comprising 83K captioned images from 20 scenarios and 193K multiple-choice VQA (MCVQA) generated from a 9.7K-image subset, spanning 10 evaluation dimensions from basic perception to higher-order reasoning.

Peng-Fei Li, Naufal Suryanto, Si-Cheng Zhang et al. · 0 citations