arxiv arXiv cs.LG · 53d ago · research

ATT&CK-Labeled Multi-Source Cybersecurity Logs Dataset Released

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A new dataset combines system, network, and browser logs from 870 Windows sessions, including 70 attacks and 800 benign cases. It provides per-event labels with MITRE ATT&CK technique IDs for 12 tactics and 53 techniques, using real attack tools like RAT and C2 tunnels. Fine-tuning three Small Language Models (SLMs) via LoRA improved chunk classification accuracy to 90–97% and achieved up to 42% exact-match accuracy in technique identification, showing strong reasoning capture despite challenges.

Importance 2/3 arXiv cs.LG Alibaba (Qwen) Microsoft Research Mistral AI AI agents Evaluation & benchmarks Reasoning models

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arxiv arXiv cs.CL · 53d ago

OPD-Evolver: On-Policy Distillation for Holistic Agent Evolving

OPD-Evolver introduces a slow-fast co-evolution framework that enables agents to select, act on, and reuse experience through on-policy self-distillation. It outperforms existing memory and training-based methods by up to 11.5% and 5.8% respectively, and demonstrates capability to challenge large-scale models like Qwen3.5-397B-A17B and Step-3.5-Flash.

arxiv arXiv cs.AI · 47d ago

LLMs Benchmarked for Web Vulnerability Detection

A study evaluates six LLMs on detecting real-world web vulnerabilities in WordPress plugins, finding detection rates vary by model and prompt design. Claude Opus 4.6 achieved the highest detection rate at 63%, while Qwen 3.5 only reached 35%, and no model consistently identified all baseline vulnerabilities across iterations.

arxiv arXiv cs.AI · 47d ago · 1 view

Benchmark Evaluation of Small Language Models for Arabic NLP

A benchmark of 240 Arabic test items across eight domains and ten skills assesses twelve small language models in zero-shot settings. Gemma 3 (12B) achieved the highest overall score (4.548/5), followed by Aya and C4AI Command Arabic, with performance linked more to Arabic alignment and instruction-following than model size. Common failure modes include prompt leakage, hallucination, and weak task adherence.

arxiv arXiv cs.CL · 47d ago · 6 views

Test-Time Steering Resolves Temporal Fact Conflicts in LLMs

Researchers identify parametric temporal conflicts in language models where outdated facts persist in parameters. They introduce Temporal Attractor Steering (TAS), a test-time method that resolves 29-57% of such conflicts without retraining, maintaining 85-99% accuracy on non-conflict queries and outperforming a baseline on three of four models.

arxiv arXiv cs.CL · 47d ago · 1 view

Factual Retrieval in LLMs Is Non-Contiguous and Redundant

Large language models use non-contiguous, redundant paths to retrieve factual attributes. These paths often skip layers and involve multiple equivalent routes, indicating distributed and redundant knowledge computation, challenging current understanding of LLM knowledge storage and retrieval.