Cybersecurity Detection Classification with Reasoning-enabled Language Models
Amol Khanna, Manu Nandan, Cristian Viorel Popa, Joan Pujol-Roig, Diana Bolocan, Laura Vasilie, Alexandru Apostu, Chase Helwig, Mihaela Gaman, Michael Brautbar, Edward Raff, Chase Midler, Sven Krasser
cs.LG, cs.CR
Submitted: 2026-07-30
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
- Towards AI-Driven Human-Machine Co-Teaming for Adaptive and Agile Cyber Security Operation Centers
- HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)
- Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
- Training Verifiers to Solve Math Word Problems
- Labeling NIDS Rules with MITRE ATT&CK Techniques: Machine Learning vs. Large Language Models
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Reinforced Self-Training (ReST) for Language Modeling
- Large Language Models for Security Operations Centers: A Comprehensive Survey
- V-STaR: Training Verifiers for Self-Taught Reasoners
- Before You Hand Over the Wheel: Evaluating LLMs for Security Incident Analysis
- Language Models (Mostly) Know What They Know
- DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
- Kimi k1.5: Scaling Reinforcement Learning with LLMs
- Tulu 3: Pushing Frontiers in Open Language Model Post-Training
- Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
- Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
- LogGPT: Exploring ChatGPT for Log-Based Anomaly Detection
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
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