{"list":"other","total":102,"rows":[{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2410.21276","title":"GPT-4o System Card","created":"2024-10-25","cited_by_count":4588},{"id":"1706.08840","title":"Gradient Episodic Memory for Continual Learning","created":"2017-06-26","cited_by_count":1898},{"id":"2104.10350","title":"Carbon Emissions and Large Neural Network Training","created":"2021-04-21","cited_by_count":567},{"id":"1711.03902","title":"Neural-Symbolic Learning and Reasoning: A Survey and Interpretation","created":"2017-11-10","cited_by_count":196},{"id":"2402.09283","title":"Attacks, Defenses and Evaluations for LLM Conversation Safety: A Survey","created":"2024-02-14","cited_by_count":130},{"id":"2405.17238","title":"IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities","created":"2024-05-27","cited_by_count":103},{"id":"2010.09470","title":"Dos and Don'ts of Machine Learning in Computer Security","created":"2020-10-19","cited_by_count":102},{"id":"2403.01038","title":"AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attacks","created":"2024-03-02","cited_by_count":96},{"id":"2503.17332","title":"CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities","created":"2025-03-21","cited_by_count":96},{"id":"2406.01637","title":"Teams of LLM Agents can Exploit Zero-Day Vulnerabilities","created":"2024-06-02","cited_by_count":95},{"id":"2406.05590","title":"NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security","created":"2024-06-08","cited_by_count":93},{"id":"2404.13161","title":"CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models","created":"2024-04-19","cited_by_count":89},{"id":"2108.11451","title":"From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey","created":"2021-08-25","cited_by_count":72},{"id":"2405.03644","title":"When LLMs Meet Cybersecurity: A Systematic Literature Review","created":"2024-05-06","cited_by_count":71},{"id":"2108.09135","title":"PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier","created":"2021-08-20","cited_by_count":65},{"id":"2305.19951","title":"Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts","created":"2023-05-31","cited_by_count":63},{"id":"2406.07599","title":"CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence","created":"2024-06-11","cited_by_count":62},{"id":"2411.05185","title":"PentestAgent: Incorporating LLM Agents to Automated Penetration Testing","created":"2024-11-07","cited_by_count":47},{"id":"2105.14074","title":"Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning","created":"2021-05-28","cited_by_count":43},{"id":"2206.12227","title":"Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective","created":"2022-06-24","cited_by_count":42},{"id":"2501.05435","title":"Neuro-Symbolic AI in 2024: A Systematic Review","created":"2025-01-09","cited_by_count":38},{"id":"2207.12355","title":"Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation","created":"2022-07-25","cited_by_count":37},{"id":"2412.01778","title":"HackSynth: LLM Agent and Evaluation Framework for Autonomous Penetration Testing","created":"2024-12-02","cited_by_count":37},{"id":"2210.15889","title":"Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computing","created":"2022-10-28","cited_by_count":35},{"id":"2302.01242","title":"Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal","created":"2023-02-02","cited_by_count":33},{"id":"2501.13411","title":"VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework","created":"2025-01-23","cited_by_count":31},{"id":"2407.17788","title":"PenHeal: A Two-Stage LLM Framework for Automated Pentesting and Optimal Remediation","created":"2024-07-25","cited_by_count":30},{"id":"2207.06236","title":"Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities","created":"2022-07-13","cited_by_count":25},{"id":"2112.01156","title":"A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space","created":"2021-12-02","cited_by_count":22},{"id":"2203.00938","title":"Neuro-Symbolic Verification of Deep Neural Networks","created":"2022-03-02","cited_by_count":21},{"id":"2302.07200","title":"Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey","created":"2023-02-14","cited_by_count":21},{"id":"2405.12750","title":"Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities","created":"2024-05-21","cited_by_count":21},{"id":"2410.03225","title":"AutoPenBench: Benchmarking Generative Agents for Penetration Testing","created":"2024-10-04","cited_by_count":21},{"id":"2412.20787","title":"SecBench: A Comprehensive Multi-Dimensional Benchmarking Dataset for LLMs in Cybersecurity","created":"2024-12-30","cited_by_count":21},{"id":"2305.16734","title":"AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Model","created":"2023-05-26","cited_by_count":19},{"id":"2406.10368","title":"A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts","created":"2024-06-14","cited_by_count":19},{"id":"2403.12451","title":"End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations","created":"2024-03-19","cited_by_count":17},{"id":"2410.17351","title":"Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense","created":"2024-10-22","cited_by_count":17},{"id":"2005.11671","title":"Arms Race in Adversarial Malware Detection: A Survey","created":"2020-05-24","cited_by_count":16},{"id":"2403.00323","title":"Softened Symbol Grounding for Neuro-symbolic Systems","created":"2024-03-01","cited_by_count":16},{"id":"2409.11445","title":"Jailbreaking Large Language Models with Symbolic Mathematics","created":"2024-09-17","cited_by_count":16},{"id":"2503.11917","title":"A Framework for Evaluating Emerging Cyberattack Capabilities of AI","created":"2025-03-14","cited_by_count":16},{"id":"2208.13058","title":"Adversarial Robustness for Tabular Data through Cost and Utility Awareness","created":"2022-08-27","cited_by_count":15},{"id":"2401.02949","title":"Graph2Tac: Online Representation Learning of Formal Math Concepts","created":"2024-01-05","cited_by_count":15},{"id":"2503.00870","title":"NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks In Open Domains","created":"2025-03-02","cited_by_count":15},{"id":"2312.06798","title":"Building Trustworthy NeuroSymbolic AI Systems: Consistency, Reliability, Explainability, and Safety","created":"2023-12-05","cited_by_count":14},{"id":"2405.20441","title":"SECURE: Benchmarking Large Language Models for Cybersecurity","created":"2024-05-30","cited_by_count":14},{"id":"2407.02528","title":"Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Models","created":"2024-06-30","cited_by_count":14},{"id":"2410.21060","title":"CTINexus: Automatic Cyber Threat Intelligence Knowledge Graph Construction Using Large Language Models","created":"2024-10-28","cited_by_count":14},{"id":"2507.13169","title":"Prompt Injection 2.0: Hybrid AI Threats","created":"2025-07-17","cited_by_count":13},{"id":"2308.14016","title":"MITRE ATT&CK: State of the Art and Way Forward","created":"2023-08-27","cited_by_count":12},{"id":"2402.01889","title":"The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning","created":"2024-02-02","cited_by_count":12},{"id":"2303.16004","title":"A Survey on Malware Detection with Graph Representation Learning","created":"2023-03-28","cited_by_count":11},{"id":"2109.14868","title":"From Zero-Shot Machine Learning to Zero-Day Attack Detection","created":"2021-09-30","cited_by_count":10},{"id":"2401.03188","title":"A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence","created":"2024-01-06","cited_by_count":10},{"id":"2212.10388","title":"ThreatKG: An AI-Powered System for Automated Open-Source Cyber Threat Intelligence Gathering and Management","created":"2022-12-20","cited_by_count":9},{"id":"2407.08516","title":"Converging Paradigms: The Synergy of Symbolic and Connectionist AI in LLM-Empowered Autonomous Agents","created":"2024-07-11","cited_by_count":9},{"id":"2303.07557","title":"Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights","created":"2023-03-14","cited_by_count":8},{"id":"2411.00773","title":"LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation","created":"2024-11-01","cited_by_count":8},{"id":"2103.03080","title":"Analyzing the Usefulness of the DARPA OpTC Dataset in Cyber Threat Detection Research","created":"2021-03-04","cited_by_count":7},{"id":"2202.09994","title":"Transferring Adversarial Robustness Through Robust Representation Matching","created":"2022-02-21","cited_by_count":7},{"id":"2204.03433","title":"Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats","created":"2022-04-07","cited_by_count":7},{"id":"2310.17944","title":"A Survey on Trustworthy Edge Intelligence: From Security and Reliability To Transparency and Sustainability","created":"2023-10-27","cited_by_count":7},{"id":"2403.04017","title":"Learning Guided Automated Reasoning: A Brief Survey","created":"2024-03-06","cited_by_count":7},{"id":"2408.09224","title":"Neuro-Symbolic AI for Military Applications","created":"2024-08-17","cited_by_count":7},{"id":"2505.06913","title":"RedTeamLLM: an Agentic AI framework for offensive security","created":"2025-05-11","cited_by_count":7},{"id":"2408.03354","title":"The Use of Large Language Models (LLM) for Cyber Threat Intelligence (CTI) in Cybercrime Forums","created":"2024-08-06","cited_by_count":6},{"id":"2410.14219","title":"Formal Explanations for Neuro-Symbolic AI","created":"2024-10-18","cited_by_count":6},{"id":"2502.11269","title":"Unlocking the Potential of Generative AI through Neuro-Symbolic Architectures: Benefits and Limitations","created":"2025-02-16","cited_by_count":6},{"id":"2304.00485","title":"Graph Mining for Cybersecurity: A Survey","created":"2023-04-02","cited_by_count":5},{"id":"2304.10558","title":"Using Z3 for Formal Modeling and Verification of FNN Global Robustness","created":"2023-04-20","cited_by_count":5},{"id":"2311.16396","title":"Toward Effective Secure Code Reviews: An Empirical Study of Security-Related Coding Weaknesses","created":"2023-11-28","cited_by_count":5},{"id":"2402.17431","title":"The KANDY Benchmark: Incremental Neuro-Symbolic Learning and Reasoning with Kandinsky Patterns","created":"2024-02-27","cited_by_count":5},{"id":"2410.11209","title":"CRUcialG: Reconstruct Integrated Attack Scenario Graphs by Cyber Threat Intelligence Reports","created":"2024-10-15","cited_by_count":5},{"id":"2502.18528","title":"ARACNE: An LLM-Based Autonomous Shell Pentesting Agent","created":"2025-02-24","cited_by_count":5},{"id":"2504.17017","title":"Neural Theorem Proving: Generating and Structuring Proofs for Formal Verification","created":"2025-04-23","cited_by_count":5},{"id":"2407.05766","title":"Multi-agent Reinforcement Learning-based Network Intrusion Detection System","created":"2024-07-08","cited_by_count":4},{"id":"2410.08390","title":"KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data","created":"2024-10-10","cited_by_count":4},{"id":"2410.16383","title":"Designing Robust Cyber-Defense Agents with Evolving Behavior Trees","created":"2024-10-21","cited_by_count":4},{"id":"2408.04996","title":"On the use of neurosymbolic AI for defending against cyber attacks","created":"2024-08-09","cited_by_count":3},{"id":"2412.02875","title":"Out-of-Distribution Detection for Neurosymbolic Autonomous Cyber Agents","created":"2024-12-03","cited_by_count":3},{"id":"2502.08932","title":"On the Promise for Assurance of Differentiable Neurosymbolic Reasoning Paradigms","created":"2025-02-13","cited_by_count":3},{"id":"2505.05515","title":"Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience","created":"2025-05-07","cited_by_count":3},{"id":"2506.07882","title":"Evaluating explainable AI for deep learning-based network intrusion detection system alert classification","created":"2025-06-09","cited_by_count":3},{"id":"2507.08216","title":"Grounding Methods for Neural-Symbolic AI","created":"2025-07-10","cited_by_count":3},{"id":"2304.13229","title":"Generating Adversarial Examples with Task Oriented Multi-Objective Optimization","created":"2023-04-26","cited_by_count":2},{"id":"2406.00938","title":"A Synergistic Approach In Network Intrusion Detection By Neurosymbolic AI","created":"2024-06-03","cited_by_count":2},{"id":"2407.04009","title":"A Critical Assessment of Interpretable and Explainable Machine Learning for Intrusion Detection","created":"2024-07-04","cited_by_count":2},{"id":"2501.08561","title":"ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins","created":"2025-01-15","cited_by_count":2},{"id":"2502.15561","title":"A Defensive Framework Against Adversarial Attacks on Machine Learning-Based Network Intrusion Detection Systems","created":"2025-02-21","cited_by_count":2},{"id":"2207.09746","title":"Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling?","created":"2022-07-20","cited_by_count":1},{"id":"2411.00217","title":"ADAPT: A Game-Theoretic and Neuro-Symbolic Framework for Automated Distributed Adaptive Penetration Testing","created":"2024-10-31","cited_by_count":1},{"id":"2501.09379","title":"First Experiments with Neural cvc5","created":"2025-01-16","cited_by_count":1},{"id":"2501.16393","title":"Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning","created":"2025-01-26","cited_by_count":1},{"id":"2503.16392","title":"Graph of Effort: Quantifying Risk of AI Usage for Vulnerability Assessment","created":"2025-03-20","cited_by_count":1},{"id":"2503.22755","title":"Reasoning Under Threat: Symbolic and Neural Techniques for Cybersecurity Verification","created":"2025-03-27","cited_by_count":1},{"id":"2505.01328","title":"Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability","created":"2025-05-02","cited_by_count":1},{"id":"2505.21322","title":"Assured Autonomy with Neuro-Symbolic Perception","created":"2025-05-27","cited_by_count":1},{"id":"2506.04454","title":"Neurosymbolic Artificial Intelligence for Robust Network Intrusion Detection: From Scratch to Transfer Learning","created":"2025-06-04","cited_by_count":1}],"next_cursor":"100"}