{"total":76,"rows":[{"id":"2506.19823","title":"Persona Features Control Emergent Misalignment","created":"2025-06-24","cited_by_count":86,"area":null},{"id":"2406.11147","title":"Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG","created":"2024-06-17","cited_by_count":68,"area":null},{"id":"2502.07049","title":"LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights","created":"2025-02-10","cited_by_count":47,"area":null},{"id":"2504.05408","title":"Frontier AI's Impact on the Cybersecurity Landscape","created":"2025-04-07","cited_by_count":21,"area":null},{"id":"2406.07595","title":"VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models","created":"2024-06-11","cited_by_count":11,"area":null},{"id":"2412.15004","title":"From Vulnerabilities to Remediation: A Systematic Literature Review of LLMs in Code Security","created":"2024-12-19","cited_by_count":10,"area":null},{"id":"2503.09433","title":"CASTLE: Benchmarking Dataset for Static Code Analyzers and LLMs towards CWE Detection","created":"2025-03-12","cited_by_count":10,"area":null},{"id":"2503.15554","title":"Rethinking the Evaluation of Secure Code Generation","created":"2025-03-18","cited_by_count":10,"area":null},{"id":"2509.10858","title":"Large Language Models for Security Operations Centers: A Comprehensive Survey","created":"2025-09-13","cited_by_count":9,"area":null},{"id":"2606.17283","title":"ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software","created":"2026-06-15","cited_by_count":9,"area":null},{"id":"2606.04460","title":"CyberGym-E2E: Scalable Real-World Benchmark for AI Agents' End-to-End Cybersecurity Capabilities","created":"2026-06-03","cited_by_count":8,"area":null},{"id":"2408.04125","title":"VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs","created":"2024-08-07","cited_by_count":7,"area":null},{"id":"2503.10784","title":"Vulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview","created":"2025-03-13","cited_by_count":7,"area":null},{"id":"2407.03093","title":"Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets","created":"2024-07-03","cited_by_count":6,"area":null},{"id":"2510.00317","title":"MAVUL: Multi-Agent Vulnerability Detection via Contextual Reasoning and Interactive Refinement","created":"2025-09-30","cited_by_count":6,"area":null},{"id":"2510.14036","title":"One Bug, Hundreds Behind: LLMs for Large-Scale Bug Discovery","created":"2025-10-15","cited_by_count":6,"area":null},{"id":"2512.16538","title":"A Systematic Study of Code Obfuscation Against LLM-based Vulnerability Detection","created":"2025-12-18","cited_by_count":5,"area":null},{"id":"2601.18844","title":"Reducing False Positives in Static Bug Detection with LLMs: An Empirical Study in Industry","created":"2026-01-26","cited_by_count":5,"area":null},{"id":"2410.11096","title":"SeCodePLT: A Unified Platform for Evaluating the Security of Code GenAI","created":"2024-10-14","cited_by_count":4,"area":null},{"id":"2412.12039","title":"Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection","created":"2024-12-16","cited_by_count":4,"area":null},{"id":"2503.14281","title":"XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants","created":"2025-03-18","cited_by_count":4,"area":null},{"id":"2507.09508","title":"A Mixture of Linear Corrections Generates Secure Code","created":"2025-07-13","cited_by_count":4,"area":null},{"id":"2509.19117","title":"LLM-based Vulnerability Discovery through the Lens of Code Metrics","created":"2025-09-23","cited_by_count":4,"area":null},{"id":"2412.13737","title":"On the Compression of Language Models for Code: An Empirical Study on CodeBERT","created":"2024-12-18","cited_by_count":3,"area":null},{"id":"2507.16887","title":"Revisiting Pre-trained Language Models for Vulnerability Detection","created":"2025-07-22","cited_by_count":3,"area":null},{"id":"2508.16625","title":"Data and Context Matter: Towards Generalizing AI-based Software Vulnerability Detection","created":"2025-08-14","cited_by_count":3,"area":null},{"id":"2508.18933","title":"VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation","created":"2025-08-26","cited_by_count":3,"area":null},{"id":"2408.02153","title":"ARVO: Atlas of Reproducible Vulnerabilities for Open-Source Software","created":"2024-08-04","cited_by_count":2,"area":null},{"id":"2409.18395","title":"Code Vulnerability Repair with Large Language Model using Context-Aware Prompt Tuning","created":"2024-09-27","cited_by_count":2,"area":null},{"id":"2505.13353","title":"Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2509.04260","title":"An Empirical Study of Vulnerabilities in Python Packages and Their Detection","created":"2025-09-04","cited_by_count":2,"area":null},{"id":"2512.09006","title":"Llama-based source code vulnerability detection: Prompt engineering vs Fine tuning","created":"2025-12-09","cited_by_count":2,"area":null},{"id":"2602.23407","title":"Learning to Generate Secure Code via Token-Level Rewards","created":"2026-02-26","cited_by_count":2,"area":null},{"id":"2408.16028","title":"ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data","created":"2024-08-28","cited_by_count":1,"area":null},{"id":"2503.08228","title":"Investigating Execution-Aware Language Models for Code Optimization","created":"2025-03-11","cited_by_count":1,"area":null},{"id":"2507.20977","title":"Repairing vulnerabilities without invisible hands. A differentiated replication study on LLMs","created":"2025-07-28","cited_by_count":1,"area":null},{"id":"2510.17163","title":"TREAT: A Code LLMs Trustworthiness / Reliability Evaluation and Testing Framework","created":"2025-10-20","cited_by_count":1,"area":null},{"id":"2512.01255","title":"Large Language Models Cannot Reliably Detect Vulnerabilities in JavaScript: The First Systematic Benchmark and Evaluation","created":"2025-12-01","cited_by_count":1,"area":null},{"id":"2602.00305","title":"Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2602.01187","title":"Autoregressive, Yet Revisable: In Decoding Revision for Secure Code Generation","created":"2026-02-01","cited_by_count":1,"area":null},{"id":"2603.17974","title":"Toward Scalable Automated Repository-Level Datasets for Software Vulnerability Detection","created":"2026-03-18","cited_by_count":1,"area":null},{"id":"2605.09461","title":"VulTriage: Triple-Path Context Augmentation for LLM-Based Vulnerability Detection","created":"2026-05-10","cited_by_count":1,"area":null},{"id":"2606.20502","title":"Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2607.05842","title":"Beyond Refusal: A Same-Lineage Study of Aligned and Abliterated LLMs for Vulnerability Analysis","created":"2026-07-07","cited_by_count":1,"area":null},{"id":"2412.11194","title":"Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points","created":"2024-12-15","cited_by_count":0,"area":null},{"id":"2507.08540","title":"White-Basilisk: A Hybrid Model for Code Vulnerability Detection","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2509.09192","title":"ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction?","created":"2025-09-11","cited_by_count":0,"area":null},{"id":"2509.15195","title":"Orion: Fuzzing Workflow Automation","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2510.11202","title":"Evaluating Line-level Localization Ability of Learning-based Code Vulnerability Detection Models","created":"2025-10-13","cited_by_count":0,"area":null},{"id":"2510.27675","title":"On the Difficulty of Selecting Few-Shot Examples for Effective LLM-based Vulnerability Detection","created":"2025-10-31","cited_by_count":0,"area":null},{"id":"2512.10485","title":"From Lab to Reality: A Practical Evaluation of Deep Learning Models and LLMs for Vulnerability Detection","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2512.12536","title":"Diverse LLMs vs. Vulnerabilities: Who Detects and Fixes Them Better?","created":"2025-12-14","cited_by_count":0,"area":null},{"id":"2512.14500","title":"C-ing Clearly: Enhanced Binary Code Explanations using C code","created":"2025-12-16","cited_by_count":0,"area":null},{"id":"2512.18456","title":"SoK: Understanding (New) Security Issues Across AI4Code Use Cases","created":"2025-12-20","cited_by_count":0,"area":null},{"id":"2601.02438","title":"Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection","created":"2026-01-05","cited_by_count":0,"area":null},{"id":"2604.01637","title":"Seclens: Role-specific Evaluation of LLM's for security vulnerablity detection","created":"2026-04-02","cited_by_count":0,"area":null},{"id":"2605.05807","title":"LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.13138","title":"A Comprehensive Evaluation of Code Language Models for Security Patch Detection","created":"2026-05-13","cited_by_count":0,"area":null},{"id":"2605.17416","title":"Benchmarking Mythos-Linked Bug Rediscovery","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2605.21615","title":"ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2605.23243","title":"Are Frontier LLMs Ready for Cybersecurity? Evidence for Vertical Foundation Models from Dual-Mode Vulnerability Benchmarks","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2606.19149","title":"OpenAnt: LLM-Powered Vulnerability Discovery Through Code Decomposition, Adversarial Verification, and Dynamic Testing","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2606.30587","title":"Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2607.03215","title":"Builder, Defender, Breaker: Measurable Independence and Bounded Autonomy When Generative Models Build, Defend and Test Software","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2607.03350","title":"LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2607.07881","title":"Functional and Secure Code Generation with Task Vectors","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2607.27030","title":"HoF-Bench: Rediscovering Real AI-Discovered CVEs Without Frontier Models","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2608.15412","title":"Invariant Pretraining for Robust Code Representations","created":"2026-08-15","cited_by_count":0,"area":null},{"id":"2608.16970","title":"Probing the Prefill: Detecting Code Vulnerabilities via Latent Activations","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2608.21107","title":"Large Language Models at the Intersection of Software Engineering and Software Security:An Evidence-Centered Structured Survey and Research Agenda","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.18496","title":"MiST: Mid-Training LLMs for Cybersecurity","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.26749","title":"Metrics Failure in LLM-Based Code Vulnerability Repair: An Empirical Study and a Change-Aware Screen","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.32890","title":"A Function-Level Vulnerability Score Measures Flag Rate More Than the Model: Protocol Effects on Paired Benchmarks","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2610.05103","title":"VulValidate: Auditing Function-Level Vulnerability Labels with Executable Evidence","created":"2026-10-04","cited_by_count":0,"area":null},{"id":"2610.08405","title":"Learning from Failures: A Failure-Driven Prompt Refinement for LLM-Based Vulnerability Analysis","created":"2026-10-06","cited_by_count":0,"area":null},{"id":"2610.14296","title":"Diagnosing Generalization Boundaries in AI-Based Vulnerability Detection via Calibrated Embedding Distances","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}