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Large Language Model for Vulnerability Detection and Repair: Literature Review and the Road Ahead
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10664-022-10216-4openalex-snapshot
SPVF: security property assisted vulnerability fixing via attention-based models
inferredcites →https://doi.org/10.1007/s10664-023-10346-3openalex-snapshot
AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities
inferredcites →https://doi.org/10.1007/s11704-024-40231-1openalex-snapshot
A survey on large language model based autonomous agents
inferredcites →https://doi.org/10.1016/j.future.2024.107504openalex-snapshot
DetectVul: A statement-level code vulnerability detection for Python
inferredcites →https://doi.org/10.1016/j.infsof.2010.12.010openalex-snapshot
Identifying relevant studies in software engineering
inferredcites →https://doi.org/10.1016/j.jss.2023.111623openalex-snapshot
CSGVD: A deep learning approach combining sequence and graph embedding for source code vulnerability detection
inferredcites →https://doi.org/10.1109/acsac14895.2008openalex-snapshot
2008 Annual Computer Security Applications Conference (ACSAC)
inferredcites →https://doi.org/10.1109/ase56229.2023openalex-snapshot
2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)
inferredcites →https://doi.org/10.1109/ase56229.2023.00144openalex-snapshot
When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection
inferredcites →https://doi.org/10.1109/ase56229.2023.00157openalex-snapshot
The Devil is in the Tails: How Long-Tailed Code Distributions Impact Large Language Models
inferredcites →https://doi.org/10.1109/dsc59305.2023openalex-snapshot
2023 8th International Conference on Data Science in Cyberspace (DSC)
inferredcites →https://doi.org/10.1109/dsc59305.2023.00041openalex-snapshot
Software Vulnerability Detection with GPT and In-Context Learning
inferredcites →https://doi.org/10.1109/icse.1993.346061openalex-snapshot
Proceedings of 1993 15th International Conference on Software Engineering
inferredcites →https://doi.org/10.1109/icse48619.2023openalex-snapshot
2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)
inferredcites →https://doi.org/10.1109/icse48619.2023.00022openalex-snapshot
Data Quality for Software Vulnerability Datasets
inferredcites →https://doi.org/10.1109/icse48619.2023.00188openalex-snapshot
An Empirical Study of Deep Learning Models for Vulnerability Detection
inferredcites →https://doi.org/10.1109/icse48619.2023.00192openalex-snapshot
Does data sampling improve deep learning-based vulnerability detection? Yeas! and Nays!
inferredcites →https://doi.org/10.1109/icsme55016.2022openalex-snapshot
2022 IEEE International Conference on Software Maintenance and Evolution (ICSME)
inferredcites →https://doi.org/10.1109/ijcnn54540.2023openalex-snapshot
2023 International Joint Conference on Neural Networks (IJCNN)
inferredcites →https://doi.org/10.1109/ijcnn55064.2022.9892280openalex-snapshot
VulBERTa: Simplified Source Code Pre-Training for Vulnerability Detection
inferredcites →https://doi.org/10.1109/infocomwkshps51825.2021.9484500openalex-snapshot
Security Vulnerability Detection Using Deep Learning Natural Language Processing
inferredcites →https://doi.org/10.1109/issrew60843.2023.00058openalex-snapshot
Software Vulnerability Detection using Large Language Models
inferredcites →https://doi.org/10.1109/jproc.2020.2993293openalex-snapshot
Software Vulnerability Detection Using Deep Neural Networks: A Survey
inferredcites →https://doi.org/10.1109/scam59687.2023.00024openalex-snapshot
Leveraging User-Defined Identifiers for Counterfactual Data Generation in Source Code Vulnerability Detection
inferredcites →https://doi.org/10.1109/scam59687.2023.00026openalex-snapshot
PTLVD:Program Slicing and Transformer-based Line-level Vulnerability Detection System
inferredcites →https://doi.org/10.1109/sp46215.2023openalex-snapshot
2023 IEEE Symposium on Security and Privacy (SP)
inferredcites →https://doi.org/10.1109/tdsc.2023.3308897openalex-snapshot
Pre-Trained Model-Based Automated Software Vulnerability Repair: How Far are We?
inferredcites →https://doi.org/10.1109/tse.2022.3147265openalex-snapshot
Neural Transfer Learning for Repairing Security Vulnerabilities in C Code
inferredcites →https://doi.org/10.1109/tse.2022.3156637openalex-snapshot
SeqTrans: Automatic Vulnerability Fix Via Sequence to Sequence Learning
inferredcites →https://doi.org/10.1109/tse.2023.3286586openalex-snapshot
Vulnerability Detection by Learning From Syntax-Based Execution Paths of Code
inferredcites →https://doi.org/10.1145/2187671.2187673openalex-snapshot
Mitigating program security vulnerabilities
inferredcites →https://doi.org/10.1145/2601248.2601268openalex-snapshot
Guidelines for snowballing in systematic literature studies and a replication in software engineering
inferredcites →https://doi.org/10.1145/2677832openalex-snapshot
Proceedings of the 6th Asia-Pacific Symposium on Internetware on Internetware
inferredcites →https://doi.org/10.1145/3092566openalex-snapshot
Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques
inferredcites →https://doi.org/10.1145/3510003.3510146openalex-snapshot
Natural attack for pre-trained models of code
inferredcites →https://doi.org/10.1145/3520312.3534862openalex-snapshot
A systematic evaluation of large language models of code
inferredcites →https://doi.org/10.1145/3540250.3549098openalex-snapshot
VulRepair: a T5-based automated software vulnerability repair
inferredcites →https://doi.org/10.1145/3540250.3549162openalex-snapshot
NatGen: generative pre-training by “naturalizing” source code
inferredcites →https://doi.org/10.1145/3564625.3567985openalex-snapshot
Transformer-Based Language Models for Software Vulnerability Detection
inferredcites →https://doi.org/10.1145/3597503.3608128openalex-snapshot
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
inferredcites →https://doi.org/10.1145/3597503.3608141openalex-snapshot
Toward Improved Deep Learning-based Vulnerability Detection
inferredcites →https://doi.org/10.1145/3597503.3639212openalex-snapshot
Combining Structured Static Code Information and Dynamic Symbolic Traces for Software Vulnerability Prediction
inferredcites →https://doi.org/10.1145/3597503.3639218openalex-snapshot
On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities
inferredcites →https://doi.org/10.1145/3597926.3598037openalex-snapshot
Understanding and Tackling Label Errors in Deep Learning-Based Vulnerability Detection (Experience Paper)
inferredcites →https://doi.org/10.1145/3597926.3598135openalex-snapshot
How Effective Are Neural Networks for Fixing Security Vulnerabilities
inferredcites →https://doi.org/10.1145/3607199.3607242openalex-snapshot
DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection
inferredcites →https://doi.org/10.1145/3611643openalex-snapshot
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
inferredcites →https://doi.org/10.1145/3611643.3616262openalex-snapshot
Comparison and Evaluation on Static Application Security Testing (SAST) Tools for Java
inferredcites →https://doi.org/10.1145/3611643.3616358openalex-snapshot
Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation
inferredcites →https://doi.org/10.1145/3631974openalex-snapshot
A Survey of Learning-based Automated Program Repair
inferredcites →https://doi.org/10.1145/3632746openalex-snapshot
Vision Transformer Inspired Automated Vulnerability Repair
inferredcites →https://doi.org/10.1145/3635711openalex-snapshot
Representation Learning for Stack Overflow Posts: How Far Are We?
inferredcites →https://doi.org/10.1145/3639476.3639762openalex-snapshot
Large Language Model for Vulnerability Detection: Emerging Results and Future Directions
inferredcites →https://doi.org/10.1145/3643991.3644919openalex-snapshot
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
inferredcites →https://doi.org/10.1145/3649506openalex-snapshot
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
inferredcites →https://doi.org/10.1145/3658644openalex-snapshot
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.1145/3671016.3671388openalex-snapshot
DFEPT: Data Flow Embedding for Enhancing Pre-Trained Model Based Vulnerability Detection
inferredcites →https://doi.org/10.1145/3671016.3674807openalex-snapshot
MatsVD: Boosting Statement-Level Vulnerability Detection via Dependency-Based Attention
inferredcites →https://doi.org/10.1155/2022/1176898openalex-snapshot
Code Vulnerability Detection Based on Deep Sequence and Graph Models: A Survey
inferredcites →https://doi.org/10.1186/s13638-023-02242-7openalex-snapshot
VulRep: vulnerability repair based on inducing commits and fixing commits
inferredcites →https://doi.org/10.18293/seke2023-077openalex-snapshot
Practices and Challenges of Using GitHub Copilot: An Empirical Study
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.443openalex-snapshot
Code and Named Entity Recognition in StackOverflow
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.139openalex-snapshot
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.685openalex-snapshot
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
inferredcites →https://doi.org/10.18653/v1/2021.naacl-main.211openalex-snapshot
Unified Pre-training for Program Understanding and Generation
inferredcites →https://doi.org/10.18653/v1/2023.acl-long.557openalex-snapshot
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
inferredcites →https://doi.org/10.18653/v1/2023.findings-emnlp.620openalex-snapshot
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy
inferredcites →https://doi.org/10.3115/1075218openalex-snapshot
Proceedings of the 38th Annual Meeting on Association for Computational Linguistics - ACL '00
inferredcites →https://doi.org/10.48550/arxiv.2307.16789openalex-snapshot
Counterfactually Auditable Lifecycle Certification for Autonomous Agents
inferredcites →https://doi.org/10.48550/arxiv.2401.06059openalex-snapshot
Investigating Data Contamination for Pre-training Language Models
inferredcites →https://doi.org/10.48550/arxiv.2402.06196openalex-snapshot
Large Language Models: A Survey
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Simple Yet Practical Backdoor Prompt Attack Against Black‐Box Code Summarization Engines
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Syn2Vec: A Semantic‐Aware Initialization Method for AST Path–Based Code Representation
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An Approach of Structure‐Enhanced Code‐Centric Graph Learning for Just‐in‐Time Software Vulnerability Detection
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To Patch or Not to Patch: Motivations, Challenges, and Implications for Cybersecurity
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Vulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview
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Evaluating Large Language Models for Vulnerability Detection Under Realistic Conditions
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Llama-Based Source Code Vulnerability Detection: Prompt Engineering vs Fine Tuning
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An Empirical Study of Large Language Models as Experts in Software Trustworthiness Assessment
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MCTS-VUL: Self-training Large Language Models via Monte Carlo Tree Search for Vulnerability Detection
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TriVul: Improving Precision of Static Vulnerability Detection through Multi-agent Reasoning
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SCTS: Self-Critique Tree Search for Out-of-Distribution Vulnerability Detection
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Vul4Py: Benchmarking Automated Vulnerability Repair in Python with Paired Exploit and Functional Oracles
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Token-Efficient Binary Vulnerability Prioritization via Function Pre-filtering with LLMs
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Deep Learning Techniques for Enhancing the Efficiency of Security Patch Development
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Large language models for software vulnerability detection: a guide for researchers on models, methods, techniques, datasets, and metrics
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SIFT: enhance the performance of vulnerability detection by incorporating structural knowledge and multi-task learning
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GPTVD: vulnerability detection and analysis method based on LLM’s chain of thoughts
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Robust vulnerability detection with limited data via training-efficient adversarial reprogramming
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Assessing the effectiveness of large language models for Java vulnerability repair: A comparative study
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HSF-Vul: hierarchical semantic fusion for vulnerability detection
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Test case generation using large language models: a systematic literature review
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HFE-DDL: hybrid feature extraction and dual deep learning for android code vulnerability detection
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Human-AI experience in integrated development environments: a systematic literature review
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AdvGen-X: Transferability driven adversarial example generation for pre-trained models of code
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The Versatility of Large Language Models: A Comprehensive Review and Structured Survey of Architectures, Applications, Challenges, and Future Trajectories
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CodeSAGE: A multi-feature fusion vulnerability detection approach using code attribute graphs and attention mechanisms
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A lightweight transformer based multi task learning model with dynamic weight allocation for improved vulnerability prediction
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Robust Vulnerability Estimation in Industrial Firmware via Incomplete Knowledge Graph Similarity
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Multi-Agent Auditing for Smart Contracts*
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AgenticVM: Agentic AI for Adaptive Software Vulnerability Management
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UntrustVul: Automated Untrustworthy Alert Identification in Vulnerability Detection Models
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Expert-in-the-Loop Systems with Cross-Domain and in-Domain Few-Shot Learning for Software Vulnerability Detection
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Large Language Models and Agentic AI for Vulnerability Management: A Systematic Review
inferred← citeshttps://doi.org/10.1145/3712003openalex-snapshot
LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision, and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3715106openalex-snapshot
Testing and Debugging Quantum Programs: The Road to 2030
inferred← citeshttps://doi.org/10.1145/3742876openalex-snapshot
Proceedings of the 24th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences
inferred← citeshttps://doi.org/10.1145/3742876.3742881openalex-snapshot
Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation
inferred← citeshttps://doi.org/10.1145/3744916.3773260openalex-snapshot
INTENTFIX: Automated Logic Vulnerability Repair via LLM-Driven Intent Modeling
inferred← citeshttps://doi.org/10.1145/3758326openalex-snapshot
A Language-based Approach to Macroprogramming for IoT Systems through Large Language Models
inferred← citeshttps://doi.org/10.1145/3763163openalex-snapshot
Large Language Model Powered Symbolic Execution
inferred← citeshttps://doi.org/10.1145/3786165.3788439openalex-snapshot
LLMs in Code Vulnerability Analysis: A Proof of Concept
inferred← citeshttps://doi.org/10.1145/3786165.3788441openalex-snapshot
Bridging Code Property Graphs and Language Models for Program Analysis
inferred← citeshttps://doi.org/10.1145/3786181.3788714openalex-snapshot
Multi-task Code LLMs: Data Mix or Model Merge?
inferred← citeshttps://doi.org/10.1145/3786582.3786847openalex-snapshot
Not All Input Helps: What Information Should We Feed to LLMs for Vulnerability Repair?
inferred← citeshttps://doi.org/10.1145/3786583.3786910openalex-snapshot
Reducing False Positives in Static Bug Detection with LLMs: An Empirical Study in Industry
inferred← citeshttps://doi.org/10.1145/3787202openalex-snapshot
Survey on Learning-based Dynamic Fault Localization: From Traditional Machine Learning to Large Language Models
inferred← citeshttps://doi.org/10.1145/3797276openalex-snapshot
LLM-as-a-Judge for Software Engineering: Literature Review, Vision, and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3797277openalex-snapshot
vul-rag : Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG
inferred← citeshttps://doi.org/10.1145/3798054openalex-snapshot
Every Maintenance Has Its Exemplar: The Future of Software Maintenance through Migration
inferred← citeshttps://doi.org/10.1145/3802827openalex-snapshot
Enhancing Automated Unit Test Generation with Large Language Models: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1145/3808105openalex-snapshot
It Takes Two: Option-Aware Directed Greybox Fuzzing for Vulnerability PoC Generation
inferred← citeshttps://doi.org/10.1145/3808197openalex-snapshot
Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3808212openalex-snapshot
RAT: Retrieval-Augmented Testing of Certificate Revocation List Parsers in TLS Implementations
inferred← citeshttps://doi.org/10.1145/3808300openalex-snapshot
Exploiting Sophisticated Static Analysis for Verilog
inferred← citeshttps://doi.org/10.1145/3815425openalex-snapshot
A Systematic Literature Review on Detecting Software Vulnerabilities with Large Language Models
inferred← citeshttps://doi.org/10.1145/3816250openalex-snapshot
Hunk-Constrained DPO: Segment-Level Optimization for Secure and Correct LLM Code Generation
inferred← citeshttps://doi.org/10.1145/3819579openalex-snapshot
Mobile App Analysis in the New Era: Challenges and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3832299openalex-snapshot
Silence of Commit Messages: An Empirical Study for Vulnerability Commit Message Generation using Large Language Models
inferred← citeshttps://doi.org/10.1145/3832783.3834497openalex-snapshot
Top-Down Multi-agent LLM System with Runtime Data for MISRA C Violation Detection
inferred← citeshttps://doi.org/10.1145/3832783.3837465openalex-snapshot
Harnessing Uncertainty in Code Language Models: Lessons from Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3832783.3837521openalex-snapshot
To Think or Not to Think: Evaluating LLM Reasoning and Agents in Vulnerability Detection
inferred← citeshttps://doi.org/10.1145/3833907.3833914openalex-snapshot
Automated Expansion of Open-Source Software Vulnerability-Fix Pairs: A Multisource Collaborative Crawling Framework
inferred← citeshttps://doi.org/10.1186/s42400-025-00361-wopenalex-snapshot
When LLMs meet cybersecurity: a systematic literature review
inferred← citeshttps://doi.org/10.1186/s42400-026-00570-xopenalex-snapshot
Litevul: a lightweight vulnerability detection via directed PPMI-weighted token graphs
inferred← citeshttps://doi.org/10.1186/s44147-026-00926-7openalex-snapshot
Towards sustainable grid security: a lightweight adaptive framework for power system software vulnerability detection
inferred← citeshttps://doi.org/10.14500/aro.12082openalex-snapshot
A Systematic Survey on Large Language Models for Static Code Analysis
inferred← citeshttps://doi.org/10.1631/fitee.2500038openalex-snapshot
Large language model-enhanced probabilistic modeling for effective static analysis alarms
inferred← citeshttps://doi.org/10.2139/ssrn.5382161openalex-snapshot
A Targetable Machine Learning Model for Effective Vulnerability Repair in Smart Contracts
inferred← citeshttps://doi.org/10.2139/ssrn.7203093openalex-snapshot
Decoupling Safety Assessment from Code Generation: Iterative Refinement with External Signals
inferred← citeshttps://doi.org/10.2139/ssrn.7442690openalex-snapshot
AgentSAST: A Knowledge-Driven Neuro-Symbolic Agent for Vulnerability Detection
inferred← citeshttps://doi.org/10.33411/ijist/1623openalex-snapshot
Improving Software Security Through an LLM-Based Vulnerability Detection Model
inferred← citeshttps://doi.org/10.3390/app15126651openalex-snapshot
Advancing Software Vulnerability Detection with Reasoning LLMs: DeepSeek-R1′s Performance and Insights
inferred← citeshttps://doi.org/10.3390/bdcc10090303openalex-snapshot
A Real CVE-Backed Benchmark for WordPress Plugin Vulnerability Detection: Re-Evaluating Static and Learning-Based Detectors Under Leakage-Controlled Evaluation
inferred← citeshttps://doi.org/10.3390/computation13020030openalex-snapshot
From Vulnerability to Defense: The Role of Large Language Models in Enhancing Cybersecurity
inferred← citeshttps://doi.org/10.3390/computers14110501openalex-snapshot
AutoQALLMs: Automating Web Application Testing Using Large Language Models (LLMs) and Selenium
inferred← citeshttps://doi.org/10.3390/electronics14142763openalex-snapshot
A Review of Mobile Surveillanceware: Capabilities, Countermeasures, and Research Challenges
inferred← citeshttps://doi.org/10.3390/fi17050207openalex-snapshot
Classification of Hacker’s Posts Based on Zero-Shot, Few-Shot, and Fine-Tuned LLMs in Environments with Constrained Resources
inferred← citeshttps://doi.org/10.3390/info17080762openalex-snapshot
Attribution-Guided Prompt Optimization for Cross-CWE Vulnerability Detection
inferred← citeshttps://doi.org/10.3390/jcp6050163openalex-snapshot
Raw CVE/CWE Retrieval Does Not Improve LLM-Based Vulnerability Detection in Python: A Pre-Specified Null Result and a Retrieval-Dose Audit
inferred← citeshttps://doi.org/10.34218/ijaird_03_01_012openalex-snapshot
ENHANCING THE ROBUSTNESS AND GENERALIZABILITY OF COMPUTER VISION SYSTEMS USING EXPLAINABLE GENERATIVE MODELS (EGMS) FOR OUT-OF-DISTRIBUTION (OOD) DETECTION AND ADAPTIVE LEARNING
inferred← citeshttps://doi.org/10.54097/7ysr5k17openalex-snapshot
Large Language Models for Cybersecurity Intelligence, Threat Hunting, and Decision Support
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.