Neural search engine for discovering semantically similar Python repositories on GitHub
EVIL (Exploiting software VIa natural Language) is an approach to automatically generate software exploits in assembly/Python language from descriptions in natural language. The approach leverages Neural Machine Translation (NMT) techniques and a dataset that we developed for this work.
Repository about small code models
Augmenting the Interpretability of GraphCodeBERT for Code Similarity Tasks
This repository contains the code, the dataset and the experimental results related to the paper "Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks" accepted for publication at The 32nd IEEE/ACM International Conference on Program Comprehension (ICPC 2024).
Improving Source Code Similarity Detection with GraphCodeBERT and Additional Feature Integration
Fine-tuning CodeBERT for Vulnerability Detection
CodeOpt: A framework for optimizing code performance using Two-Stage Sampling, Few-Shot Learning, and Iterative Self-Reflection with support for Genetic Algorithm Inspired Chain-of-Thought (GA-COT).
Django implementation of CodeBERT for detecting vulnerable code.
The modern web development landscape is plagued by a peculiar paradox: despite the abundance of UI components and design systems, developers still spend countless hours reimplementing similar interfaces. S0 addresses this challenge by introducing a novel approach that combines advanced vector search capabilities.
A deterministic and neuro-symbolic framework for evaluating LLM-generated code using Abstract Syntax Trees, Semantic Embeddings, and Integrated Gradients. Think of it as a 'Digital Polygraph' for AI. It uses a three-step verification process to ensure the AI didn't 'misunderstand' your instructions
🤖 Generate tailored AI training datasets quickly and easily, transforming your domain knowledge into essential training data for model fine-tuning.
Implementation and dataset for A Zero-Shot Framework for Cross-Project Vulnerability Detection in Source Code (Empirical Software Engineering, 2026).
AI/ML Trained Python Code Validator with Gradio Web Interface
Multi-model vulnerability detection for C code using CodeBERT, GraphCodeBERT, and CodeT5. Trained on Microsoft’s Devign dataset, VulnAI identifies both keyword-based and structural vulnerabilities with a Python API and CLI.
Reproducibility report ofCoSQA: 20,000+ Web Queries for Code Search and QuestionAnswering for ML Reproducibility Challenge 2021
🛠️ Generate AI training datasets easily, transforming complex information from documents into structured data for model fine-tuning.
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