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AI Ecosystem Intelligence Explorer

Code Generation

21 of 73 articles

GitHub - openai/codex-universal: Base docker image used in Codex environments

Base docker image used in Codex environments. Contribute to openai/codex-universal development by creating an account on GitHub.

Applied AI
Code Generation
 
5/19/2025

Type-Constrained Code Generation with Language Models

Large language models (LLMs) have achieved notable success in code generation. However, they still frequently produce uncompilable output because their next-token inference procedure does not model formal aspects of code. Although constrained decoding is a promising approach to alleviate this issue, it has only been applied to handle either domain-specific languages or syntactic features of general-purpose programming languages. However, LLMs frequently generate code with typing errors, which are beyond the domain of syntax and generally hard to adequately constrain. To address this challenge, we introduce a type-constrained decoding approach that leverages type systems to guide code generation. For this purpose, we develop novel prefix automata and a search over inhabitable types, forming a sound approach to enforce well-typedness on LLM-generated code. We formalize our approach on a foundational simply-typed language and extend it to TypeScript to demonstrate practicality. Our evaluation on the HumanEval and MBPP datasets shows that our approach reduces compilation errors by more than half and significantly increases functional correctness in code synthesis, translation, and repair tasks across LLMs of various sizes and model families, including state-of-the-art open-weight models with more than 30B parameters. The results demonstrate the generality and effectiveness of our approach in constraining LLM code generation with formal rules of type systems.

Code Generation
 
5/14/2025

GitHub - voideditor/void

Contribute to voideditor/void development by creating an account on GitHub.

Applied AI
Code Generation
 
5/10/2025

A Critical Look at MCP - Raz Blog

“MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.”

Code Generation
 
5/10/2025

The Cursor Mirage

Why One of the Most Hyped AI Coding Tools is a Minefield for Real Engineering Teams

Code Generation
 
4/26/2025

GitHub - x1xhlol/system-prompts-and-models-of-ai-tools: FULL v0, Cursor, Manus, Same.dev, Lovable, Devin & Replit Agent System Prompts, Tools & AI Models.

FULL v0, Cursor, Manus, Same.dev, Lovable, Devin & Replit Agent System Prompts, Tools & AI Models. - x1xhlol/system-prompts-and-models-of-ai-tools

Code Generation
 
4/19/2025

AI Will Not Replace Software Engineers (and May, in Fact, Require More)

Gartner Information Technology Research on AI Will Not Replace Software Engineers (and May, in Fact, Require More)

Work and Labor
Code Generation
 
4/9/2025

Vibe Coded AI App Generates Recipes for Cyanide Ice Cream and Cum Soup

A Y Combinator partner proudly launched an AI recipe app that told people how to make “Actual Cocaine” and a “Uranium Bomb.”

Harm and Risk
Code Generation
 
4/3/2025

MCP Security Notification: Tool Poisoning Attacks

We have discovered a critical vulnerability in the Model Context Protocol (MCP) that allows for

Cybersecurity
Code Generation
 
4/2/2025
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