GAIR-NLP/ASI-Arch

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1183 stars · 218 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A multi-agent framework that lets an LLM autonomously conduct end-to-end research on neural network architecture discovery, specifically linear attention mechanisms. It includes a discovery pipeline, MongoDB-based architecture database, and cognition base, and ships 106 discovered state-of-the-art linear attention architectures.

Use cases

• automate neural architecture discovery with LLM agents
• search for novel linear attention mechanisms
• run autonomous AI-driven scientific research pipelines
• store and retrieve experiment history for architecture search
• explore a gallery of discovered attention architectures

When to choose

• you want an autonomous multi-agent system for architecture research
• you need a starting set of state-of-the-art linear attention designs
• you want to reproduce or extend LLM-driven scientific discovery experiments

When to avoid

• you need a production-ready attention implementation library
• you lack GPU resources for large-scale empirical validation
• you want a simple hyperparameter search tool rather than architecture discovery

Facets

framework · maturity active

agent-framework llm-inference machine-learning database workflow-automation artificial-intelligence large-language-models deep-learning python autonomous-research linear-attention multi-agent scientific-discovery architecture-search ai-agents research docker linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="GAIR-NLP/ASI-Arch")