github aiming-lab/AutoResearchClaw v0.5.0
AutoResearchClaw v0.5.0

one month ago

AutoResearchClaw v0.5.0

Highlights

  • Multi-Domain Architecture: Expanded beyond ML to support HEP Physics, Biology, Quantum Computing, and Statistics domains with profile-driven deployment
  • ARC-Bench Evaluation Framework: Standardized benchmark suite with 50+ topics across 5 domains (ML01-ML25, P01-P10, Q01-Q10, B01-B07, S01-S03), rubric-based judging, and baseline adapters for AIDE, Agent Laboratory, and AI-Scientist-v2
  • ColliderAgent Integration: Full HEP physics simulation pipeline support (MadGraph → Pythia → Delphes) with incremental experiment mode and Stage-12 re-entry
  • Biology-Agent Integration: Metabolic modeling with COBRApy/Biopython skills, FBA simulation, and GSMM validation
  • Quantum-Qiskit Skill: Qiskit-based quantum computing experiment support for quantum topics
  • Statistics Domain Agent: Statistical method design, experiment evaluation, and theory analysis
  • Requirements Gate: LLM capability validation before pipeline execution
  • Profile-Driven Deployment: Interactive CLI for domain profile creation and management
  • Incremental Experiment Mode: Resume experiments at Stage-12 with delta-prompt assembly
  • Expanded Test Suite: New tests for HEP prompt hygiene, incremental experiments, and domain integrations

Breaking Changes

  • Topic IDs renamed: T01-T25 → ML01-ML25 in ARC-Bench
  • researchclaw/prompts.py refactored into researchclaw/prompts/ package (domain-aware prompt banks)

Documentation

  • Domain Integration Guide for adding new scientific domains
  • Tester guides in English, Chinese, and Japanese
  • ARC-Bench experiment design docs and run guides
  • Showcase papers demonstrating pipeline outputs

Full Changelog: v0.4.0...v0.5.0

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