EvoScientist
✨A self-evolving multi-agent AI scientist framework for end-to-end scientific discovery, from idea generation to paper publication.
A self-evolving multi-agent AI scientist framework for end-to-end scientific discovery, from idea generation to paper publication.
A Python library providing key functional primitives for research in multimodal language models, agentic AI, and knowledge graphs, featuring unified model invocation, multi-agent collaboration and debate, knowledge graph lifecycle management, and multimodal generation.
Transparent live-first benchmark harness for evaluating LLM Agent capability inside the OpenClaw runtime, with deterministic scoring and multi-dimensional assessment.
A flexible, efficient, and production-ready post-training reinforcement learning framework for LLMs
A benchmark measuring whether AI models challenge nonsensical prompts rather than confidently answering them, featuring 100 questions across 5 domains with a 3-tier judgment system and multi-judge panel.
A zero-dependency, Markdown-native autonomous ML research workflow system covering the full research lifecycle from idea discovery to rebuttal via cross-model adversarial collaboration.
An AI Agent-driven automated experiment framework that points at any code repo, autonomously analyzes, designs, runs experiments, and keeps improvements that work
A local-first AI research assistant featuring multi-LLM support, 20+ research strategies, multi-search-engine integration, and automated quality scoring for 212K+ academic sources, producing citation-backed PDF/Markdown reports via CLI, Web UI, REST API, or MCP Server.
An all-in-one AI ecosystem browser in the terminal — explore models, benchmarks, coding agents, and provider status via TUI/CLI
An AI agent-driven multi-platform aggregated search engine for the last 30 days, ranked by social engagement signals across 15+ sources including Reddit, X, YouTube, HN, and Polymarket.
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