llm-for-zotero
✨An AI research assistant plugin that deeply integrates LLMs into Zotero, featuring paper chat, multi-paper comparison, Agent Mode for automated literature management, and note export to Obsidian/Logseq.
An AI research assistant plugin that deeply integrates LLMs into Zotero, featuring paper chat, multi-paper comparison, Agent Mode for automated literature management, and note export to Obsidian/Logseq.
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 self-hostable AI research workspace for grounded chat, paper study, 206+ scientific skills, and 13-stage deep research execution.
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.
A systematic skill library for AI Agent context management, covering fundamentals, architectural patterns, operational optimization, and evaluation systems. Compatible with Claude Code, Cursor, and other platforms. Distinguished from prompt engineering by its holistic approach to curating all information entering the model's attention budget.
An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.
An open-source collection of tutorials and runnable scripts for over 30 advanced Retrieval-Augmented Generation (RAG) techniques, including Graph RAG, Agentic RAG, and various retrieval optimization strategies, implemented primarily with LangChain.
A comprehensive AI engineering hub featuring 93+ production-ready projects with in-depth tutorials and implementations for LLMs, RAGs, AI Agents, and MCP, covering beginner to advanced skill levels.
An AI-driven multi-agent research assistant based on LangGraph that automates the entire research workflow from hypothesis generation, data analysis, and visualization to comprehensive report writing.
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