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π Main Results β¨ Getting Started β’ π¨ Contact β’ π Citation β’ π Star History
The main features of tsinghuac3i/ssrl are: Search and Research Agents, Single Agent Optimization.
Projects with overlapping indexed features include: dzhng/deep-research β This project is an AI research tool designed for autonomous web information gathering and automated topic research. Itβ¦ arc53/docsgpt β DocsGPT is a retrieval-augmented generation platform and private knowledge base used to build AI agents that performβ¦ aq-medai/medresearcher-r1 β ο½π€ HuggingFace Model ο½ π arXiv ο½ π δΈζ ο½. chengpengli1003/cort. chengsong-huang/r-zero β Check out our paper or webpage for the details. allenai/open-instruct β Open-Instruct is a distributed training and instruction tuning framework for large language models. It functions as aβ¦
This project is an AI research tool designed for autonomous web information gathering and automated topic research. It utilizes agent orchestration to combine search engines and web scraping, enabling the system to discover detailed information and build a comprehensive understanding of complex subjects without manual step-by-step guidance. The tool employs an iterative research execution model that recursively generates targeted search queries and refines directions based on previous results. It includes a feedback loop that compares current findings against initial objectives to identify kn
DocsGPT is a retrieval-augmented generation platform and private knowledge base used to build AI agents that perform grounded search and analysis. It functions as a multi-model AI orchestrator and enterprise agent builder, allowing for the integration of various local and cloud language models to customize reasoning and text generation. The project provides a visual environment for developing automated assistants using conditional logic and third-party API connectivity. It enables the creation of private AI agents capable of performing enterprise search and detailed document analysis using pr
ο½π€ HuggingFace Model ο½ π arXiv ο½ π δΈζ ο½
Open-Instruct is a distributed training and instruction tuning framework for large language models. It functions as a coordinator for supervised fine-tuning, reinforcement learning from human feedback pipelines, and tool-use training, providing specialized roles for dataset curation and model alignment. The project distinguishes itself through a high-performance training architecture that utilizes actor-based distributed coordination and hybrid sharding to manage large GPU clusters. It implements advanced alignment techniques including direct preference optimization, group relative policy opt