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Mobile-Agent: The Powerful Mobile Device Operation Assistant Family
[SIGIR 2024 perspective] The implementation of paper "On Generative Agents in Recommendation"
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
"EasyRec: Simple yet Effective Language Model for Recommendation"
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
AI Hospital: Interactive Evaluation and Collaboration of LLMs as Intern Doctors for Clinical Diagnosis
a state-of-the-art-level open visual language model | 多模态预训练模型
"GraphAgent: Agentic Graph Language Assistant"
[ACL 2024] AUTOACT: Automatic Agent Learning from Scratch for QA via Self-Planning
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Agentica: Effortlessly Build Intelligent, Reflective, and Collaborative Multimodal AI Agents! 轻松构建智能、具备反思能力、可协作的多模态AI Agent。
🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
[NeurIPS 2024] Agent Planning with World Knowledge Model
[ICLR 2024] Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
[NeurIPS 2024] Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
Official Repository of "GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration".
ICML 2024: Improving Factuality and Reasoning in Language Models through Multiagent Debate
Agent S: an open agentic framework that uses computers like a human
A simple, easy-to-hack GraphRAG implementation
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning (NeurIPS 2024)
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
The official Github repository for paper "R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation" (EMNLP 2024 Findings).
This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi.