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Gaotianhong
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Open-source evaluation toolkit of large vision-language models (LVLMs), support 160+ VLMs, 50+ benchmarks
High-quality datasets, tools, and concepts for LLM fine-tuning.
An Open Large Reasoning Model for Real-World Solutions
Official implementation of OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
A modular graph-based Retrieval-Augmented Generation (RAG) system
🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
✨✨Latest Advances on Multimodal Large Language Models
Repo for Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent
[NeurIPS 2024 Oral][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-sim…
HunyuanVideo: A Systematic Framework For Large Video Generation Model
A Self-Training Framework for Vision-Language Reasoning
ACL 2024: LoRA-Flow Dynamic LoRA Fusion for Large Language Models in Generative Tasks
WWW2025 Multimodal Intent Recognition for Dialogue Systems Challenge
A novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings.
精选机器学习，NLP，图像识别， 深度学习等人工智能领域学习资料，搜索，推荐，广告系统架构及算法技术资料整理。算法大牛笔记汇总
致力于实习/校招/社招进大厂打法，计算机基础知识学习，C++、Java、算法学习路线，专注于编程打法！
[NeurIPS 24 Spotlight] MaskLLM: Learnable Semi-structured Sparsity for Large Language Models
MICCAI 2024 - Loose Lesion Location Self-supervision Enhanced Colorectal Cancer Diagnosis
GPT4V-level open-source multi-modal model based on Llama3-8B
MiniCPM3-4B: An edge-side LLM that surpasses GPT-3.5-Turbo.
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路
整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。
Qodo-Cover: An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement! 💻🤖🧪🐞