✨✨Latest Advances on Multimodal Large Language Models
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Updated
Dec 4, 2024
✨✨Latest Advances on Multimodal Large Language Models
Mobile-Agent: The Powerful Mobile Device Operation Assistant Family
ModelScope-Agent: An agent framework connecting models in ModelScope with the world
LLaMA-Omni is a low-latency and high-quality end-to-end speech interaction model built upon Llama-3.1-8B-Instruct, aiming to achieve speech capabilities at the GPT-4o level.
Cambrian-1 is a family of multimodal LLMs with a vision-centric design.
[ICML 2024] Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs (RPG)
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
✨✨VITA: Towards Open-Source Interactive Omni Multimodal LLM
LLaVA-Plus: Large Language and Vision Assistants that Plug and Learn to Use Skills
✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models. The first work to correct hallucinations in MLLMs.
Speech, Language, Audio, Music Processing with Large Language Model
A collection of resources on applications of multi-modal learning in medical imaging.
A novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings.
[CVPR 2024] MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
实时语音交互数字人,支持端到端语音方案(GLM-4-Voice - THG)和级联方案(ASR-LLM-TTS-THG)。可自定义形象与音色,无须训练,支持音色克隆,首包延迟低至3s。Real-time voice interactive digital human, supporting end-to-end voice solutions (GLM-4-Voice - THG) and cascaded solutions (ASR-LLM-TTS-THG). Customizable appearance and voice, supporting voice cloning, with initial package delay as low as 3s.
✨✨Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
MLCD & UNICOM : Large-Scale Visual Representation Model
NeurIPS 2024 Paper: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
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