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✨✨Latest Advances on Multimodal Large Language Models
Mobile-Agent: The Powerful Mobile Device Operation Assistant Family
StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.
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.
✨✨VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
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)
A family of lightweight multimodal models.
A novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings.
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.
Speech, Language, Audio, Music Processing with Large Language Model
LLaVA-Plus: Large Language and Vision Assistants that Plug and Learn to Use Skills
A collection of resources on applications of multi-modal learning in medical imaging.
Large-Scale Visual Representation Model
✨✨Woodpecker: Hallucination Correction for Multimodal Large Language Models
[CVPR 2024] MovieChat: From Dense Token to Sparse Memory for Long Video Understanding
NeurIPS 2024 Paper: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing
✨✨[CVPR 2025] Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis