I am not a robot — a captcha solver for macOS: local model, Gemini vision, a stealth browser for checkbox captchas, RuCaptcha as the last resort. 2Captcha-compatible API and an MCP server.
A 4B grounding foundation model for physical intelligence. Unifies detection, referring, pointing, OCR, GUI, and layout grounding, achieving SOTA overall across 34 benchmarks and improving robot generalization and data efficiency in controlled evaluations.
OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and Understanding
X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, point cloud and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.
Scene-Designer: Learning Design Intelligence for Agentic 3D Scene Generation
👀 Train a 65M-parameter VLM from scratch in just 2h!
为纯文本模型"看图“设计更好的视觉工具箱和技能,支持多图理解,图片问答,前端UI还原、GUI 自动化等,并可选无缝接入多个主流agent,直接识别粘贴图片| A vision toolkit and skill designed for text-only llms — image Q&A, long-screenshot OCR, frontend UI restoration, and GUI automation, with optional seamless integration for Codex, Claude Code, Pi, Oh My Pi, and OpenCode
Aesthetic code generation with decoupled cross-modal rewards: turning prompts into editable, verifiable HTML/CSS infographics, with image generators as aesthetic guidance.
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
The Swiss Army Knife of Offline AI. Chat, see, speak, and generate images on your phone or Mac — GGUF LLMs, vision, Whisper speech-to-text, Stable Diffusion, tool calling, and local-network servers. Runs on your CPU, GPU, or NPU. No account, no API key, zero data leaves your device.
High-performance OpenAI and Anthropic compatible LLM inference server for Apple Silicon. Native MLX, continuous batching, multimodal models, MCP tool calling, and Claude Code support.
[dsh]为纯文本模型设计更强大的视觉工具箱:一行安装使用、粘贴图片直接识别、多张图片问答、截图到前端UI 还原等|DeepSeek Harness-native integration for agent-vision-toolkit: image Q&A, long-screenshot OCR, UI restoration, grounding, pixel diff, Artifacts, and Web UI.
[ICLR 2026] ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving
🌐 Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future
Code as World: Agentic Discovery of Executable World Representations for Physical Reasoning
[NeurIPS 2026] Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
A 4B diffusion grounding model for fast, precise visual evidence extraction. Unifies diverse grounding tasks through parallel decoding, with optional self-speculative decoding delivering 4.51x autoregressive throughput on COCO.
Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success but 65% Fewer Tokens
🚀🚀 A 0.8B JEV-like multimodal model playing GUI games directly from raw pixels.
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
One-for-All Multimodal Evaluation Toolkit Across Text, Image, Video, and Audio Tasks
Collection of AWESOME vision-language models for vision tasks
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
A curated list of awesome LLM/VLM/VLA/World Model for Autonomous Driving(LLM4AD) resources (continually updated)
Get clean data from tricky documents, powered by vision-language models ⚡
Resources and paper list for "Thinking with Images for LVLMs". This repository accompanies our survey on how LVLMs can leverage visual information for complex reasoning, planning, and generation.
日本語LLMまとめ - Overview of Japanese LLMs
Fully Open Framework for Democratized Multimodal Training
Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey
An open-weight 11B model series for long-form and real-time video understanding
[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
A most Frontend Collection and survey of vision-language model papers, and models GitHub repository. Continuous updates.
Turn documents into AI-ready Markdown with visual understanding
Bilingual (中文+EN) ML / LLM / diffusion / agent interview cheat sheets for AI 秋招 — generated by ARIS /interview-cheatsheet, rendered by /render-html into single-file HTML, reads anywhere — plus a CV→DBLP-fact-checked academic homepage generator and hand-authored long-form blogs 🌱
ParseBench - A Document Parsing Benchmark for AI Agents
😎 up-to-date & curated list of awesome Attacks on Large-Vision-Language-Models papers, methods & resources.
🚀🚀 A multimodal System One decision model that gives calibrated answers to typed questions about screens, photos, video and text in one forward pass.
S-Space: Exploring Spatial Workspace in Multimodal Models
🎬 OraRL — Annotations as Rollouts for efficient, scalable reinforcement learning of unified video MLLMs.
Open-source financial multimodal LLM for document understanding, chart/table reasoning, numerical reasoning, and financial analysis, with SFT, dual-branch RL, MOPD distillation, and public benchmark evaluation.
Evaluate visual models on your own images, JSON Schema, and production constraints with LangGraph, Pareto analysis, and a no-key Replay demo.
An open-source, efficient System I decision model for autonomous driving.
Learning Spatial Reasoning through Interaction with the Observable Physical World
A measurement-first lab for low-latency local camera inference with Glance.
A token-efficient, provider-agnostic vision layer for reasoning models via MCP.
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ds-vision-skill-plus:是基于ds-vision-skill的升级版,主要功能是给deepseek类似的纯文本推理模型提供可随着大语言模型发展而迭代提升的高效、可复用的计算机视觉能力和计算机生图能力
Ask an open vision-language model typed questions about an image and get probabilities back, on your own machine.
Unified reproductions, benchmarking & evaluation for perception-aware RLVR and OPD in VLMs. 19 methods · 30+ benchmarks · Official code of CGPO (ACM MM 2026 Oral).