Topics / #vision-language-models

Vision-language-models projects on GitHub

Multimodal models trained jointly on images and text for captioning, QA, and grounding

As of , the most-starred Vision-language-models projects on GitHub are ParseBench (603 stars), Qwen-Drive-1.0 (515 stars) and Zero-WAM (434 stars). GitHub.Locker tracks 7 Vision-language-models repositories with 2.7K stars combined. The fastest-growing on October 17 was ParseBench, with +1 stars in a day.

7Projects
2.7KStars in total
+2Stars in a day
Browse in the catalog →github.com/topics/vision-language-models ↗

Hot right now

Most stars gained in a day · Oct 17

+1

ParseBench

run-llama/ParseBench · ★ 603

ParseBench is a benchmark that measures how well document parsing tools (OCR engines, VLMs, commercial parsing APIs) convert PDFs into structured output that AI agents can reliably act on, rather than just text that looks similar to the original.

+1

Code-as-World

MirroS-Lab/Code-as-World · ★ 420

Code-as-World is a research project that represents the physical world as executable code, discovered through an agentic loop of simulation and verification, so models get reusable physical data (states, dynamics, mechanisms) instead of just raw pixels.

The all-time top

7 projects · by stars

  1. #1 · run-llama/ParseBench

    ParseBench

    ParseBench is a benchmark that measures how well document parsing tools (OCR engines, VLMs, commercial parsing APIs) convert PDFs into structured output that AI agents can reliably act on, rather than just text that looks similar to the original.

    603
  2. #2 · QwenLM/Qwen-Drive-1.0

    Qwen-Drive-1.0

    Qwen-Drive-1.0 is a vision-language foundation model for autonomous driving, built on the Qwen3.5-4B VLM and extended with 3D perception, visual question answering, and motion planning in one unified model.

    515
  3. #3 · robbyant-research/Zero-WAM

    Zero-WAM

    Zero-WAM is a research method for zero-shot cross-task robotic manipulation: a causal video-action policy that learns in-context world-action modeling, predicting future robot observations and executable actions from either language instructions or human demonstration videos.

    434
  1. 4

    Code-as-World

    420MirroS-Lab/Code-as-World · Python

    Code-as-World is a research project that represents the physical world as executable code, discovered through an agentic loop of simulation and verification, so models get reusable physical data (states, dynamics, mechanisms) instead of just raw pixels.

  2. 5

    EvoVLM

    332zzzz7788990213-ops/EvoVLM · Python

    EvoVLM is a research project that runs LLM-guided, multi-objective evolutionary search over vision-language inference programs. It targets the accuracy-latency trade-off on scientific chart understanding while keeping model weights frozen.

  3. 6

    damo-radar

    207alibaba-damo-academy/damo-radar · Python

    RADAR is a generalist vision-language AI model for abdominal CT diagnosis, trained on over 400,000 contrast-enhanced abdominal CT exams with 15 million anatomy-aware image-text pairs derived directly from clinical reports.

  4. 7

    Embodied-AI-Start

    199ppsdk/Embodied-AI-Start

    A Chinese-language 'Embodied AI Starter Map' that organizes a learning path from robotics fundamentals (coordinates, kinematics, ROS 2) up to VLA policies, World Models, model-based RL and World Action Models (WAM), linking papers, code, benchmarks and practice guides at each step.

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