LibertFan

LibertFan's Stars

• huggingface/lerobot

  🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning

  Language:Python7.6k82127729

• LargeWorldModel/LWM

  Large World Model -- Modeling Text and Video with Millions Context

  Language:Python7.2k6671552

• xlang-ai/OSWorld

  [NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

  Language:Python1.4k3151161

• THUDM/AgentTuning

  AgentTuning: Enabling Generalized Agent Abilities for LLMs

  Language:Python1.4k165396

• ShareGPT4Omni/ShareGPT4Video

  [NeurIPS 2024] An official implementation of ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

  Language:Python1.3k323944

• yaodongC/awesome-instruction-dataset

  A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)

  1.1k16859

• wilson1yan/VideoGPT

  Language:Jupyter Notebook9852239120

• robocasa/robocasa

  RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots

  Language:Python578119448

• LAION-AI/aesthetic-predictor

  A linear estimator on top of clip to predict the aesthetic quality of pictures

  Language:Jupyter Notebook49013720

• Vision-CAIR/ChatCaptioner

  Official Repository of ChatCaptioner

  Language:Jupyter Notebook4534828

• WooooDyy/AgentGym

  Code and implementations for the paper "AgentGym: Evolving Large Language Model-based Agents across Diverse Environments" by Zhiheng Xi et al.

  Language:Python35851446

• njucckevin/SeeClick

  The model, data and code for the visual GUI Agent SeeClick

  Language:HTML23024512

• allenai/WildBench

  Benchmarking LLMs with Challenging Tasks from Real Users

  Language:Python1984838

• victorsungo/MMDialog

  The official site of paper MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation

  Language:Python191447

• PKU-EPIC/DexGraspNet

  Language:Python18731923

• XiaoxiaoGuo/fashion-iq

  Language:Python14631739

• google-research/android_world

  AndroidWorld is an environment and benchmark for autonomous agents

  Language:Python1393913

• Yushi-Hu/VisualSketchpad

  Codes for Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models

  Language:Jupyter Notebook125887

• alipay/Ant-Multi-Modal-Framework

  Research Code for Multimodal-Cognition Team in Ant Group

  Language:Python1234205

• yjy0625/equibot

  Official implementation for paper "EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning".

  Language:Python1203016

• LibertFan/AI_Hospital

  AI Hospital: Interactive Evaluation and Collaboration of LLMs as Intern Doctors for Clinical Diagnosis

  Language:Python1181517

• OpenGVLab/MMT-Bench

  ICML'2024 | MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI

  Language:Python95573

• yiye3/GUICourse

  GUICourse: From General Vision Langauge Models to Versatile GUI Agents

  Language:Python84496

• princeton-nlp/CharXiv

  [NeurIPS 2024] CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

  Language:Python76388

• MILVLG/activitynet-qa

  An VideoQA dataset based on the videos from ActivityNet

  Language:Python67369

• prometheus-eval/prometheus-vision

  [ACL 2024 Findings & ICLR 2024 WS] An Evaluator VLM that is open-source, offers reproducible evaluation, and inexpensive to use. Specifically designed for fine-grained evaluation on customized score rubric, Prometheus-Vision is a good alternative for human evaluation and GPT-4V evaluation.

  Language:Python58146

• google-research-datasets/screen_annotation

  The Screen Annotation dataset consists of pairs of mobile screenshots and their annotations. The annotations are in text format, and describe the UI elements present on the screen: their type, location, OCR text and a short description. It has been introduced in the paper `ScreenAI: A Vision-Language Model for UI and Infographics Understanding`.

  48639

• KwanWaiChung/MT-Eval

  Code and data for "MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models"

  Language:Python30244

• chuyg1005/seeclick-crawler

  Language:Python12103

• SkyworkAI/agent-studio

  Environments, tools, and benchmarks for general computer agents

  Language:Python34813