World Embedding Benchmark
cs.CV, cs.CL
Submitted: 2026-10-02
Updated: 2026-10-02
Code: https://github.com/World-Representation-Lab/World-Embedding-Benchmark
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- MAEB: Massive Audio Embedding Benchmark
- MVEB: Massive Video Embedding Benchmark
- V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
- PhysRAG: Enhancing Physics-Awareness in Video Generation via Retrieval-Augmented Generation
- E5-V: Universal Embeddings with Multimodal Large Language Models
- Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
- EvalCrafter: Benchmarking and Evaluating Large Video Generation Models
- CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics
- IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning
- Pixel Sentence Representation Learning
- RAR-b: Reasoning as Retrieval Benchmark
- Omni-Embed-Nemotron: A Unified Multimodal Retrieval Model for Text, Image, Audio, and Video
- On the Design Fundamentals of Pixel Text Representation Learning
- ReasonAudio: A Benchmark for Evaluating Reasoning Beyond Matching in Text-Audio Retrieval
- VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness
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