mlsanityData to 14 Oct 2026

FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning

arXiv 2512.12756 ↗First posted 14 Dec 2025cs.CVcited by 5

On the map: LLM reasoning → Audio-language model reasoning

also in 1 more
Abstract (arXiv)

Despite rapid progress in multimodal large language models (MLLMs) and emerging omni-modal architectures, current benchmarks remain limited in scope and integration, suffering from incomplete modality coverage, restricted interaction to text-centric outputs, and weak interdependence and complementarity among modalities. To bridge these gaps, we introduce FysicsWorld, the first unified full-modality benchmark that supports bidirectional input-output across image, video, audio, and text, enabling comprehensive any-to-any evaluation across understanding, generation, and reasoning. FysicsWorld encompasses 16 primary tasks and 3,268 curated samples, aggregated from over 40 high-quality sources and covering a rich set of open-domain categories with diverse question types. We also propose the Cross-Modal Complementarity Screening (CMCS) strategy integrated in a systematic data construction framework that produces omni-modal data for spoken interaction and fusion-dependent cross-modal reasoning. Through a comprehensive evaluation of over 30 state-of-the-art baselines, spanning MLLMs, modality-specific models, unified understanding-generation models, and omni-modal language models, FysicsWorld exposes the performance disparities and limitations across models in understanding, generation, and reasoning. Our benchmark establishes a unified foundation and strong baselines for evaluating and advancing next-generation full-modality architectures.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Audio-language model reasoning, one of 17 directions in LLM reasoning. Builds on 49 of its 82 references that are in the map. First posted on arXiv 14 Dec 2025.

Builds on

49 of 82 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs12 Oct
  2. 2025MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark5 Jun
  3. 2025Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities23 May
  4. 2025MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix19 May
  5. 2025Qwen2.5-Omni Technical Report26 Mar
  6. 2024MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark24 Oct

Other references · 43

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2025Qwen2.5-VL Technical Reportcited by 5,587
  3. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
  4. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,834
  5. 2025Gemma 3 Technical Reportcited by 1,824
  6. 2024HunyuanVideo: A Systematic Framework For Large Video Generative Modelscited by 1,660
  7. 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiencycited by 1,510
  8. 2024MiniCPM-V: A GPT-4V Level MLLM on Your Phonecited by 1,079
  9. 2025Qwen-Image Technical Reportcited by 1,044
  10. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 1,006
  11. 2023SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehensioncited by 940
  12. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 897
31 more
  1. 2025Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scalingcited by 812
  2. 2023Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Modelscited by 608
  3. 2024Qwen2-Audio Technical Reportcited by 560
  4. 2025Qwen3-Omni Technical Reportcited by 497
  5. 2024Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelscited by 477
  6. 2025GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Modelscited by 467
  7. 2025Step1X-Edit: A Practical Framework for General Image Editingcited by 429
  8. 2024Seed-TTS: A Family of High-Quality Versatile Speech Generation Modelscited by 300
  9. 2025Seedance 1.0: Exploring the Boundaries of Video Generation Modelscited by 259
  10. 2025OmniGen2: Towards Instruction-Aligned Multimodal Generationcited by 253
  11. 2025Show-o2: Improved Native Unified Multimodal Modelscited by 250
  12. 2025Seedream 4.0: Toward Next-generation Multimodal Image Generationcited by 249
  13. 2025WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generationcited by 204
  14. 2025VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interactioncited by 197
  15. 2025WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMscited by 155
  16. 2025HunyuanImage 3.0 Technical Reportcited by 149
  17. 2025Emu3.5: Native Multimodal Models are World Learnerscited by 132
  18. 2025Baichuan-Omni-1.5 Technical Reportcited by 111
  19. 2025Ovis2.5 Technical Reportcited by 108
  20. 2024OmniBench: Towards The Future of Universal Omni-Language Modelscited by 102
  21. 2025Ovis-U1 Technical Reportcited by 67
  22. 2025Ming-Omni: A Unified Multimodal Model for Perception and Generationcited by 66
  23. 2025BLIP3o-NEXT: Next Frontier of Native Image Generationcited by 54
  24. 2025SeedEdit 3.0: Fast and High-Quality Generative Image Editingcited by 53
  25. 2024AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information?cited by 47
  26. 2025Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecyclecited by 35
  27. 2025RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmarkcited by 33
  28. 2025Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Modelcited by 18
  29. 2025SAIL-Embedding Technical Report: Omni-modal Embedding Foundation Modelcited by 10
  30. 2025HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses through Reasoning MLLMscited by 9
  31. 2025Improving Multimodal Sentiment Analysis via Modality Optimization and Dynamic Primary Modality Selectioncited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

Similar, not cited

Close in wording, no citation either way

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  2. 2024OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities
  3. 2025OMHBench: Benchmarking Balanced and Grounded Omni-Modal Multi-Hop Reasoning
  4. 2026Evaluating Cross-Modal Reasoning Ability and Problem Characteristics with Multimodal Item Response Theory
  5. 2026Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model
  6. 2026MMOU: A Massive Multi-Task Omni Understanding and Reasoning Benchmark for Long and Complex Real-World Videos
  7. 2025Contra4: Evaluating Contrastive Cross-Modal Reasoning in Audio, Video, Image, and 3D
  8. 2026Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation