FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning
On the map: LLM reasoning → Audio-language model reasoning
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
- 2025OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs12 Oct
- 2025MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark5 Jun
- 2025Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities23 May
- 2025MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix19 May
- 2025Qwen2.5-Omni Technical Report26 Mar
- 2024MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark24 Oct
Other references · 43
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Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026OmniFysics: Towards Physical Intelligence Evolution via Omni-Modal Signal Processing and Network Optimizationcited by 5
- 2026Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Modelscited by 5
- 2026C3PO: Evaluating Cross-Modal Composition and Counterfactual Performance in Omnimodal Modelscited by 2
- 2026SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generationcited by 2
- 2026OmniFysics-Nano-V2 Technical Report: Understanding the Physical World Across Modalitiescited by 0
- 2026OmniFysics-Nano-V2 Technical Report: Understanding the Physical World Across Modalities22 Sep 2026
- 2026SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generation1 Sep 2026
- 2026C3PO: Evaluating Cross-Modal Composition and Counterfactual Performance in Omnimodal Models5 Aug 2026
- 2026Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models27 Apr 2026
- 2026OmniFysics: Towards Physical Intelligence Evolution via Omni-Modal Signal Processing and Network Optimization5 Feb 2026
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