MVVBench: Benchmarking 4D Reasoning in Vision-Language Models

arXiv:2609.30952 · cs.CV, cs.AI · Submitted 2026-09-25 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Benchmark — 43× in this paper · explained in 2 episodes
• Verifier — 12× in this paper · explained in 2 episodes
• Temporal Reasoning — 9× in this paper · explained in 2 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Verification — 8× in this paper · explained in 2 episodes
• Grounding — 7× in this paper · explained in 3 episodes
• Benchmarking — 5× in this paper · explained in 3 episodes
• Multi-hop Reasoning — 5× in this paper · explained in 3 episodes
• Reinforcement Learning — 5× in this paper · explained in 4 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Tool-Augmented Dynamic Scene Graph — 4× in this paper
• Chain-of-Thought Prompting — 3× in this paper · explained in 2 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Scaffolding — 3× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Structured Reasoning — 2× in this paper · explained in 3 episodes
• Verifiable Rewards — 2× in this paper · explained in 2 episodes
• Causal Reasoning — 1× in this paper · explained in 2 episodes
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Chain-of-Thought (CoT) Prompting — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
• TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models
• SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
• PaLI: A Jointly-Scaled Multilingual Language-Image Model
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
• GPT-4o System Card
• Towards Comprehensive Scene Understanding: Integrating First and Third-Person Views for LVLMs
• LLaVA-OneVision: Easy Visual Task Transfer
• LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
• MINERVA: Evaluating Complex Video Reasoning
• SpaRE: Enhancing Spatial Reasoning in Vision-Language Models with Synthetic Data
• 3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans
• GraphEQA: Using 3D Semantic Scene Graphs for Real-time Embodied Question Answering
• Gemma 3 Technical Report
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• Cambrian-S: Towards Spatial Supersensing in Video
• MiniCPM-V: A GPT-4V Level MLLM on Your Phone
• Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs

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