VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning

arXiv:2608.26105 · cs.CV, cs.AI, cs.LG, cs.MM, cs.RO · Submitted 2026-08-26 · Read on arXiv

cs.CV, cs.AI, cs.LG, cs.MM, cs.RO

Submitted: 2026-08-26

Updated: 2026-09-10

Comments: Homepage: https://video-reason.com/

Project page: https://video-reason.com

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 34× in this paper · explained in 2 episodes
• Reinforcement Learning — 22× in this paper · explained in 4 episodes
• Transformer — 12× in this paper · explained in 2 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Verifiable Rewards — 10× in this paper · explained in 2 episodes
• Fine-Tuning — 8× in this paper · explained in 5 episodes
• Generative Model — 8× in this paper · explained in 2 episodes
• Generative Models — 8× in this paper · explained in 3 episodes
• Diffusion Model — 7× in this paper · explained in 8 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Diffusion Models — 6× in this paper · explained in 6 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Transferability — 6× in this paper · explained in 4 episodes
• Benchmarking — 5× in this paper · explained in 4 episodes
• Failure Modes — 5× in this paper · explained in 3 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Abstraction — 4× in this paper · explained in 1 episode
• GRPO — 4× in this paper · explained in 6 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• KL Regularization — 3× in this paper · explained in 2 episodes
• Multimodal Reasoning — 3× in this paper · explained in 5 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Supervised Fine-Tuning — 3× in this paper
• Supervised Fine-Tuning (SFT) — 3× in this paper · explained in 8 episodes
• Coefficients-Preserving Sampling — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Reinforcement Learning with Verifiable Rewards — 2× in this paper
• Reward Function — 2× in this paper · explained in 2 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Alternation — 1× in this paper · explained in 1 episode
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Latent Visual Reasoning — 1× in this paper · explained in 2 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO
• BabyVision: Visual Reasoning Beyond Language
• OpenCoF: Learning to Reason Through Video Generation
• RealDPO: Real or Not Real, that is the Preference
• EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models
• Emerging Properties in Unified Multimodal Pretraining
• SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
• ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning
• LTX-2: Efficient Joint Audio-Visual Foundation Model
• RULER-Bench: Probing Rule-based Reasoning Abilities of Next-level Video Generation Models for Vision Foundation Intelligence
• VGI-Bench: Probing Visual Intelligence in Video Generation Models
• DiffThinker: Towards Generative Multimodal Reasoning with Diffusion Models
• GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
• Liger Kernel: Efficient Triton Kernels for LLM Training
• Bridging Interleaved Multi-Modal Reasoning as a Unified Decision Process
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes
• Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
• Imagine while Reasoning in Space: Multimodal Visualization-of-Thought
• UniGRPO: Unified Policy Optimization for Reasoning-Driven Visual Generation

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