Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning
cs.CV
Submitted: 2026-05-25
Updated: 2026-10-13
Terminology
Sources
- Qwen3-VL Technical Report
- Qwen2.5-VL Technical Report
- UniVG-R1: Reasoning Guided Universal Visual Grounding with Reinforcement Learning
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- LLaVA-OneVision: Easy Visual Task Transfer
- LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models
- Imagination Helps Visual Reasoning, But Not Yet in Latent Space
- Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models
- VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Kimi-VL Technical Report
- Learning to Reason under Off-Policy Guidance
- R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization
- DAPO: An Open-Source LLM Reinforcement Learning System at Scale
- SPARK: Multi-Vision Sensor Perception and Reasoning Benchmark for Large-scale Vision-Language Models
- ExGRPO: Learning to Reason from Experience
- R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning
- Group Sequence Policy Optimization
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