RubiCap: Rubric-Guided Reinforcement Learning for Dense Image Captioning
cs.CV, cs.AI, cs.LG
Submitted: 2026-03-10
Updated: 2026-09-26
Terminology
Sources
- Microsoft COCO Captions: Data Collection and Evaluation Server
- Text-only Synthesis for Image Captioning
- From Pixels to Prose: A Large Dataset of Dense Image Captions
- SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
- Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
- RL's Razor: Why Online Reinforcement Learning Forgets Less
- Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data
- Kimi k1.5: Scaling Reinforcement Learning with LLMs
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- CapArena: Benchmarking and Analyzing Detailed Image Captioning in the LLM Era
- CaptionQA: Is Your Caption as Useful as the Image Itself?
- DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World
- VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
- Chart-RVR: Reinforcement Learning with Verifiable Rewards for Explainable Chart Reasoning
- Reinforced Visual Perception with Tools
- CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
- DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
- Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
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