AI RESEARCH
Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards
arXiv CS.LG
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ArXi:2603.06958v1 Announce Type: new Accurate chart comprehension represents a critical challenge in advancing multimodal learning systems, as extensive information is compressed into structured visual representations. However, existing vision-language models (VLMs) frequently struggle to generalize on unseen charts because it requires abstract, symbolic, and quantitative reasoning over structured visual representations. In this work, we