Visual-ERM is a new multimodal reward model that supplies fine-grained visual feedback for training vision-language models on chart-to-code, table, and SVG tasks, yielding measurable gains over prior rewards.
Viscodex: Unified multimodal code generation via merging vision and coding models.arXiv preprint arXiv:2508.09945
4 Pith papers cite this work. Polarity classification is still indexing.
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A 7B/8B model trained with decoupled tri-perspective SFT and QA-verified RL matches GPT-4o and approaches GPT-5 on chart-to-code generation benchmarks.
Neural Change Prediction generates mutation data to train bidirectional models linking code changes to behavioral effects for any executable program.
A structured survey of multimodal code intelligence that formulates the field by code roles and organizes work into four domains while proposing verification-centered research directions.
citing papers explorer
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Visual-ERM: Reward Modeling for Visual Equivalence
Visual-ERM is a new multimodal reward model that supplies fine-grained visual feedback for training vision-language models on chart-to-code, table, and SVG tasks, yielding measurable gains over prior rewards.
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CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution
A 7B/8B model trained with decoupled tri-perspective SFT and QA-verified RL matches GPT-4o and approaches GPT-5 on chart-to-code generation benchmarks.
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Neural Change Prediction: Relating Software Changes to Their Effects and Vice Versa
Neural Change Prediction generates mutation data to train bidirectional models linking code changes to behavioral effects for any executable program.
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Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence
A structured survey of multimodal code intelligence that formulates the field by code roles and organizes work into four domains while proposing verification-centered research directions.