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.
Chartcoder: Advancing multimodal large language model for chart-to-code generation
7 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.
IVG combines spec-grounded introspection and view-grounded interaction to let VLMs achieve 0.81 QA accuracy on interactive charts, with gains on overlapping elements, using a new benchmark of 500 Plotly figures.
SciTikZer-8B uses a new dataset, benchmark, and dual self-consistency RL to generate TikZ code for scientific graphics, outperforming much larger models like Gemini-2.5-Pro.
ChartVerse uses Rollout Posterior Entropy and truth-anchored inverse QA synthesis to produce 640K high-quality chart reasoning samples, training an 8B model that surpasses its 30B teacher.
PairCoder is a two-agent pair-programming method that leverages toolchain verification oracles to improve LLM generation of verifiable structured artifacts on 17 benchmarks across seven models.
chart-plot is an agentic harness using style-aware code generation from venue figures, a LaTeX-aware render-and-revise loop, and structured edit handles to produce top-venue-ready academic charts.
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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Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
IVG combines spec-grounded introspection and view-grounded interaction to let VLMs achieve 0.81 QA accuracy on interactive charts, with gains on overlapping elements, using a new benchmark of 500 Plotly figures.
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Scientific Graphics Program Synthesis via Dual Self-Consistency Reinforcement Learning
SciTikZer-8B uses a new dataset, benchmark, and dual self-consistency RL to generate TikZ code for scientific graphics, outperforming much larger models like Gemini-2.5-Pro.
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ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch
ChartVerse uses Rollout Posterior Entropy and truth-anchored inverse QA synthesis to produce 640K high-quality chart reasoning samples, training an 8B model that surpasses its 30B teacher.
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PairCoder++: Pair Programming as a Universal Paradigm for Verified Code-Driven Multimodal and Structured-Artifact Generation
PairCoder is a two-agent pair-programming method that leverages toolchain verification oracles to improve LLM generation of verifiable structured artifacts on 17 benchmarks across seven models.
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Demonstrating chart-plot: Closing the Last Mile of Academic Chart Generation
chart-plot is an agentic harness using style-aware code generation from venue figures, a LaTeX-aware render-and-revise loop, and structured edit handles to produce top-venue-ready academic charts.