mlsanityData to 14 Oct 2026

LinePilot Digitizer: Line-Plot Recovery with Manual and Automatic Calibration

arXiv 2609.19377 ↗First posted 16 Sep 2026cs.CV cs.AIcited by 0

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Abstract (arXiv)

Recovering numerical series from line plots requires accurate axis calibration and reliable curve extraction. We present LinePilot Digitizer (LinePilot), which combines continuous color-based curve recovery with three calibration modes: LinePilot (standard), LinePilot (enhanced), and LinePilot (OCR). We also introduce DigitizerBench, the first dedicated benchmark for systematically evaluating digitizer performance, using an orthogonal design spanning signal, rendering, and plot-structure factors with complementary automatic and human-guided evaluations. We evaluate performance using failure-penalized capped normalized root-mean-square error (FPC-NRMSE), which assigns unit loss to missing, unusable, or catastrophically inaccurate outputs. On DigitizerBench-Full, LinePilot (OCR) achieves the lowest mean FPC-NRMSE (0.672) and highest trusted usability (38.2%) among the tested automatic pipelines. On DigitizerBench-Lite, LinePilot (enhanced) achieves the lowest mean FPC-NRMSE (0.081), 100% output success, and highest trusted usability (93.3%). The orthogonal benchmark design further enables factor analysis to identify the factors that most significantly affect digitizer performance. Together, the three calibration modes provide a practical trade-off between automation, user control, and accuracy within a shared curve-recovery workflow.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 17 references that are in the map. First posted on arXiv 16 Sep 2026.

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4 of 17 references.

References · 4

  1. 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,479
  2. 2019PlotQA: Reasoning over Scientific Plotscited by 321
  3. 2021Plot2Spectra: an Automatic Spectra Extraction Toolcited by 5
  4. 2026IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Reviewcited by 2

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