mlsanityData to 14 Oct 2026

OmniSch: A Multimodal PCB Schematic Benchmark For Structured Diagram Visual Reasoning

arXiv 2604.00270 ↗First posted 31 Mar 2026cs.CVcited by 2

On the map: LLM reasoning → Multimodal reasoning

Abstract (arXiv)

Recent large multimodal models (LMMs) have made rapid progress in visual grounding, document understanding, and diagram reasoning tasks. However, their ability to convert Printed Circuit Board (PCB) schematic diagrams into machine-readable spatially weighted netlist graphs, jointly capturing component attributes, connectivity, and geometry, remains largely underexplored, despite such graph representations are the backbone of practical electronic design automation (EDA) workflows. To bridge this gap, we introduce OmniSch, the first comprehensive benchmark designed to assess LMMs on schematic understanding and spatial netlist graph construction. OmniSch contains 1,854 real-world schematic diagrams and includes four tasks: (1) visual grounding for schematic entities, with 109.9K grounded instances aligning 423.4K diagram semantic labels to their visual regions; (2) diagram-to-graph reasoning, understanding topological relationship among diagram elements; (3) geometric reasoning, constructing layout-dependent weights for each connection; and (4) tool-augmented agentic reasoning for visual search, invoking external tools to accomplish (1)-(3). Our results reveal substantial gaps of current LMMs in interpreting schematic engineering artifacts, including unreliable fine-grained grounding, brittle layout-to-graph parsing, inconsistent global connectivity reasoning and inefficient visual exploration.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 20 of its 35 references that are in the map. First posted on arXiv 31 Mar 2026.

Builds on

20 of 35 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning20 May
  2. 2023MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action20 Mar

Other references · 18

  1. 2023Visual Instruction Tuningcited by 7,869
  2. 2023Qwen Technical Reportcited by 3,344
  3. 2025Qwen3-VL Technical Reportcited by 2,793
  4. 2023Kosmos-2: Grounding Multimodal Large Language Models to the Worldcited by 1,089
  5. 2023Ferret: Refer and Ground Anything Anywhere at Any Granularitycited by 509
  6. 2024YOLO-World: Real-Time Open-Vocabulary Object Detectioncited by 503
  7. 2023V*: Guided Visual Search as a Core Mechanism in Multimodal LLMscited by 482
  8. 2023GLaMM: Pixel Grounding Large Multimodal Modelcited by 455
  9. 2025PaddleOCR 3.0 Technical Reportcited by 143
  10. 2024Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Modelscited by 119
  11. 2024AMSNet: Netlist Dataset for AMS Circuitscited by 25
  12. 2024Masala-CHAI: A Large-Scale SPICE Netlist Dataset for Analog Circuits by Harnessing AIcited by 18
6 more
  1. 2025AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detectioncited by 9
  2. 2025MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generationcited by 8
  3. 2025Image2Net: Datasets, Benchmark and Hybrid Framework to Convert Analog Circuit Diagrams into Netlistscited by 7
  4. 2026SINA: A Circuit Schematic Image-to-Netlist Generator Using Artificial Intelligencecited by 4
  5. 2021A Public Ground-Truth Dataset for Handwritten Circuit Diagram Imagescited by 3
  6. 2025RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarioscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025CircuitSense: A Hierarchical MLLM Benchmark Bridging Visual Comprehension and Symbolic Reasoning in Engineering Design Process
  2. 2026DiagramNet: An End-to-End Recognition Framework and Dataset for Non-Standard System-Level Diagrams
  3. 2025A Large Language Model Powered Integrated Circuit Footprint Geometry Understanding
  4. 2026Beyond Pixels: Vector-to-Graph Transformation for Reliable Schematic Auditing
  5. 2024VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context
  6. 2026CircuitReason-1k: Benchmarking Long-Horizon Visual-to-Symbolic Reasoning inElectrical Circuits
  7. 2026Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding
  8. 2026OmniMech: All-in-one Multimodal Mechanical Benchmark for 3D Reconstruction