Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding

arXiv:2609.15668 · cs.CV, cs.AI, cs.LG · Submitted 2026-09-14 · Read on arXiv

cs.CV, cs.AI, cs.LG

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: Accepted at European Conference on Computer Vision (ECCV) 2026

Code: https://github.com/IC-Yuan/Circuit-MLLM

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Latent Space — 34× in this paper · explained in 7 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Latent Representation — 7× in this paper · explained in 2 episodes
• Latent Representations — 7× in this paper · explained in 3 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• Ablation study — 4× in this paper · explained in 1 episode
• Latent Visual Reasoning — 4× in this paper · explained in 2 episodes
• Multimodal Reasoning — 4× in this paper · explained in 5 episodes
• Chain of Thought — 3× in this paper
• Exact Match Ratio — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• GRPO — 3× in this paper · explained in 6 episodes
• Latent Reasoning — 3× in this paper · explained in 2 episodes
• Chain-of-Thought (CoT) — 2× in this paper · explained in 4 episodes
• Core — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Supervised Fine-Tuning — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Alignment Methods — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Guided attention — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• MLLMs in Electronic Design Automation — 1× in this paper
• Mean Squared Error — 1× in this paper
• RAG — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes
• Semantic Gap — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Topological Order — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Masala-CHAI: A Large-Scale SPICE Netlist Dataset for Analog Circuits by Harnessing AI
• PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model
• Interleaved Latent Visual Reasoning with Selective Perceptual Modeling
• AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
• Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
• Latent Visual Reasoning
• AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detection
• AMSbench: A Comprehensive Benchmark for Evaluating MLLM Capabilities in AMS Circuits
• SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning
• Machine Mental Imagery: Empower Multimodal Reasoning with Latent Visual Tokens
• Multimodal Chain-of-Thought Reasoning in Language Models
• MAPS: Advancing Multi-Modal Reasoning in Expert-Level Physical Science

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models