Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding
Paper recorded by Signals 4 on 2026-09-14 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15
Category: cs.CV · 计算机视觉 · first seen 2026-09-15
Abstract
Through pre-training on extensive text and image datasets, current multi-modal large language models (MLLMs) achieve strong performance on general tasks. However, circuit schematics present a unique challenge for MLLMs due to their dense component layouts and distinct topological logic, demanding fine-grained structural parsing to extract the electrical semantics. To address this, we propose Circu
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Cite this page: Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding: the #59 most recent of 237 cs.CV papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/circuit-mllm-topological-logic-guided-latent-space-visual-reasoning-for-circuit-.html
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