arXiv AI
CircuTutor: Transforming Static Circuit Problems into Intelligent and Dynamic Tutoring
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
arXiv AI
Aug 11
CircuitReason-1k: Benchmarking Long-Horizon Visual-to-Symbolic Reasoning inElectrical Circuits
arXiv:2608. 09374v1 Announce Type: new Abstract: Electrical circuit analysis requires more than recognizing components in an image.
arXiv AI
Sep 15
Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving
The paper introduces an enhanced end‑to‑end circuit analysis framework built on Gemini 2.5 Pro, targeting engineering education. It addresses two key failure modes—circuit‑recognition hallucinations and reasoning‑process hallucinations—by adding a YOLO detector for source polarity re‑identification and an ngspice verification loop for iterative refinement. The resulting pipeline achieves 97.59 % accuracy on 83 undergraduate problems, markedly outperforming the baseline Gemini model and demonstrating significant gains across varied diagram styles and textbooks.
arXiv Machine Learning
Oct 22
Sketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis
The paper introduces Sketch2Sim, an end‑to‑end modular framework that transforms hand‑drawn circuit diagrams into SPICE‑compatible netlists and automatically computes nodal voltages and currents. It employs a three‑stage pipeline: dual YOLO detectors for components and text, a CRNN‑CTC OCR module for symbol value extraction, and image‑processing techniques (thresholding, skeletonization, DBSCAN) to identify nodes and map components. Experiments on a curated dataset of 1,000 RLC circuits show robust performance across diverse handwriting styles, lighting, and clutter, and the system includes a user interface for rapid digitization and simulation.
arXiv AI
Oct 27
Making Reasoning Visible: Configuration-Aware Diagnostic Modeling for Adaptive Scaffolding in Structured Reasoning Tasks
arXiv:2610.35609v1 Announce Type: cross Abstract: Modeling the latent, multi-step reasoning processes of learners is a core challenge for adaptive tutoring systems, which often rely on simple right/w...
arXiv AI
Aug 10
Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education
arXiv:2608. 07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Generative AI with LaTeX and Python to automate the creation of reproducible, visually consistent, and technically precise materials for STEM education.
arXiv Machine Learning
Jul 3
A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA
arXiv:2504. 03711v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI)-driven electronic design automation (EDA) techniques have been extensively explored for VLSI circuit design applications.