[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81884-en":3,"doc-seo-81884-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":20,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},81884,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","Weave Verified Netlist-to-Schematic Conversion via Layered Graph Layout","Converting a SPICE netlist into a human-readable schematic is a central automation challenge, since simulators and ML pipelines produce netlists while engineers rely on diagrams to understand circuit structure and signal flow. Weave presents a deterministic SPICE netlist-to-LTspice .asc converter using layered (Sugiyama-style) graph layout and certified correctness via round-trip connectivity checking. Generated schematics are re-parsed into anetlists and compared net-for-net for identical partitions, yielding a binary certificate. Client-side execution avoids dependencies by embedding LTspice pin tables and achieving strong verified connectivity results.","Weave: Verified Netlist-to-Schematic Conversion  \nvia Layered Graph Layout  \nSenol Gulgonul  \nDepartment of Electrical and Electronics Engineering  \nOstim Technical University, Ankara, Turkey  \narXiv :2607 .03835v 1 [ cs .AR] 4 Jul 2026  \nAbstract—Converting a SPICE netlist into a human-readable schematic is a longstanding problem in electronic design automation: simulators and machine-learning pipelines readily produce netlists, but designers reason about circuits through diagrams. Recent learning-based approaches translate netlists into schematics probabilistically, yet they provide no guarantee that the generated drawing preserves the original connectivity, and their accuracy degrades sharply as circuits grow. We present Weave, a deterministic converter that turns a SPICE netlist into an LTspice .asc schematic using a layered (Sugiyama-style) graph layout, and that certifies every output by a round-trip connectivity check: the generated schematic is re-parsed into anetlist and compared, net for net, against the input. A result is reported as correct only when the two partitions are identical, giving a binary correctness certificate rather than a similarity score. Weave runs entirely client-side as a single dependency-free file and embeds a pin table for 5093 LTspice symbols. On the identical public Circuits-LTSpice test set used by the state-of-theart LLM converter Schemato (117 circuits, netlisted with LTspice itself), Weave achieves 100% compilation and 100% roundtrip-verified connectivity equivalence, compared with Schemato’s reported 76% compilation and a graph-edit-distance similarity of 0.35; notably, 73% of that set exceeds the five-component threshold beyond which Schemato reports losing connectivity accuracy. On a larger and harder corpus, the 3460 netlistable circuits of the official Analog Devices LTspice demo collection, Weave verifies exact connectivity for 88.4% of circuits, with the remaining failures concentrated in a single, well-characterized class of dense multi-pin power modules.  \nIndex Terms—Automatic schematic generation, netlist-toschematic, layered graph layout, LTspice, connectivity verification, electronic design automation.  \nI. INTRODUCTION  \nThe netlist is the lingua franca of circuit simulation, but it is not how engineers understand circuits. Designers rely on schematics to recognize structure, trace signal flow, and debug behavior [1] . As machine-learning methods increasingly generate circuits directly as netlists, the gap between machine-produced netlists and human-interpretable schematics has become a practical bottleneck: to bring domain experts into the loop, netlists must be turned back into readable diagrams quickly and accurately [2] .  \nAutomatic schematic generation (ASG) is a mature field. The recent review by Yang et al. [1] organizes ASG layout into two families: heuristic-based methods and, more recently, deep-reinforcement-learning-based methods. The heuristic line is classical and well understood. Swinkels and Hafer [3] framed schematic layout as an expert-system problem with horizontal and vertical ordering; Jehng et al. [4] introduced  \nthe ASG value-propagation layout; Arsintescu [5] placed symmetric pairs on a grid and minimized wire length and bends; Wu [6] and others advanced function-block placement along the signal-flow direction. Naveen and Raghunathan [7] built an early netlist-to-schematic generator with channel routing, and Frezza and Levitan [8] combined placement and routing in a single system. These methods are interpretable and fast, but, as the review notes, they typically settle for a good rather than an optimal arrangement [1] .  \nThe modern wave is learning-based. Hsu and Lin [9] generate analog schematics through building-block classification and reinforcement learning, optimizing an aesthetic reward. Most directly related to our work, Schemato [2] fine-tunes a large language model to translate netlists into LTspice .asc files, reporting up to 76% compila","cbCaihEzevaiqw5E","https://ap.wps.com/l/cbCaihEzevaiqw5E","pdf",221921,6,1,"English","en",105,"# Abstract\n# Introduction\n## Background and motivation\n## Prior work in automatic schematic generation\n## Learning-based approaches and limitations\n## Weave’s approach and contributions","[{\"question\":\"What problem does Weave address in electronic design automation?\",\"answer\":\"Weave targets the gap between SPICE netlists generated by tools/ML and the schematic diagrams engineers need for understanding, debugging, and tracing circuit behavior.\"},{\"question\":\"How does Weave guarantee that a generated schematic preserves connectivity?\",\"answer\":\"Weave performs round-trip verification: it parses the generated LTspice .asc schematic back into a netlist and compares connectivity net-for-net with the original, accepting only when partitions are identical.\"},{\"question\":\"How do Weave’s results compare with the LLM-based converter Schemato?\",\"answer\":\"On a public Circuits-LTSpice test set, Weave reports 100% compilation and 100% roundtrip-verified connectivity equivalence, while Schemato reports 76% compilation and lower connectivity accuracy as circuit size increases.\"}]","Weave Verified Netlist-to-Schematic Conversion via Layered Graph Layout | 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problem does Weave address in electronic design automation?","Question",{"text":76,"@type":77},"Weave targets the gap between SPICE netlists generated by tools/ML and the schematic diagrams engineers need for understanding, debugging, and tracing circuit behavior.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How does Weave guarantee that a generated schematic preserves connectivity?",{"text":81,"@type":77},"Weave performs round-trip verification: it parses the generated LTspice .asc schematic back into a netlist and compares connectivity net-for-net with the original, accepting only when partitions are identical.",{"name":83,"@type":74,"acceptedAnswer":84},"How do Weave’s results compare with the LLM-based converter Schemato?",{"text":85,"@type":77},"On a public Circuits-LTSpice test set, Weave reports 100% compilation and 100% roundtrip-verified connectivity equivalence, while Schemato reports 76% compilation and lower connectivity accuracy as circuit size 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