{"as_of":"2026-08-20T21:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8e44392b7d8bc20549c2cf3cb2c89022f31df5c125f07b8487c1584edc452df3","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T16:43:54.123138Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2411.15212/citation-record","integrity":"/paper/2411.15212/integrity","json":"/paper/2411.15212/citation-record.json","paper":"/paper/2411.15212"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.904934Z","title":"A review on vlsi floor- planning optimization using metaheuristic algorithms,","venue":null,"work_id":"369f8b0d-0fe5-4b26-8f60-eefa16810483","year":2016},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.002894Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:9899b53b6249795c22d375260b4ae8f6ad21ab970253718fe91d633e736b98e3","observation_id":"7a810a16-82ce-4e26-add6-77513fb973fc","resolution":{"observed_at":"2026-08-12T16:43:54.909067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.007656Z","title":"A customized graph neural network model for guiding analog IC placement,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.007656Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:a564bb361ad5188194ecf43cd7b2921131932d70f6563fa2a650b763b3e5ace9","observation_id":"ed959a94-ad6a-46dc-a956-de9432b7ea7e","resolution":{"observed_at":"2026-08-12T16:43:54.007656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.011464Z","title":"Reinforcement learning for combinatorial optimization: A survey,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.011464Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:bdbc49a06c1236c60bab905b73b2235189b427e9006fe07d4fd62a776f6bfa50","observation_id":"1251ac55-f257-4b06-8798-dbc127536fc6","resolution":{"observed_at":"2026-08-12T16:43:54.011464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.885102Z","title":"Maskplace: Fast chip placement via rein- forced visual representation learning,","venue":null,"work_id":"08b228db-db14-47ec-92d4-43a19e8a2dee","year":2022},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.015866Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:3f2e9b0dbe8aed415bc263f43b90d4fec81546fff61ff943c1ea2ba9a09c6a7b","observation_id":"9c2ce585-f4d7-470f-a2dc-9bd8325cee52","resolution":{"observed_at":"2026-08-12T16:43:54.889516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.873388Z","title":"On joint learning for solving placement and routing in chip design,","venue":null,"work_id":"1aaec3c7-07df-48eb-a8fd-3f5df7ece071","year":2024},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.020452Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:15466c0aae33bd707bbc5ea79187ac099d6552a9e52748177bbdb600220424d5","observation_id":"5eaad38e-d0fe-4d91-a979-7de8a2baa5a1","resolution":{"observed_at":"2026-08-12T16:43:54.877331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.025113Z","title":"Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.025113Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:def14a9bf966c094a711e2b6c2b95af27e0294db433083f794244857f28f46c1","observation_id":"f0c089f1-7a9b-40a5-b743-629a5ea592b2","resolution":{"observed_at":"2026-08-12T16:43:54.025113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.860833Z","title":"Chipformer: Trans- ferable chip placement via offline decision transformer,","venue":null,"work_id":"545805a8-1d19-43a0-be68-2492cc4fd48c","year":2023},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.029679Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:01d47bf124ea6c66639242147a9dce49d4423afa392e5f8d0c00ca3e858dd488","observation_id":"eee13026-f5a8-43eb-9361-152374e75a50","resolution":{"observed_at":"2026-08-12T16:43:54.865543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/1054676","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.547345Z","title":"Miracle: Multi-action reinforcement learning-based chip floorplanning reasoner,","venue":null,"work_id":"78307c87-cccc-47eb-b988-052f8ff3be30","year":2024},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.033340Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:a89619942c111cb51d7bc961343b28795dcc2780731be8af2640d6fe68d58a26","observation_id":"86b5cb36-f984-4a1c-ab47-75ce4657aa35","resolution":{"observed_at":"2026-08-12T16:43:54.553310Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.848625Z","title":"Modeling relational data with graph convolutional net- works,","venue":null,"work_id":"bbdffeca-1163-4dbc-86dd-a63e2b48a75a","year":2018},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.036574Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:4a74f1e7fb12abb48dce43ac1e0256fb9059f3ac74ab1ea3839e0c87a079b571","observation_id":"738f6176-a86d-4967-81fe-6705fc164628","resolution":{"observed_at":"2026-08-12T16:43:54.852964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.08458","last_updated":"2015-12-02T18:06:03Z","snapshot_observed_at":"2026-08-20T05:06:23.408777Z","submitted_at":"2015-11-26T17:45:01Z","title":"An Introduction to Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.08458","snapshot_observed_at":"2026-08-12T16:43:54.039625Z","title":"An introduction to convolutional neural networks,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.039625Z"},"links":{"cited_paper":"/paper/1511.08458","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:9dd17804dc25d6715d2283ed71649adc8a14b247f1d9271e6feef48e4dee0bbd","observation_id":"e11aabc1-5932-433c-b899-dd2146d5666e","resolution":{"observed_at":"2026-08-12T16:43:54.039625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.837243Z","title":"Anagen: A methodology for analog circuit generation,","venue":null,"work_id":"b463ab8b-0b5b-4565-b7ab-6bdfc7aa81bc","year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.043206Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:3e5fefe2ba1b79fd75892a5a59460f796d46c57ac494cda9e322c7e742992504","observation_id":"43632342-884a-4998-86c1-b39be397fc03","resolution":{"observed_at":"2026-08-12T16:43:54.841295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.825210Z","title":"A procedural generator for the sizing and physical synthesis of a mosfet low-side driver,","venue":null,"work_id":"cd788427-b191-4e3a-afa3-3aa3548f98b9","year":2023},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.046449Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:ed15d649e462f727acd4609d57363e05c67171f841ff7c3d2fa8123082a69f15","observation_id":"0d7be252-1707-4363-bc6f-4d336da98a8e","resolution":{"observed_at":"2026-08-12T16:43:54.829132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16951","last_updated":"2024-05-27T08:42:42Z","snapshot_observed_at":"2026-08-19T12:36:36.332810Z","submitted_at":"2024-05-27T08:42:42Z","title":"Fast ML-driven Analog Circuit Layout using Reinforcement Learning and Steiner Trees","version":1},"cited_work":{"arxiv_id":"2405.16951","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.16951","snapshot_observed_at":"2026-08-12T16:43:54.463662Z","title":"Fast ML-driven Analog Circuit Layout using Reinforcement Learning and Steiner Trees","venue":"cs.LG","work_id":"a1a43a15-1790-4d24-893d-661cbdc56b87","year":2024},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.050130Z"},"links":{"cited_paper":"/paper/2405.16951","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:734fc335ccc36640d0411a913ba9b9622522303691c72453405e3eed73426e3b","observation_id":"36682717-5201-49d8-ae70-4edd1008c9c3","resolution":{"observed_at":"2026-08-12T16:43:54.468388Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.812411Z","title":"Symmetry within the sequence-pair representation in the context of placement for analog design,","venue":null,"work_id":"3e30332d-5d0b-4457-89e4-a6efbc3fcbaa","year":2000},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.054080Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:5e278a21d837c00736eb76f921c443f25ff20faf6cd819e6c6d90caaa8564886","observation_id":"316e4ace-cb1b-4b62-82fa-3afc2d94ee5f","resolution":{"observed_at":"2026-08-12T16:43:54.816944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.800494Z","title":"A Novel B*tree Crossover-Based Simulated Annealing Algorithm for Com- binatorial Optimization in VLSI Fixed-Outline Floorplans,","venue":null,"work_id":"99d44be9-f62f-4278-a7bf-41de9d5efebb","year":2020},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.057888Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:4da8dd7443b748533e61328992bd168a0f6abeafc4a5cb6f398f3ef98605115f","observation_id":"300bb2d0-a152-499d-ad03-5840e85673a1","resolution":{"observed_at":"2026-08-12T16:43:54.804377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.788905Z","title":"Scalable and order invariant analog integrated circuit placement with Attention-based Graph-to-Sequence deep models,","venue":null,"work_id":"737d94c4-9e15-4ab3-aa93-9beafb6daf0b","year":2022},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.061814Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:e29cd41acb0abb1575b4c283585ac590268944a96774174c44fb93a312fa557b","observation_id":"dead038f-04fb-40bf-9f0b-3a46af3f1b6b","resolution":{"observed_at":"2026-08-12T16:43:54.792478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.778426Z","title":"Analog layout placement for FinFET technol- ogy using reinforcement learning,","venue":null,"work_id":"5403029e-942c-4f22-b7a4-328b5b1e2e49","year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.065389Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:686296ed08e8eb66085acedfca4567160bfc278328cc1576df6602c8103a30a3","observation_id":"60e36ea0-fe30-42e4-b7ff-7d4e89536085","resolution":{"observed_at":"2026-08-12T16:43:54.782018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/9531070","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.444130Z","title":"A survey of graph neural networks for electronic design automation,","venue":null,"work_id":"f873731d-3edb-4d68-ae35-b1a5e67cb30a","year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.069577Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:b5528cf0f18240735ef80c4745be9891e342d2ec2884c4c3be11ed8cf4bfe508","observation_id":"afd9395e-bc98-4221-b02a-ba7b0482c4a0","resolution":{"observed_at":"2026-08-12T16:43:54.449892Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.766845Z","title":"Neu- ral message passing for quantum chemistry,","venue":null,"work_id":"05f87a1a-900f-4727-9fec-d63519ec868b","year":2017},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.073986Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:0eabe08804a7c26e30bd2c7763da6960de96a2d0ada28c76ba111b348dc3a910","observation_id":"5fa2005d-5336-407a-bce7-6b03e70953ba","resolution":{"observed_at":"2026-08-12T16:43:54.771141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.755015Z","title":"Semi-supervised classification with graph convolutional networks,","venue":null,"work_id":"6eeb629b-3fa7-4ae1-9e9f-f2802d2c538b","year":2017},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.078272Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:44e23932dd835468a01665607ec40e9c539f5472490158d64c95ea278e0a393e","observation_id":"040d4cc1-2efa-4ad8-9ff5-1842222c637c","resolution":{"observed_at":"2026-08-12T16:43:54.759000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.743721Z","title":"Machine learning based structure recognition in analog schematics for constraints generation,","venue":null,"work_id":"b414a44e-a5c1-4fe4-92e9-85fbf0208029","year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.081636Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:58d63d8a1b32061d054c96b97f62bc1230f7feb9d485fb9379f1ec1f785550f5","observation_id":"88e35aad-679e-435b-9df8-79819309a6e4","resolution":{"observed_at":"2026-08-12T16:43:54.747454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"pubmed/3410869","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.375267Z","title":"A graph placement methodology for fast chip design","venue":null,"work_id":"340afcd4-2d8f-4954-a5d8-9e33edd5a4e5","year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.085259Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:2f2d1800765ea633feed8e69bdd4ed9a728713402cea8296c7ac51dbaf99f297","observation_id":"ea93121f-e580-4c1e-ab2c-2ab44f9041b1","resolution":{"observed_at":"2026-08-12T16:43:54.381766Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.731824Z","title":"Toward Reinforcement Learning-based Rectilinear Macro Placement Under Human Constraints,","venue":null,"work_id":"9ad9c3e1-3581-4ac7-ab84-a23979dd7632","year":2023},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.089258Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:8115a4f330abc037a3f6fa44a37ee649c77699be60da3afbae461b8b7a61cc8d","observation_id":"de82f740-bfba-4cab-b038-b263c13f1309","resolution":{"observed_at":"2026-08-12T16:43:54.735834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-08-20T07:04:06.309989Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-12T16:43:54.093549Z","title":"Prox- imal Policy Optimization Algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.093549Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:ab7454cab4e616ec58e25556d6cb46e082c44670124be8f93ea4a3c036f6ae68","observation_id":"6287625e-a4d8-4a72-ad8b-12390c4484dd","resolution":{"observed_at":"2026-08-12T16:43:54.093549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.14171","last_updated":"2022-05-31T01:58:03Z","snapshot_observed_at":"2026-08-20T17:24:36.725718Z","submitted_at":"2020-06-25T04:47:09Z","title":"A Closer Look at Invalid Action Masking in Policy Gradient Algorithms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.14171","snapshot_observed_at":"2026-08-12T16:43:54.097758Z","title":"A closer look at invalid action masking in policy gradient algorithms,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.097758Z"},"links":{"cited_paper":"/paper/2006.14171","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:10cb2d30599b4c87eca776273f4794f9ec11fd11a9c2536cb189ad322e59f38b","observation_id":"652b256a-eaaf-4233-94de-631fc1e5f332","resolution":{"observed_at":"2026-08-12T16:43:54.097758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1410.4615","last_updated":"2015-02-19T15:33:35Z","snapshot_observed_at":"2026-08-14T23:15:21.933877Z","submitted_at":"2014-10-17T01:35:12Z","title":"Learning to Execute","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1410.4615","snapshot_observed_at":"2026-08-12T16:43:54.101432Z","title":"Learning to Execute,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.101432Z"},"links":{"cited_paper":"/paper/1410.4615","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:7566e48bfa43039f2027253c303d260a01cc616654d4ab244bd136f201a4e3ff","observation_id":"3e927cf2-8594-49a1-963d-e2aae15bcc1b","resolution":{"observed_at":"2026-08-12T16:43:54.101432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.720426Z","title":"Magical: An open- source fully automated analog ic layout system from netlist to gdsii,","venue":null,"work_id":"a1c91d46-51fb-40b2-ac82-738e9a665f2a","year":null},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.105286Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:133af4bd7e5be8e41fe4f336014cd7caf483ac6acab56d98befb1d311cf2296a","observation_id":"6ea1b388-2447-495d-998a-765c62d02d3c","resolution":{"observed_at":"2026-08-12T16:43:54.724601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.707596Z","title":"Align: A system for automating analog layout,","venue":null,"work_id":"0a67f84a-58aa-42d5-9447-43e9a95cc353","year":2020},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.113775Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:3d0497b2a872e3d9305ef091e9e6af0dd1a8967ab9aad1529e2984ff64ebf8f0","observation_id":"db378856-cf08-43a5-87a6-d04c9f97ef11","resolution":{"observed_at":"2026-08-12T16:43:54.711905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.01315","last_updated":"2020-08-25T15:46:13Z","snapshot_observed_at":"2026-08-18T10:54:34.717319Z","submitted_at":"2019-09-03T17:10:28Z","title":"Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.01315","snapshot_observed_at":"2026-08-12T16:43:54.118070Z","title":"Deep graph library: A graph-centric, highly-performant package for graph neural networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.118070Z"},"links":{"cited_paper":"/paper/1909.01315","citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:80425ee86c69e4f02a30ce3047a9a88d577d27d7da299f52c1732e0e58997551","observation_id":"1e6ef213-966b-4297-9f27-a4f19ee08312","resolution":{"observed_at":"2026-08-12T16:43:54.118070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.123138Z","title":"Stable-baselines3: Reliable reinforcement learning implementations,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.123138Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:48ec9b3a1b37a3ab86f342e1c24591ae6194abac85bec14d32ecb4eea290b74d","observation_id":"10c967d2-cbc3-4ad2-9fe4-c0550fbc80b5","resolution":{"observed_at":"2026-08-12T16:43:54.123138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/9195880","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:43:54.271234Z","title":"Available: https://ieeexplore.ieee.org/document/9195880/","venue":null,"work_id":"a7096223-c924-4a6d-9c01-cd86cf15103d","year":null},"citing_paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-12T16:43:54.109380Z"},"links":{"citing_paper":"/paper/2411.15212"},"observation_digest":"sha256:bbef74971e92192503147cc4edc7adc226d210bc13779a9c792b16c073882243","observation_id":"c5fe9fb9-d635-4468-8c92-fbf7c09ac6b0","resolution":{"observed_at":"2026-08-12T16:43:54.278823Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.15212","last_updated":"2024-11-20T12:11:12Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-19T12:31:26.039531Z","submitted_at":"2024-11-20T12:11:12Z","title":"Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":5,"verified_fuzzy":17},"total_outbound_references":31},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2411.15212."}