{"as_of":"2026-08-08T14:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a5fcb0697633dbde29575f5f743f0e962de041feb5bf9b7630d830cf416051c","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:54:58.649823Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.04001/citation-record","integrity":"/paper/2506.04001/integrity","json":"/paper/2506.04001/citation-record.json","paper":"/paper/2506.04001"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2101.08134","last_updated":"2021-03-19T10:43:12Z","snapshot_observed_at":"2026-07-06T10:34:02.819928Z","submitted_at":"2021-01-20T13:59:52Z","title":"Zero-Cost Proxies for Lightweight NAS","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.08134","snapshot_observed_at":"2026-08-07T10:54:58.434900Z","title":"Zero-cost proxies for lightweight nas","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.434900Z"},"links":{"cited_paper":"/paper/2101.08134","citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:6d0a6da8c2e008e0b1dbce157978ccbabf3f1d86d966c92fbc72f5d95134092b","observation_id":"b62a2204-18d5-456b-bf4e-29cf9e67dc9f","resolution":{"observed_at":"2026-08-07T10:54:58.434900Z","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":"2026-08-07T10:54:59.303063Z","title":"Random search for hyper-parameter optimization","venue":null,"work_id":"6596ada7-c4ec-4ef1-90f9-ef60087814f8","year":2012},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.439480Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:c26acc8eb1da1ff64684ee15d46ac421e9a8d24467e5baff3fd322c8257c68fa","observation_id":"1186c38b-1689-4eca-85f9-0cfc2fff62fb","resolution":{"observed_at":"2026-08-07T10:54:59.305995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.294052Z","title":"Progres- sive differentiable architecture search: Bridging the depth gap between search and evaluation","venue":null,"work_id":"7f1d35ca-28ca-44c2-9f26-3c079194498a","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.444808Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:cfcbcc749dcb2944b555ddf133b01a79abe73d382c791128783a92e3e5bb0d54","observation_id":"c228f78d-00cd-4424-a462-059cb78d1980","resolution":{"observed_at":"2026-08-07T10:54:59.297459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.285515Z","title":"Drnas: Dirichlet neu- ral architecture search","venue":null,"work_id":"7d39548e-2957-43e5-b098-8cd4a08611d9","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.449001Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:c23a4aa96d405ac586f608c69a6acf24c6317489113335414ff18f96ffa154d8","observation_id":"26cbbe9e-27b6-4345-8c44-ac296bb2b789","resolution":{"observed_at":"2026-08-07T10:54:59.288676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.276393Z","title":"Not all operations contribute equally: Hier- archical operation-adaptive predictor for neural architecture search","venue":null,"work_id":"1abc9153-b510-4058-b017-c19a1e9c6868","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.452817Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:302d9000f0bd27722de7818630e7025004b97ccc59a0274c2725c3ded68931fb","observation_id":"83fe5f6f-b43c-42fb-a8fe-b7eb33774294","resolution":{"observed_at":"2026-08-07T10:54:59.280108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.267668Z","title":"Fair darts: Eliminating unfair advantages in differentiable ar- chitecture search","venue":null,"work_id":"52bf8f1b-8fdc-49ef-9fa7-497b8c2ff403","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.456140Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:93cb65e7c5a474b98749990a7c63fa4cb11e064b51a15714d3a98acbe4025fd3","observation_id":"bda9754f-ea97-44fa-9ce5-f3a4088b4e28","resolution":{"observed_at":"2026-08-07T10:54:59.270755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.258879Z","title":"Environment inference for invariant learning","venue":null,"work_id":"dca07cb9-df77-469b-bba8-265a1ccd9e67","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.459668Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:5ae5a22c509f420c781c3b4208315e87ad5956618495f003c669cb2615e21037","observation_id":"7e0aa1c4-2ad0-4a9e-994d-269be28b3a21","resolution":{"observed_at":"2026-08-07T10:54:59.261878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.250051Z","title":"NAS-Bench-201: Extending the scope of reproducible neural architecture search","venue":null,"work_id":"0a911a5a-832b-4975-83f9-d85a01d5eaa1","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.462848Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:ae22162da43c5e9108adee80c1fea0edc127d69895e7f4d30467dd874eef9c0f","observation_id":"81bc993d-ce29-4e28-ad3a-aaae71279d0b","resolution":{"observed_at":"2026-08-07T10:54:59.253159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.241183Z","title":"Searching for a robust neu- ral architecture in four gpu hours","venue":null,"work_id":"d29b4956-2f3e-4999-ba82-c149a0b4eca5","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.466007Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:607bad3f6a976b217402c28e7edcbb6eec96a1c598f87c3a2d7fcc188fb2a15c","observation_id":"224f1ce5-db54-4cfa-a9d9-61aff2287808","resolution":{"observed_at":"2026-08-07T10:54:59.244258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.232406Z","title":"TransNAS-Bench-101: Improving transferability and generalizability of cross-task neural architecture search","venue":null,"work_id":"45b0f35d-5dd4-4d42-b6e3-7722ebcbf84a","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.468956Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:f11d9613131d6a2a399191cf55355f7afdb754968f3f6789ca3cba78424eb6a8","observation_id":"7052c531-197e-4163-93a2-7e721633c55e","resolution":{"observed_at":"2026-08-07T10:54:59.235759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.222474Z","title":"Brp-nas: Prediction-based nas using gcns","venue":null,"work_id":"6dc342d8-509e-4019-8234-3063387fb49d","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.472047Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:5360a642ce8359ca10682548329aa08c0e556821f111f9625e73da7d12ec3994","observation_id":"e78489e4-1df7-4ef0-b5e7-65f13bcc3898","resolution":{"observed_at":"2026-08-07T10:54:59.226635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.213552Z","title":"Neural architecture search: A survey","venue":null,"work_id":"b61e7e1c-1422-48e9-89cc-511c65cdca23","year":1997},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.475124Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:0efcd83e5910c4e5fc098a9e7b50751b28288d0dc373ffe010518dd4bd757421","observation_id":"6862d597-3bdf-4e89-8172-b4fcbacf38b5","resolution":{"observed_at":"2026-08-07T10:54:59.216731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.204276Z","title":"Generalizing few-shot NAS with gradient matching","venue":null,"work_id":"42b81d50-9a2a-4892-bf4a-2681e7aee2db","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.478659Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:349d774553f20a9c79bd3a216a89bf8ce6e2bf663184c812596741fbbcc80ecd","observation_id":"b66c0617-5b24-441e-919b-792f5653560b","resolution":{"observed_at":"2026-08-07T10:54:59.207577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.195058Z","title":"Angle-based search space shrinking for neural architecture search","venue":null,"work_id":"817aa3d2-55f4-44fa-894a-2304041fc5a2","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.481818Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:b536df699189d93a7237379ddb359734270b08a36cbf1e17833787e44007fb9f","observation_id":"aa67d02d-c3ec-4899-8c8a-d8c54645b6d9","resolution":{"observed_at":"2026-08-07T10:54:59.198236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.185396Z","title":"Arch-Graph: Acyclic architecture relation predictor for task-transferable neural ar- chitecture search","venue":null,"work_id":"c1b07651-6a15-4a79-86d4-94ce3943d87e","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.484946Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:80a04484ff1b995066729034cb53c978fd5b38d2d71b02cd8f3f00deda6408d9","observation_id":"eb299312-7701-4f74-9947-ffadcde1b8d7","resolution":{"observed_at":"2026-08-07T10:54:59.189007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.175896Z","title":"Flowerformer: Empowering neural architecture encod- ing using a flow-aware graph transformer","venue":null,"work_id":"64bbff36-c0f2-4b5e-a469-459e7aab5572","year":2024},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.487796Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:23537986d9aa2797da75690e1a28c2c4765ea5eaa87a603207b340956d0345b9","observation_id":"201ee0f2-749e-489f-ae36-9704c5d898fa","resolution":{"observed_at":"2026-08-07T10:54:59.179213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.166324Z","title":"Graph masked au- toencoder enhanced predictor for neural architecture search","venue":null,"work_id":"fa1e9bd6-a7f7-445f-9cad-d14c2cf24417","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.490862Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:2e88eb76e9697af422f2033cd5fe3ad0f39a8918b220e306c861655fd6c0a7c8","observation_id":"0fae98cd-dfc8-4407-af39-becbb5466729","resolution":{"observed_at":"2026-08-07T10:54:59.169600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.157044Z","title":"Neural architecture search with bayesian optimisation and optimal transport.Ad- vances in neural information processing systems , 31, 2018","venue":null,"work_id":"86535c79-d495-4eae-a4b7-4677adc32a72","year":2018},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.494549Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:7571496d8baa41e1dac7ec64457beb9deb329d8e20a14c47911aa6408496c5e3","observation_id":"4bfe9eb6-cb91-4e77-83b2-f3c6a2f1ed8b","resolution":{"observed_at":"2026-08-07T10:54:59.160445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.147159Z","title":"Semi-supervised classi- fication with graph convolutional networks","venue":null,"work_id":"6d71bea5-fbfd-4ca8-ad2e-5dc22ca09549","year":2016},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.497390Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:3eaac2af4511f530d6901d63bbeb42dedd37b33a7ced41fd72b235e266acc8b1","observation_id":"6b773a1b-c6ed-4bc9-9a97-8a604a88b27e","resolution":{"observed_at":"2026-08-07T10:54:59.150695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.136910Z","title":"Nas-bench-nlp: neural architecture search benchmark for natural language processing","venue":null,"work_id":"c6079e5b-bf0c-496b-9ae0-92b83faa9198","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.500199Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:9863a2dfc25935dcbe459fe481494f7ab596a09b6f5e4ab1b5dc65f58fafd3a2","observation_id":"090d67a0-81bc-4113-b4d7-fbeb150d9bd6","resolution":{"observed_at":"2026-08-07T10:54:59.140264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.503248Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.503248Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:11bef2d1ccbc6a9e13b75fd736dcac2ddad9f6135b24e2938389da7eea719663","observation_id":"bd72b23b-af93-4deb-ad3b-662228c7a8c3","resolution":{"observed_at":"2026-08-07T10:54:58.503248Z","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":"2026-08-07T10:54:59.121933Z","title":"Az-nas: Assembling zero- cost proxies for network architecture search","venue":null,"work_id":"858eb3b0-b45f-412a-a5e1-b586626f041f","year":2024},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.506269Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:2554c46425478b89ee834dd594815bfa025247a36bbe6e3fd565c64e00c49eaa","observation_id":"a20f152f-93ab-4476-a533-852b075cb609","resolution":{"observed_at":"2026-08-07T10:54:59.125099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.112668Z","title":"Random search and repro- ducibility for neural architecture search","venue":null,"work_id":"ed40c2fa-1c1e-4a09-bc0e-4883058fd7ad","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.509233Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:c32251e236b4b3fb5db6d3cfb2cb3f1e52e38a725b386876fe0916690e07c4ab","observation_id":"bb17f158-8380-4e85-8527-ddff9f18a05f","resolution":{"observed_at":"2026-08-07T10:54:59.116170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.103574Z","title":"Improving one-shot NAS by suppressing the posterior fading","venue":null,"work_id":"45a77741-6af4-4bd7-9cba-7e0b0ab55208","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.512466Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:d82af9fe14eaa4d13b63a4f06df14c69907743da102b8a7586384b465da2ccb9","observation_id":"b1c648c2-9c1d-418d-b3fe-eefb2d0adfe7","resolution":{"observed_at":"2026-08-07T10:54:59.106792Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.094290Z","title":"DARTS: Differentiable architecture search","venue":null,"work_id":"2bf069e1-30b8-4742-b148-7a5fd2a51c8f","year":2018},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.515535Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:0c5a985da4eeb48eceabb7a70133b0b273fd1ca99d2cf04d4662e7aa387c3c3e","observation_id":"cc6779ed-d4ee-40f0-b496-0c2b3277edbf","resolution":{"observed_at":"2026-08-07T10:54:59.097582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.084285Z","title":"Homogeneous ar- chitecture augmentation for neural predictor","venue":null,"work_id":"e3307090-9d92-48fd-a8d5-0564763f2677","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.518459Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:05870c67b2cb3742fae0c95c496e7228f67bc039ccf7506995ac726a299e8f14","observation_id":"4c465fa4-a925-4f1f-8d31-b1eb43d67fa0","resolution":{"observed_at":"2026-08-07T10:54:59.088156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.075137Z","title":"Bridge the gap between architecture spaces via a cross-domain predictor","venue":null,"work_id":"a50c2fc5-b50b-47eb-ac40-39298483b133","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.521584Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:f262ee6bda8e7e8c55d615bb5b96072e7c41f50e4fe928566a0f09c4635939f0","observation_id":"21037da5-d988-4716-bcb7-bd0d319cf1b9","resolution":{"observed_at":"2026-08-07T10:54:59.078572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.065404Z","title":"TNASP: A transformer-based NAS predictor with a self- evolution framework","venue":null,"work_id":"4712a538-abd9-4f32-b68c-ea92403f402c","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.524503Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:80a278061e0ac227771bde68e617d46a4db6fce77652161cac4e7dd00f95804c","observation_id":"c6b9308c-f44b-489b-9639-a994392c7ad2","resolution":{"observed_at":"2026-08-07T10:54:59.068686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.055711Z","title":"Pinat: A permutation invari- ance augmented transformer for nas predictor","venue":null,"work_id":"f6f583b7-f481-4b9a-a1c2-87a6363d149a","year":2023},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.527635Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:f97420d76e81abc7bf8d9eafcc4c5a3d009091aa496036b558da0f7d0beee828","observation_id":"d5c85e52-587d-4898-b1d1-cc69b56fdc70","resolution":{"observed_at":"2026-08-07T10:54:59.059347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.046046Z","title":"PA&DA: Jointly sam- pling path and data for consistent NAS","venue":null,"work_id":"82eb6da8-2369-48c9-a253-e5c0f2b37fad","year":2023},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.530739Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:7e69aaab7e634356e9ba8ecb01f225c16426147b5b4c8d5fd5489f0160c39923","observation_id":"a575f151-6f59-4766-80f0-b450d8c97cef","resolution":{"observed_at":"2026-08-07T10:54:59.049356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.036850Z","title":"Neural architecture optimization","venue":null,"work_id":"3ea79668-23a3-40a1-bac9-ff1d7d7ee46b","year":2018},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.533618Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:eb858b80d3867e5b2106c1fd4a7f31055a300e9c284d18a8611c69faf0d602ca","observation_id":"08a92353-453b-48a8-ab6c-0841eee01e10","resolution":{"observed_at":"2026-08-07T10:54:59.040026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.027550Z","title":"Neural architecture search without training","venue":null,"work_id":"488c7ca6-2159-4e61-9439-c3af8333ee88","year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.536398Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:155a776f7e9643ebe0e1e1198baa55fdc6eddac63afe0d3fc43f1d83fbf71955","observation_id":"787f2e8a-1b2a-4842-87c1-3580e55db4e5","resolution":{"observed_at":"2026-08-07T10:54:59.030715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.016710Z","title":"Build- ing optimal neural architectures using interpretable knowl- edge","venue":null,"work_id":"d27620a8-36d7-4acd-b494-c89cbae0cdce","year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.539684Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:0770238c3271cfa535b1bb3995e3860a8e50469366d0ac3ecabdfcdb1540963e","observation_id":"8cdc2211-5063-4224-9811-339bdd6d9b38","resolution":{"observed_at":"2026-08-07T10:54:59.020822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:59.007125Z","title":"A generic graph-based neural architecture encoding scheme for predictor-based NAS","venue":null,"work_id":"33e5ef3f-6536-4d27-b777-35dc69a2ae34","year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.542601Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:be7017f83377aee0a2c5dda86639c70fd0446ac061494d3c98e8c7fb001a719f","observation_id":"20fbaa90-625d-4742-9cff-4ab76e02ca86","resolution":{"observed_at":"2026-08-07T10:54:59.010498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.998183Z","title":"Evaluat- ing efficient performance estimators of neural architectures","venue":null,"work_id":"5afcf645-2bc6-4ef9-a095-9f186f4a41e9","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.545855Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:8658ef236eb82cd72d76bb56bda9309f24d7b1ba2c15362dee5487576d5fab67","observation_id":"0bc9a170-1290-4905-808b-82a575a2d9c6","resolution":{"observed_at":"2026-08-07T10:54:59.001434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.989095Z","title":"Ta-gates: An encoding scheme for neu- ral network architectures","venue":null,"work_id":"b8706a42-c39e-4ab8-ad1d-8ec67fb972c4","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.549129Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:525ec0f42481fb71aa56d674459cc7b94076106bae6a7f7354d25ebf561c0814","observation_id":"f9007f8c-be4f-4913-95fc-a12f4752c0ae","resolution":{"observed_at":"2026-08-07T10:54:58.992431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.979174Z","title":"Causality","venue":null,"work_id":"ec7c0c0c-f67f-4e80-b1ee-77a4d8085d73","year":2009},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.552204Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:12c5f396cd5743145c5703616e74c4c2bb4ab7d3ef4e18f029dc42638b6243bd","observation_id":"b3cd015c-69c4-46ed-adbf-0ed39b85aca4","resolution":{"observed_at":"2026-08-07T10:54:58.982861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.554982Z","title":"Causal inference in statistics: A primer","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.554982Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:8205d6a7f785d5cd09c494e991b34e83946ad6d3a775c8d3925e5bf54cc70365","observation_id":"6cbb647d-7c75-4b12-9df4-0ba4633196b5","resolution":{"observed_at":"2026-08-07T10:54:58.554982Z","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":"2026-08-07T10:54:58.964125Z","title":"Models, reasoning and inference","venue":null,"work_id":"6f878878-5eac-4fcf-a552-427849fd7b24","year":2000},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.558211Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:9e6604f0557aeeb50ced4e39f0a02e75722e0e214995e5a67ec51794c0dcdfc2","observation_id":"b203a9fd-c1cc-497c-bcda-ef9ef49621a4","resolution":{"observed_at":"2026-08-07T10:54:58.967756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.955379Z","title":"PRE-NAS: Evolutionary neu- ral architecture search with predictor","venue":null,"work_id":"8c20f577-7ba9-4822-9118-59999e26a792","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.561133Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:41bb45903eab915bd70c04e68f602c0cfcce7f6271bd9f5c470e2eca7f034dd6","observation_id":"bd9df181-a574-4430-859e-363d63d82f2e","resolution":{"observed_at":"2026-08-07T10:54:58.958652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.946551Z","title":"Regularized evolution for image classifier architecture search","venue":null,"work_id":"e786f286-f551-4f5c-96e3-f057f708f261","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.564155Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:0c90966b88bf1d68e103ad50b53a1b3aa52530fe1f62ff333279c00d82be13eb","observation_id":"4b5961a4-1558-4cba-8bbd-d0c8a41fc4b4","resolution":{"observed_at":"2026-08-07T10:54:58.949733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.936317Z","title":"A comprehensive survey of neural architecture search: Challenges and solu- tions","venue":null,"work_id":"5dafa16e-879c-4024-98d6-c0e6cd09122a","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.567225Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:112273c8b465df4ed63a58516c58fb78414c9485a3dc9c02799cf91c20b13b99","observation_id":"74393821-ebed-4582-856f-544a684545a0","resolution":{"observed_at":"2026-08-07T10:54:58.939685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.926532Z","title":"Interpretable neural architecture search via bayesian optimisation with weisfeiler-lehman kernels","venue":null,"work_id":"a2eb6ad6-97a9-4236-85a3-b176f887b894","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.570300Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:7b2ee66ac423590fcfb7cfd89889c6c7bd5cbb563bc54b3df6b5de2d783479c8","observation_id":"37175a45-f0c0-4025-bd50-b4aa6192cedb","resolution":{"observed_at":"2026-08-07T10:54:58.930010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.917355Z","title":"Estimates of the regression coefficient based on kendall’s tau","venue":null,"work_id":"86ec157a-3390-4cf7-bee9-c3a76c36f37a","year":1968},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.573238Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:74cc302e14924b5ed01720160ce74b3dedff89f78b905afb15c1fc174d6d6487","observation_id":"ee2a4bb5-5cd9-43b3-a9a4-97e24236f885","resolution":{"observed_at":"2026-08-07T10:54:58.920700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.907613Z","title":"Bridging the gap between sample-based and one-shot neural architecture search with BONAS","venue":null,"work_id":"c9888d16-d175-4004-885d-9717b4360579","year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.576347Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:5473758ba126db6a12c022112f98e7904e2d596c9787d6484eb917ec636a3606","observation_id":"ac24cfd5-d6ba-401c-adaf-4a7f4fc5ead5","resolution":{"observed_at":"2026-08-07T10:54:58.910991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.897830Z","title":"Mnas- net: Platform-aware neural architecture search for mobile","venue":null,"work_id":"f8dd0421-a42f-4d30-9bd9-749ac463ebd1","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.579644Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:f1349b7bc66eb3b90da69ddaf1ba65570a751ad4b3094997f7d2bd2364bde5e9","observation_id":"90cacdd2-3386-4d84-8142-1eb40eb2023c","resolution":{"observed_at":"2026-08-07T10:54:58.900838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.887985Z","title":"Invariant feature learning for generalized long-tailed classification","venue":null,"work_id":"a53da88c-e424-40b5-b3be-23bf9f362add","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.582552Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:75069d18cfc38405e5fd146915a1c27a4e60aac4b1a0ea091ffc591d1ac61dd5","observation_id":"e28975f9-0318-4a44-9203-ebf4967c85c8","resolution":{"observed_at":"2026-08-07T10:54:58.891330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.879181Z","title":"Attention is all you need","venue":null,"work_id":"a7ebb71f-e571-4544-a888-f088b3cc00e6","year":2017},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.585438Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:52bb7213af920a2c4db13719579d70615f0ed80137f1712245165eee95285bb4","observation_id":"0a39d667-ca76-49ed-b50d-d0fb216c5a4e","resolution":{"observed_at":"2026-08-07T10:54:58.882185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.869625Z","title":"On redundancy and diversity in cell-based neural architecture search","venue":null,"work_id":"c0737245-07b2-44de-a7d1-c8ab1ecedb68","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.588132Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:598e1647b6f931042d0a3b97850c5f041f3adee455b40d991f95bee8cb919dce","observation_id":"041d4daa-3600-4178-be34-a04b3c470230","resolution":{"observed_at":"2026-08-07T10:54:58.872752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.860557Z","title":"Visual commonsense R-CNN","venue":null,"work_id":"e0416208-b04b-449e-9c0d-c11ba2344c4c","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.590906Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:9b2ba276730eaef3e79b11cb1ec36aef73393f275cc1213db4f8db2ee6ee778f","observation_id":"c707054e-cf99-4e3b-b7fe-d6c61aa9a713","resolution":{"observed_at":"2026-08-07T10:54:58.863604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.851395Z","title":"NPENAS: Neural predictor guided evolution for neural architecture search","venue":null,"work_id":"4402c711-0d71-49b3-bb2b-d17408cb6018","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.594156Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:b8d3d510da648f212f1d5cd2f05aa446a326a51f92c633bcca78d25cb0c9b08c","observation_id":"0e6ce800-5b45-48d4-b893-88d51e3e578f","resolution":{"observed_at":"2026-08-07T10:54:58.854931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.842227Z","title":"Neural predictor for neural architecture search","venue":null,"work_id":"aba81794-d2ab-473a-9fca-dc04d946267c","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.597609Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:8a504a2f5c2e9f0a1f12d3aec0ee0085ff43dd38b78dfc13c9eb504cbe41e4d8","observation_id":"d0565ad2-517d-4387-b6d7-eb464689864e","resolution":{"observed_at":"2026-08-07T10:54:58.845375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.833088Z","title":"BA- NANAS: Bayesian optimization with neural architectures for neural architecture search","venue":null,"work_id":"e16fe6f7-c830-4e20-bb6b-3b22ef666546","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.600668Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:33184d5e10e4491e475965c5bad780d8bfed65062262fb0e436083c21e8a004d","observation_id":"10ed635e-8e20-4c97-aaf2-463ea71b3861","resolution":{"observed_at":"2026-08-07T10:54:58.836348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.823327Z","title":"Stronger NAS with weaker predic- tors","venue":null,"work_id":"df7323e6-e182-49a9-a60c-a9cb8967b707","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.603703Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:bd66a30e3a8bc3e27dc91f90acdea177f760cf38bcdaedc2f31d13554a734853","observation_id":"fa21af73-a690-4287-9ed8-6d838c5bd263","resolution":{"observed_at":"2026-08-07T10:54:58.827275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.814204Z","title":"Representing long- 10 range context for graph neural networks with global atten- tion","venue":null,"work_id":"67a9ec56-9936-427e-95dd-c90e9603ab5c","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.607811Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:bd15e8304c5a1854a794e6af419e9b60ce093a1b526ae3ee494f52ce12d4a048","observation_id":"f3a30dc6-dac5-42b1-a9d5-402ca5b3d118","resolution":{"observed_at":"2026-08-07T10:54:58.817367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.805365Z","title":"Shapley-NAS: Discovering operation contribution for neural architecture search","venue":null,"work_id":"3b9535d3-2b08-4957-89e1-c63fe5411fb7","year":2022},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.611531Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:6642f7dfb9995bed534c02de181bc2e78194ed5b18719772f8485aa04db25302","observation_id":"738c42c5-4523-44bd-8d11-b8365b2b51c0","resolution":{"observed_at":"2026-08-07T10:54:58.808570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.796019Z","title":"Genetic cnn","venue":null,"work_id":"2cb12dbe-8caf-441b-a2bc-56f465d3303e","year":2017},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.614477Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:961867511070190990a62d928210c042e996c274e587705cff4f6143fd8e674a","observation_id":"88aea546-442d-4921-b9bd-94badafa53bf","resolution":{"observed_at":"2026-08-07T10:54:58.799574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.00826","last_updated":"2019-02-22T19:15:54Z","snapshot_observed_at":"2026-07-06T07:05:24.565760Z","submitted_at":"2018-10-01T17:11:31Z","title":"How Powerful are Graph Neural Networks?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.00826","snapshot_observed_at":"2026-08-07T10:54:58.617623Z","title":"How powerful are graph neural networks? arXiv preprint arXiv:1810.00826, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.617623Z"},"links":{"cited_paper":"/paper/1810.00826","citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:0cd5d0da9b8af1e1324ef65a741648b2fc1ffa86b71c722b70c6b987e3d2c35a","observation_id":"0b3dd115-8327-4945-851b-e859ed9e0ec7","resolution":{"observed_at":"2026-08-07T10:54:58.617623Z","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":"2026-08-07T10:54:58.786560Z","title":"PC-DARTS: Par- tial channel connections for memory-efficient architecture search","venue":null,"work_id":"6c4b2f1e-7bfd-45b0-a2b0-67bd31ec76c1","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.620870Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:dd4a97fae1b47ad5d59a46e76d4a5de5773461508f92d2e2bc92bace8440d507","observation_id":"aabb544f-67a6-4d1d-9b3b-9bdf8d76cd7d","resolution":{"observed_at":"2026-08-07T10:54:58.789777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.776059Z","title":"Renas: Relativistic eval- uation of neural architecture search","venue":null,"work_id":"f55011f9-ce4c-4f49-919f-3d073453023a","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.624739Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:1776547b21d739acde382b5d0a33f487f8d5fd70b0bc2dc5454bb1f924878219","observation_id":"89a31e6d-2fc1-440a-8565-a0e478eb79e9","resolution":{"observed_at":"2026-08-07T10:54:58.780064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.766286Z","title":"Does unsupervised architecture representation learning help neural architecture search? Advances in Neural Information Processing Systems, 33:12486–12498, 2020","venue":null,"work_id":"bda28f6c-24a0-4387-ac91-5d499127ac70","year":2020},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.627788Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:f76748b9929bee013b1846bc2c48cedbde240fd7d7966101f47fdbc0160dc276","observation_id":"28aa2230-8a11-42a7-b2bf-1f7ef6a757f5","resolution":{"observed_at":"2026-08-07T10:54:58.769936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.756515Z","title":"CATE: Computation-aware neural architecture encoding with trans- formers","venue":null,"work_id":"2f907532-4973-45e1-b50b-22ca814b42e9","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.630725Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:6279835dca017721488edfa3b9328e38a2cf138efd11b612359338207fc12069","observation_id":"73c12754-d0da-4806-a8d0-2e24d988f70a","resolution":{"observed_at":"2026-08-07T10:54:58.759879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.746351Z","title":"NAR-Former: Neural architecture representa- tion learning towards holistic attributes prediction","venue":null,"work_id":"01120d84-534f-4910-b83a-4a261b0488f7","year":2023},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.633655Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:13573bcd034c2a5571ecb3c010726ed7d0dfc53519bceae2ead9d160b22c84cc","observation_id":"5dac3692-38b3-4f11-9b3c-190503479368","resolution":{"observed_at":"2026-08-07T10:54:58.749770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.736785Z","title":"NAS-Bench-101: To- wards reproducible neural architecture search","venue":null,"work_id":"fe56a114-f6dc-42a7-b472-5d08b932041c","year":2019},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.636577Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:1ebac50296684f845e60696d1216c4b4bf5cab034db6a90500118bca24fdd1f2","observation_id":"78b310c8-59e6-478f-a2d8-b04d9d439c98","resolution":{"observed_at":"2026-08-07T10:54:58.740176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.726878Z","title":"Do transformers really perform badly for graph representation? Advances in neural information processing systems , 34: 28877–28888, 2021","venue":null,"work_id":"8d62fdfa-812a-4dff-8315-591cfd65f28e","year":2021},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.639496Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:614bc2406929d1be6d02639c10d1b699459ac2fc287c7e39e13b77dd116f4cd5","observation_id":"d76af151-e66e-47f3-a947-48051f546acb","resolution":{"observed_at":"2026-08-07T10:54:58.730421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T10:54:58.716979Z","title":"Dclp: Neu- ral architecture predictor with curriculum contrastive learn- ing","venue":null,"work_id":"a73b1e39-f266-4faf-90d6-4b6db589e685","year":2024},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.642385Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:489c9667422db31d978e15cd731b1a7008c1f0f475929e395684a64f15105e4a","observation_id":"8633e4b2-7fd6-4c86-ba26-d710476394b3","resolution":{"observed_at":"2026-08-07T10:54:58.720414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.01578","last_updated":"2017-02-15T05:28:05Z","snapshot_observed_at":"2026-07-06T05:17:29.499249Z","submitted_at":"2016-11-05T00:41:37Z","title":"Neural Architecture Search with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.01578","snapshot_observed_at":"2026-08-07T10:54:58.645487Z","title":"Neural architecture search with reinforcement learn- ing","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.645487Z"},"links":{"cited_paper":"/paper/1611.01578","citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:fbcd448dd7ba25c8d28db8be0199f12d5af825361d4507d3f624e6c7bae88fd0","observation_id":"b3db12af-60c5-4f16-944b-0e9650dcbf4f","resolution":{"observed_at":"2026-08-07T10:54:58.645487Z","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":"2026-08-07T10:54:58.704582Z","title":"Learning transferable architectures for scalable image recognition","venue":null,"work_id":"829d6a80-4b1a-4a8a-92f4-eb8d9c74dd0c","year":null},"citing_paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T10:54:58.649823Z"},"links":{"citing_paper":"/paper/2506.04001"},"observation_digest":"sha256:743813182a7532749830a3141d4e1f51dc49a99c0582e1f25b8edd38dbac0f06","observation_id":"7208c9e5-48d8-467b-8914-821f8418cd80","resolution":{"observed_at":"2026-08-07T10:54:58.710034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.04001","last_updated":"2025-06-04T14:30:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T10:47:19.537160Z","submitted_at":"2025-06-04T14:30:55Z","title":"CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":63},"total_outbound_references":68},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2506.04001."}