{"as_of":"2026-08-09T18:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:199c6454209fb87798f7cf26dc420fec8d10b28200dd47b0c2ce01fb3b2e84b7","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:35:49.754751Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2507.05263/citation-record","integrity":"/paper/2507.05263/integrity","json":"/paper/2507.05263/citation-record.json","paper":"/paper/2507.05263"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:35:57.614811Z","title":"Spin glasses: Experimental facts, theoretical concepts, and open questions","venue":null,"work_id":"f9573b17-8191-4e72-9bbd-bfdb61348733","year":1986},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.124947Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:25d9477c200d35e3a7ea113b31721744743fc920431a2718d64d2de76882c727","observation_id":"4bf87971-a5af-482d-ac41-e1ec37866fe8","resolution":{"observed_at":"2026-08-06T23:35:57.744851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:57.194905Z","title":"The physics of amorphous solids","venue":null,"work_id":"4e9017fb-2fed-41e6-9ce2-98440766c472","year":2008},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.162034Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:9e7e80e68cc7f29ce4b0c8da623bb1d5dfc05bb1bbb8f9f70627a608ba209fa1","observation_id":"d067df9c-3573-49ea-8540-05689d410060","resolution":{"observed_at":"2026-08-06T23:35:57.364742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:56.864751Z","title":"Percolation on complex networks: Theory and application","venue":null,"work_id":"2fe662f1-fa9b-4251-8fee-c3b9112974f5","year":2021},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.214898Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:2c46cd0b4a81c54b881fe21cfc48733ebdc9a72cf3bbaa54da7382f91a5ea051","observation_id":"5de7c5f8-a987-41cc-a2cf-4dbc1398b239","resolution":{"observed_at":"2026-08-06T23:35:57.021885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:46.254828Z","title":"Absence of diffusion in certain random lattices","venue":null,"work_id":null,"year":1958},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.254828Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:20abb65b95f2e1184ca92e456afa6344cb84046eb551424e55e778ce6ad15d6b","observation_id":"e5ab073c-8b7b-4cd5-970f-28ea80aefe95","resolution":{"observed_at":"2026-08-06T23:35:46.254828Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:35:46.303835Z","title":"The jamming transition and the marginally jammed solid","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.303835Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:5fa7269becc48df250bad194e987f3f0fbc845c38f19a0ebca6e6a4e1836ca89","observation_id":"a70ebf54-f4de-482b-8860-ad31d2ad97ae","resolution":{"observed_at":"2026-08-06T23:35:46.303835Z","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":"2026-08-06T23:35:56.258573Z","title":"Neural networks and physical systems with emergent collective com- putational abilities","venue":null,"work_id":"acecfea7-007e-4a7e-a137-9502a2bdd030","year":1982},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.354916Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:47a7fcbfbf7f7e8ff0ac0eb522d18b0d167023dc5a10cd909e4988d96a328c80","observation_id":"1141f22e-47eb-42c7-887c-151d557df950","resolution":{"observed_at":"2026-08-06T23:35:56.474753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:55.985885Z","title":"Chaos in random neural networks","venue":null,"work_id":"5923edd8-704f-4a06-bc1f-10c4e2bdb839","year":1988},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.424749Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:140817509ac88877b67664b325bbca45fc75b847fff0e2a6e62704d5ca7bc8ec","observation_id":"91ae7f75-0bfe-4a92-8d24-d65a941ac2d1","resolution":{"observed_at":"2026-08-06T23:35:56.133481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:55.784343Z","title":"Comparing dy- namics: Deep neural networks versus glassy systems","venue":null,"work_id":"f26b271a-dc09-4dcd-b235-47730e2f03c3","year":2018},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.474750Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:3ba06bffff7d4627ed2187c67caa5396a5cdf021da92f2c20db40b434c477187","observation_id":"e0451edf-06f0-4793-8d20-0b70319049fc","resolution":{"observed_at":"2026-08-06T23:35:55.864980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:55.575844Z","title":"Spin-glass models of neural networks","venue":null,"work_id":"93cdf5c1-8c3d-4de2-a7e0-a67e1e2e9da3","year":1985},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.564937Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:52821b2ab64ffa689187e7c696e92d216025f306479f959cf5492a5c6620cdf3","observation_id":"d876fc6d-381b-4898-b428-b5ccd3d0b6c8","resolution":{"observed_at":"2026-08-06T23:35:55.661850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:55.336021Z","title":"Geometry of neural network loss surfaces via random matrix theory","venue":null,"work_id":"9d6886cc-c44c-4d3e-a931-e55178805dde","year":null},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.629794Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:0c556552dbf7bdc79322475934e42bb7c42804a4e550ac78159bac033f7b47a0","observation_id":"7838fbb3-100e-46f0-a286-d71ce97c1fcb","resolution":{"observed_at":"2026-08-06T23:35:55.477585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:55.081544Z","title":"Statistical mechanics of deep learning","venue":null,"work_id":"5828925c-193c-4bbb-997b-99eb829a3cde","year":2020},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.690672Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:fa5aab15654cf68b4bced4004c2ea5cb134e168f60ee8ba190e37ed56335301c","observation_id":"17935dd7-b62f-44d1-a37d-0ef9aa780d3d","resolution":{"observed_at":"2026-08-06T23:35:55.205549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:54.728652Z","title":"Statistical physics of deep neural networks: Initialization toward optimal channels.Physical Review Research, 5(2):023023, 2023","venue":null,"work_id":"2bc83065-8252-4eec-938e-4dc22e8ad08a","year":2023},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:46.834754Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:3fa0258682d433e4b4d11d8c79ba9bf62bb3d2dd46369842f4a36349f1d4db51","observation_id":"bab81740-fe10-4bd4-a091-6300a64f8df4","resolution":{"observed_at":"2026-08-06T23:35:54.878512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00396","last_updated":"2025-06-18T06:30:20Z","snapshot_observed_at":"2026-07-06T19:25:01.580792Z","submitted_at":"2024-10-01T04:39:04Z","title":"Dynamic neuron approach to deep neural networks: Decoupling neurons for renormalization group analysis","version":2},"cited_work":{"arxiv_id":"2410.00396","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.00396","snapshot_observed_at":"2026-08-06T23:35:51.114935Z","title":"Dynamic neuron approach to deep neural networks: Decoupling neurons for renormalization group analysis","venue":"cond-mat.stat-mech","work_id":"af4d66d7-c5d7-41db-90c6-f68b7b2a7c8b","year":2024},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.065621Z"},"links":{"cited_paper":"/paper/2410.00396","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:07cc57856afe271cb3c79a747fa3f5bba402e0b3c65bdfc230ff2a35befc2954","observation_id":"412f48f5-3fc2-4a0c-965f-fb1434bcd5be","resolution":{"observed_at":"2026-08-06T23:35:51.224174Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-06T23:35:47.244822Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.244822Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:dac04b41252bf392066627818e9c4d0e557245e1c6d2057016d24272021c650a","observation_id":"dfc48ff7-d2c6-40fa-b501-5d2884e9c799","resolution":{"observed_at":"2026-08-06T23:35:47.244822Z","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":"2026-08-06T23:35:54.508551Z","title":"A phase transition between positional and semantic learning in a solvable model of dot-product attention","venue":null,"work_id":"2e2b72bc-1628-402b-a195-214b3985afb4","year":2024},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.404751Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:281777c36786df4f171144c979a3b26810d4c34b23c54000a49264d3770d35b9","observation_id":"55fb6922-b488-421c-9a01-d82e00a6a4af","resolution":{"observed_at":"2026-08-06T23:35:54.604904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03789","last_updated":"2024-05-05T12:21:36Z","snapshot_observed_at":"2026-07-06T16:28:26.234851Z","submitted_at":"2023-10-05T18:00:01Z","title":"Grokking as a First Order Phase Transition in Two Layer Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03789","snapshot_observed_at":"2026-08-06T23:35:47.534854Z","title":"Grokking as a first order phase transition in two layer networks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.534854Z"},"links":{"cited_paper":"/paper/2310.03789","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:a24b775520c831efbe70aa498dbecadfb9d4eea9773cf88e048b6eab6e98d7c4","observation_id":"0091626b-dead-4767-bf5a-465b4f2f9132","resolution":{"observed_at":"2026-08-06T23:35:47.534854Z","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":"2026-08-06T23:35:54.301991Z","title":"Sampling with flows, diffusion, and autoregressive neural networks from a spin-glass perspective","venue":null,"work_id":"50f69298-f50d-4daa-95cc-d49a02be73f6","year":2024},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.695120Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:e3795ffc3727ee18bb77c0e398f759ef2b843831711c837fc1e4a2e90946f531","observation_id":"430e0c65-9d5b-47a3-8ac8-25c2b8c335d7","resolution":{"observed_at":"2026-08-06T23:35:54.358745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2503.01361","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:35:50.493099Z","title":"Statistical physics analysis of graph neural net- works: Approaching optimality in the contextual stochastic block model","venue":null,"work_id":"87af5458-f99a-40cb-a4ce-a10b4f259837","year":2025},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.804750Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:2dcb767bde0607ae2070e3c31af00b5b0fa71dc3613f34ee9c0f5b7a1de2f4e3","observation_id":"7a0af469-14ff-48b8-ba38-41c9fe57fa34","resolution":{"observed_at":"2026-08-06T23:35:50.628632Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:54.097682Z","title":"Graph neural networks for social recommendation","venue":null,"work_id":"420a3a9a-e01f-4529-82a2-2644f780c0cf","year":2019},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:47.915370Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:bbae24a38e305de00666e14344fb3ddd83c5691001c7b740eb55eb737fa04e61","observation_id":"9bd17c51-a497-4dc2-8d5b-a0f2f569c36f","resolution":{"observed_at":"2026-08-06T23:35:54.184271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.01411","last_updated":"2021-05-16T02:35:25Z","snapshot_observed_at":"2026-08-09T15:46:31.143748Z","submitted_at":"2020-09-03T01:54:25Z","title":"Learning from Protein Structure with Geometric Vector Perceptrons","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.01411","snapshot_observed_at":"2026-08-06T23:35:48.057462Z","title":"Learning from protein structure with geometric vector perceptrons.arXiv preprint arXiv:2009.01411, 2020","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.057462Z"},"links":{"cited_paper":"/paper/2009.01411","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:a6caac8eb78bca37708033ddf4e0e2d06f6b8eeccbff4b3ee42d37025b5ea54b","observation_id":"8bd983f8-b77b-45f6-a983-4a85da3bf806","resolution":{"observed_at":"2026-08-06T23:35:48.057462Z","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":"2026-08-06T23:35:53.910525Z","title":"Graph neu- ral networks for materials science and chemistry","venue":null,"work_id":"600e1d45-a6c6-403a-9e0e-7067a437db8c","year":2022},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.166297Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:dd7345dc50810f99039e5afaf51e4c9231582fce8c89a16409c91b51122f0899","observation_id":"c03ddf50-6246-4079-970d-027dc7eaa966","resolution":{"observed_at":"2026-08-06T23:35:53.981054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10947","last_updated":"2021-01-06T13:32:14Z","snapshot_observed_at":"2026-07-06T07:55:41.176211Z","submitted_at":"2019-05-27T02:59:06Z","title":"Graph Neural Networks Exponentially Lose Expressive Power for Node Classification","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10947","snapshot_observed_at":"2026-08-06T23:35:48.251490Z","title":"Graph neural networks exponentially lose expressive power for node classification","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.251490Z"},"links":{"cited_paper":"/paper/1905.10947","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:57ee645be06a68631b4756fe46f3d79749cc9a945eff4a9c1fd7fc66ed8f75eb","observation_id":"96892fdf-eee3-4be7-a84c-944b2e4b2dbf","resolution":{"observed_at":"2026-08-06T23:35:48.251490Z","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":"2026-08-06T23:35:53.653502Z","title":"Measuring and relieving the over-smoothing problem for graph neural networks from the topological view","venue":null,"work_id":"f1b6218b-bd4c-41a0-a908-9827ea1ead49","year":2020},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.364751Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:6539d8d1f286f531650bf4c27917d6048e588daa5269c015eefed59caa327d89","observation_id":"2b22296f-5afe-4f51-8035-023242a96561","resolution":{"observed_at":"2026-08-06T23:35:53.786814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:53.403892Z","title":"Deepgcns: Can gcns go as deep as cnns? In Proceedings of the IEEE/CVF international conference on computer vision, pages 9267–9276, 2019","venue":null,"work_id":"58d0f52b-6bde-434c-b254-cc3876039c90","year":2019},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.484749Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:8c074dbf35d52fa1f3fdbf52df3d22690aa9e4befc281f63729a2548a3547f15","observation_id":"eb917777-79b4-43e4-ba31-7d8d607c0692","resolution":{"observed_at":"2026-08-06T23:35:53.523835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.10903","last_updated":"2020-03-12T08:04:36Z","snapshot_observed_at":"2026-07-06T08:10:07.945422Z","submitted_at":"2019-07-25T08:57:45Z","title":"DropEdge: Towards Deep Graph Convolutional Networks on Node Classification","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.10903","snapshot_observed_at":"2026-08-06T23:35:48.574839Z","title":"Dropedge: Towards deep graph convolutional networks on node classification","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.574839Z"},"links":{"cited_paper":"/paper/1907.10903","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:9406fc83754861473546df3113fdc3bcafe94c1baf0ed933750d4e1061a47627","observation_id":"a2317651-03eb-4ccd-85e7-357142e9c707","resolution":{"observed_at":"2026-08-06T23:35:48.574839Z","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":"2026-08-06T23:35:53.157216Z","title":"Pde-gcn: Novel architectures for graph neural networks motivated by partial differential equations","venue":null,"work_id":"fb28517c-d4c0-457a-9160-01bfc68f06c3","year":2021},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.724877Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:5a21f60c68188aa61c88174c283e0408e5de65431417e812e0c1d91d6ec5ccf5","observation_id":"b231bb33-c413-4902-96f1-d2c75e1830e0","resolution":{"observed_at":"2026-08-06T23:35:53.255853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:52.898171Z","title":"Fifty years of anderson localization","venue":null,"work_id":"9455dbe5-471d-4027-ab17-a2ebf85dcba2","year":2009},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:48.874829Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:2061ddaa102c1188ec27a191c482d194593a53d7d1d9680a4c174596cd70f324","observation_id":"acade56c-c8d4-47ec-a6ef-eb1776790175","resolution":{"observed_at":"2026-08-06T23:35:52.971057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:52.604748Z","title":"Direct observation of anderson localization of matter waves in a controlled disorder","venue":null,"work_id":"f3491e4c-45fa-4ab4-914d-d2657e491b62","year":2008},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.024830Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:1d2d233fdaf50850c0986b00d14a20517a4f47f938a61dbd2bd5c0c47891329e","observation_id":"cfdad4b1-7d80-4ba9-b2ab-32e0076a5392","resolution":{"observed_at":"2026-08-06T23:35:52.683782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:52.343365Z","title":"Many-body localization and thermalization in quantum statistical mechanics","venue":null,"work_id":"ccb943e6-ff2c-4f3b-90f8-2cb2da94518d","year":2015},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.134830Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:d1a5f10897480ad8586a267d2b05468c8c34415620c33f58ac317a1d29f50585","observation_id":"0cfc426a-e4ba-454e-84d2-5d666aa4a96f","resolution":{"observed_at":"2026-08-06T23:35:52.428303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:51.994747Z","title":"Interplay of non- hermitian skin effects and anderson localization in nonreciprocal quasiperiodic lattices","venue":null,"work_id":"4370e1f9-8a9b-485a-a497-17dc6bffc83a","year":2019},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.265132Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:678fd198e1f715c34062a6682f7aeef39a4cb33eeaf04d3d8d13f894e492e668","observation_id":"ea3e5018-90f5-4535-8de1-9d7160bbbca2","resolution":{"observed_at":"2026-08-06T23:35:52.194895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-06T23:35:49.365156Z","title":"Semi-supervised classification with graph convolu- tional networks","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.365156Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:970019caad762b2ca8a02b8e114762ac7fe1df4fb3b49445b30e1b3f6da8dcaf","observation_id":"7cadf28f-6fdf-4f20-9db6-892bd5884caa","resolution":{"observed_at":"2026-08-06T23:35:49.365156Z","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":"2026-08-06T23:35:51.700756Z","title":null,"venue":null,"work_id":"a1c1ebc2-3d6e-4826-a0ba-a9cec181d164","year":null},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.535986Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:8bb10bb39d6a4cc0c61dd4fbeb916efe1f208a7b89a114b8e088492b64ba91f8","observation_id":"727a178f-5c08-4e6d-a3d3-5618f267f585","resolution":{"observed_at":"2026-08-06T23:35:51.794750Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T23:35:51.388716Z","title":"Bridging the gap between spatial and spectral domains: A unified framework for graph neural networks","venue":null,"work_id":"954c2b1b-2ebc-43e5-b3e2-205c5c1a986d","year":2023},"citing_paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T23:35:49.754751Z"},"links":{"citing_paper":"/paper/2507.05263"},"observation_digest":"sha256:7bca4e999afc3cbf5abc0b9453f3e33e583dffb59dada6f3f0e534a887b06675","observation_id":"3bca706b-22c0-4ce8-bfbe-7eed069d6955","resolution":{"observed_at":"2026-08-06T23:35:51.554753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.05263","last_updated":"2025-06-20T18:54:10Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T23:28:13.644847Z","submitted_at":"2025-06-20T18:54:10Z","title":"Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":2,"verified_fuzzy":22},"total_outbound_references":33},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.05263."}