{"as_of":"2026-08-14T20:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:abcbb3d9d0e34ce93ebc4666e55aa9471882d499a0a3f78c7e1787eee34eb201","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T05:23:48.050833Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T00:50:39.622302Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T16:09:57.525108Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"cited_work":{"arxiv_id":"2412.17609","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.17609","snapshot_observed_at":"2026-07-04T16:09:57.525108Z","title":"URL https://openreview.net/forum?id=mSoDRZXsqj","venue":null,"work_id":"6f28d9d4-46e3-4d4c-b0e5-0502d0e33864","year":null},"citing_paper":{"arxiv_id":"2605.04834","last_updated":"2026-05-06T12:30:50Z","snapshot_observed_at":"2026-08-11T13:35:42.220145Z","submitted_at":"2026-05-06T12:30:50Z","title":"Bridging Input Feature Spaces Towards Graph Foundation Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T17:18:21.259797Z"},"links":{"cited_paper":"/paper/2412.17609","citing_paper":"/paper/2605.04834"},"observation_digest":"sha256:bf26c2a76d2d38931ae0f975db41823feca939435196a8c9d6efb5d1ab3fd2b9","observation_id":"68fc3f46-578b-49bc-89f3-895a229fe18f","resolution":{"observed_at":"2026-05-11T17:41:08.762109Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"cited_work":{"arxiv_id":"2412.17609","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.17609","snapshot_observed_at":"2026-07-04T16:09:57.525108Z","title":"URL https://openreview.net/forum?id=mSoDRZXsqj","venue":null,"work_id":"6f28d9d4-46e3-4d4c-b0e5-0502d0e33864","year":null},"citing_paper":{"arxiv_id":"2606.24509","last_updated":"2026-06-23T12:41:43Z","snapshot_observed_at":"2026-08-08T03:35:19.936330Z","submitted_at":"2026-06-23T12:41:43Z","title":"A Fair Evaluation of Graph Foundation Models for Node Property Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-26T00:50:39.622302Z"},"links":{"cited_paper":"/paper/2412.17609","citing_paper":"/paper/2606.24509"},"observation_digest":"sha256:468a42e0db387061a2163eb21aaf8c03954549b12ca7dbd8b378c6af8a27c3ed","observation_id":"d0a57732-d3d1-49bb-acbf-7351c2c5be14","resolution":{"observed_at":"2026-07-04T16:09:57.527492Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.17609/citation-record","integrity":"/paper/2412.17609/integrity","json":"/paper/2412.17609/citation-record.json","paper":"/paper/2412.17609"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1905.11460","last_updated":"2020-08-12T01:18:12Z","snapshot_observed_at":"2026-08-14T16:25:39.484840Z","submitted_at":"2019-05-27T19:16:52Z","title":"Incidence Networks for Geometric Deep Learning","version":4},"cited_work":{"arxiv_id":"1905.11460","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.11460","snapshot_observed_at":"2026-08-11T05:23:48.233015Z","title":"Incidence Networks for Geometric Deep Learning","venue":"cs.LG","work_id":"67e6becb-4bbb-46e7-9faa-440dc62fc99d","year":2019},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:47.947064Z"},"links":{"cited_paper":"/paper/1905.11460","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:2c810c6215f4725712dde67e444515bce443247a901574b2764bae7c4c205bfb","observation_id":"cd53cc58-6627-45e5-bfae-5737c4c50c9c","resolution":{"observed_at":"2026-08-11T05:23:48.296558Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T05:23:48.317773Z","title":null,"venue":null,"work_id":"6f303e40-6690-4159-af91-faa2f4183a66","year":2022},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.046619Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:3e1215c9b5a3af6690cd3f945b0414a6b017df03a0b8189fcdd1d42ac7c5cdf9","observation_id":"b251d7a9-98fd-4c41-8938-902529e92bf0","resolution":{"observed_at":"2026-08-11T05:23:48.321120Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T05:23:48.470022Z","title":"These rep- resentations are linearly transformed by component (d), and then summed along with the encoding of the explicit, original node features in output from component (e)","venue":null,"work_id":"4459ac7a-fc3d-4e6e-8005-e5ee415b536f","year":2024},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.038834Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:b1e38cc420a3874fc86ac72fb4f5755d14abf4bb956771c5be78ea178c8474a4","observation_id":"85c2460c-990a-441e-b51e-d3c6720168f8","resolution":{"observed_at":"2026-08-11T05:23:48.504186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.13934","last_updated":"2024-09-22T03:47:19Z","snapshot_observed_at":"2026-08-13T00:01:53.459790Z","submitted_at":"2024-05-22T19:06:39Z","title":"Text-Free Multi-domain Graph Pre-training: Toward Graph Foundation Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.13934","snapshot_observed_at":"2026-08-11T05:23:48.030264Z","title":"arXiv:2405.13934 [cs]","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.030264Z"},"links":{"cited_paper":"/paper/2405.13934","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:d9645256a263b4b2a220dd4165ec485ba555ec83614ce8e20b80c4ba32073dc8","observation_id":"251fc98d-2c88-4f8d-ad7c-fc9e40fbe42e","resolution":{"observed_at":"2026-08-11T05:23:48.030264Z","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":"2026-08-11T05:23:48.513544Z","title":"We use the same ‘mae + cosine similarity’ loss (Cant¨ urk et al., 2024)","venue":null,"work_id":"9a6453f7-d057-4199-8528-0e395a0e9b29","year":2024},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.034834Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:8f15ad3111dec25320fff2c07aee0c60013a67b3a44d15098fbfa0468e27465d","observation_id":"a3816ab5-f8eb-4e8c-bed0-1fe3e1cfb915","resolution":{"observed_at":"2026-08-11T05:23:48.517959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T05:23:48.305392Z","title":"in-dataset","venue":null,"work_id":"91bec086-506c-4e22-8790-42b7543dfaa3","year":2024},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.050833Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:68cf23e4091aa9bae668c3127e42968ffacb912aa3da81bf171b0eb90b090a2f","observation_id":"5c598726-704f-4f78-a35a-778ac576a2ad","resolution":{"observed_at":"2026-08-11T05:23:48.308886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T05:23:48.328783Z","title":"In accordance with Cant¨ urk et al","venue":null,"work_id":"9486b153-ecb9-4d29-8c5f-e2a594017c9d","year":2024},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":128,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.042843Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:8976ecfbbc56a287efc3ab42c2ec72b684af396d648e6a65a202292fb6e07d66","observation_id":"ac2cc943-8d69-41b5-9b56-a53f1f8015a1","resolution":{"observed_at":"2026-08-11T05:23:48.399645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00149","last_updated":"2024-07-12T23:01:32Z","snapshot_observed_at":"2026-08-14T03:13:16.635373Z","submitted_at":"2023-09-29T21:15:26Z","title":"One for All: Towards Training One Graph Model for All Classification Tasks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00149","snapshot_observed_at":"2026-08-11T05:23:48.025336Z","title":"One for All: Towards Training One Graph Model for All Classification Tasks, December 2023a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.025336Z"},"links":{"cited_paper":"/paper/2310.00149","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:eb73b292b4a4c2804994a8103216b8389c7270bdf6f893ea95a30d592fa4fe75","observation_id":"60b3964c-d267-465d-b708-d4f47381c794","resolution":{"observed_at":"2026-08-11T05:23:48.025336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.07553","last_updated":"2018-04-24T08:19:32Z","snapshot_observed_at":"2026-08-14T20:11:44.023605Z","submitted_at":"2017-11-20T21:28:40Z","title":"Residual Gated Graph ConvNets","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.07553","snapshot_observed_at":"2026-08-11T05:23:48.009572Z","title":"Semih Cant¨ urk, Renming Liu, Olivier Lapointe-Gagn´ e, Vincent L´ etourneau, Guy Wolf, Dominique Beaini, and Ladislav Ramp´ aˇ sek","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.009572Z"},"links":{"cited_paper":"/paper/1711.07553","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:e61cc5e9287794479e4ceb262d28f6df884581672cf7a693b3d3bf71114f2d77","observation_id":"afe06e31-0cf0-4566-8f9a-56cff09a9548","resolution":{"observed_at":"2026-08-11T05:23:48.009572Z","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":"2026-08-11T05:23:48.526640Z","title":null,"venue":null,"work_id":"449a0f92-1334-4c39-a38a-bc12ec8c18ca","year":1905},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.001151Z"},"links":{"citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:4b5d88ca8860c86a37d2cc31d81f1f308e8d8228c9ae2925330a946ff3104999","observation_id":"0afd902a-f44b-4bb3-aba8-db360e21097d","resolution":{"observed_at":"2026-08-11T05:23:48.530990Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.00982","last_updated":"2022-12-28T04:57:24Z","snapshot_observed_at":"2026-08-13T23:22:42.355874Z","submitted_at":"2020-03-02T15:58:46Z","title":"Benchmarking Graph Neural Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.00982","snapshot_observed_at":"2026-08-11T05:23:48.018034Z","title":"Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, and Xavier Bres- son","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.018034Z"},"links":{"cited_paper":"/paper/2003.00982","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:0bb91a2216b0023ac11e937b45734165928bd31fa70a0a887893bbcf6a0f0e1a","observation_id":"ce63fd51-d703-4d56-b8cc-8876e7c4bce5","resolution":{"observed_at":"2026-08-11T05:23:48.018034Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.12600","last_updated":"2023-05-21T23:16:30Z","snapshot_observed_at":"2026-08-14T19:58:11.584962Z","submitted_at":"2023-05-21T23:16:30Z","title":"PRODIGY: Enabling In-context Learning Over Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.12600","snapshot_observed_at":"2026-08-11T05:23:48.021354Z","title":"arXiv:2305.12600 [cs]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-11T05:23:48.021354Z"},"links":{"cited_paper":"/paper/2305.12600","citing_paper":"/paper/2412.17609"},"observation_digest":"sha256:a3c3c7f156ee515054b284dcdd862a217e58606456b5c07099fe05734d7c3655","observation_id":"62e823d4-89da-4a91-b6cd-fb038210e18e","resolution":{"observed_at":"2026-08-11T05:23:48.021354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.17609","last_updated":"2024-12-23T14:28:56Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T03:13:30.204779Z","submitted_at":"2024-12-23T14:28:56Z","title":"Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":1,"verified_fuzzy":4},"total_outbound_references":12},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2412.17609."}