{"as_of":"2026-08-09T06:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e70c11ba693b3299c9469b5902e1b2877cc58886c8879277b646b5a2ceb356a8","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T05:29:38.352508Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"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/2502.08353/citation-record","integrity":"/paper/2502.08353/integrity","json":"/paper/2502.08353/citation-record.json","paper":"/paper/2502.08353"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T05:29:38.768616Z","title":"Compositional fairness constraints for graph embeddings","venue":null,"work_id":"2b2b80a5-ca1d-4def-a7df-fbba5c195216","year":2019},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.221535Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:3e220d29ef8caa11f2bf33dba80e068a1da13e4c950de31f3195dc1cbbd3680b","observation_id":"9aaf130f-889d-47b2-8a5d-c3b41e10da1e","resolution":{"observed_at":"2026-08-08T05:29:38.773673Z","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":"2212.12040","last_updated":"2022-12-22T21:20:43Z","snapshot_observed_at":"2026-07-06T14:34:15.774963Z","submitted_at":"2022-12-22T21:20:43Z","title":"Graph Learning with Localized Neighborhood Fairness","version":1},"cited_work":{"arxiv_id":"2212.12040","doi":null,"metadata_source":"pith","pith_arxiv_id":"2212.12040","snapshot_observed_at":"2026-08-08T05:29:38.538822Z","title":"Graph Learning with Localized Neighborhood Fairness","venue":"cs.SI","work_id":"d2e75916-1730-42d6-a596-619dac7b5639","year":2022},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.237751Z"},"links":{"cited_paper":"/paper/2212.12040","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:2868b9f981e421e4afa9cfaddf6b9a1d76adc082dd662a85e69c533c4e54b7c8","observation_id":"1d1d2407-b894-4ee4-95d1-21ef94e17122","resolution":{"observed_at":"2026-08-08T05:29:38.543774Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-08T05:29:38.719460Z","title":"Networks in biology","venue":null,"work_id":"483eb929-3f62-4b7e-8dfe-f593bb7e0a1b","year":2019},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.249553Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:07d8919e1353b372d4563f72d3eae1d05b2b8d98d1942ce89694a9b4d3121151","observation_id":"5b2c4000-945a-4126-b371-7405a93ed973","resolution":{"observed_at":"2026-08-08T05:29:38.723127Z","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":"2407.12068","last_updated":"2024-07-28T16:44:21Z","snapshot_observed_at":"2026-07-06T18:47:25.751118Z","submitted_at":"2024-07-16T09:05:31Z","title":"Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12068","snapshot_observed_at":"2026-08-08T05:29:38.253612Z","title":"Learning on graphs with large language models (llms): A deep dive into model robustness","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.253612Z"},"links":{"cited_paper":"/paper/2407.12068","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:6deb0930a5c0c44a9cc79ab8814dd1d3faf3c61bea1ba870e080c9b568cfc991","observation_id":"fa7a1c90-0270-4b58-a76a-42f3af4ae5de","resolution":{"observed_at":"2026-08-08T05:29:38.253612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-08T05:29:38.257914Z","title":"[Guo et al., 2025] Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shi- rong Ma, Peiyi Wang, Xiao Bi, et al","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.257914Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:bc71dd7a79035fa7e0154f4152fd47c841ccfc30f2b77399534210f2e6ae7178","observation_id":"9847672f-038b-4f05-b7d9-15ea76f10011","resolution":{"observed_at":"2026-08-08T05:29:38.257914Z","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":"2026-08-08T05:29:38.708490Z","title":null,"venue":null,"work_id":"7c1d2d91-9571-407b-8860-b301a8b2dfbc","year":2022},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.264927Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:5f020a2398dccd7fcf0d43c66a2f1b84c9c304c2d792370cfe9fdca7c43aa6b2","observation_id":"02236e4a-0838-4e65-8d20-17e75008cdb8","resolution":{"observed_at":"2026-08-08T05:29:38.712205Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-08T05:29:38.696170Z","title":"Verbalized graph representation learn- ing: A fully interpretable graph model based on large lan- guage models throughout the entire process","venue":null,"work_id":"4c0b74c0-502e-4db2-84c9-ef8d9893e4d7","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.268104Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:db6e5785940780638653fb93d0f0d86df994a21091c389eb89bc115eaa38c35f","observation_id":"d8bfd7b3-6fa3-4947-ad8a-e9e31cfd410f","resolution":{"observed_at":"2026-08-08T05:29:38.700387Z","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":"2026-08-08T05:29:38.684295Z","title":"Could graph neural networks learn better molecular representa- tion for drug discovery? a comparison study of descriptor- based and graph-based models","venue":null,"work_id":"099bd986-63ea-49e8-b44a-17969c24aa24","year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.271085Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:53b7540d990ef628becd418eb6811a20d48f8ac3f9ab5f7b9ae9d52519e0574b","observation_id":"b519d28c-2e8a-4e82-8aa6-a0ab9c720625","resolution":{"observed_at":"2026-08-08T05:29:38.688262Z","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":"2026-08-08T05:29:38.672759Z","title":"Llm-empowered few-shot node classifica- tion on incomplete graphs with real node degrees,","venue":null,"work_id":"ded47d1b-c114-4160-a11b-e529c1c0aac4","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.277876Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:3cab52f23e693551c6ba843e156420cf786d51a28dc3210cac91ee9238ad96bd","observation_id":"46bb64e3-1b0f-4af7-a3d0-b4b09ae1c918","resolution":{"observed_at":"2026-08-08T05:29:38.676920Z","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":"2308.05374","last_updated":"2024-03-21T00:21:14Z","snapshot_observed_at":"2026-08-02T17:09:20.540788Z","submitted_at":"2023-08-10T06:43:44Z","title":"Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.05374","snapshot_observed_at":"2026-08-08T05:29:38.281501Z","title":"[Liu et al., 2023] Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.281501Z"},"links":{"cited_paper":"/paper/2308.05374","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:6450c808c1604dbe0c317760062b32ba8389a12c683aba62714aa295ea3446fd","observation_id":"72086012-d31f-4e57-8ad0-4a6ff1467ce2","resolution":{"observed_at":"2026-08-08T05:29:38.281501Z","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":"2026-08-08T05:29:38.662332Z","title":"Learning to drop: Robust graph neural network via topological denoising","venue":null,"work_id":"07cf2f02-1b14-43ff-a081-b04c293beb8b","year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.285200Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:264ccfb01a40de7bc77c7fb286b62e5ce0526dd3d5040f09872ab649b5ef888c","observation_id":"b6afb653-27c5-49ea-9f23-ed88c71f1b1a","resolution":{"observed_at":"2026-08-08T05:29:38.666046Z","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":"2304.13712","last_updated":"2023-04-27T17:56:11Z","snapshot_observed_at":"2026-07-06T15:20:25.388057Z","submitted_at":"2023-04-26T17:52:30Z","title":"Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.13712","snapshot_observed_at":"2026-08-08T05:29:38.289100Z","title":"Large language models in cybersecurity: State-of-the-art","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.289100Z"},"links":{"cited_paper":"/paper/2304.13712","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:cd9168942f4b325435fd2e2c0a70030e90561a84e1d702a9a480bb53586e7010","observation_id":"2929ab7b-5a14-4bed-8c8e-7c8407669edb","resolution":{"observed_at":"2026-08-08T05:29:38.289100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07511","last_updated":"2024-10-14T02:50:55Z","snapshot_observed_at":"2026-07-06T19:30:52.402150Z","submitted_at":"2024-10-10T01:01:10Z","title":"CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype Associations","version":2},"cited_work":{"arxiv_id":"2410.07511","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.07511","snapshot_observed_at":"2026-08-08T05:29:38.452657Z","title":"CSGDN: Contrastive Signed Graph Diffusion Network for Predicting Crop Gene-phenotype Associations","venue":"cs.LG","work_id":"e70c1a65-9bb9-4f88-9b78-682daa646f0d","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.293246Z"},"links":{"cited_paper":"/paper/2410.07511","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:55973635f99e22b9226f94207afde213e1cb2c765d956388ae4eecc31aaaf033","observation_id":"f04f360d-0920-487c-8d50-1b21d7f7a501","resolution":{"observed_at":"2026-08-08T05:29:38.458921Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-08T05:29:38.652031Z","title":"Learning transferable visual models from nat- ural language supervision","venue":null,"work_id":"52a10160-44e7-4d50-94be-cdfbb2eceac1","year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.297810Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:8c3b099ee39407d279921cf5db3fd8cadf718bf7d71135c09700f832b4510e06","observation_id":"f4b81496-13dc-4d16-b4d2-22ca14672f05","resolution":{"observed_at":"2026-08-08T05:29:38.655507Z","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":"2026-08-08T05:29:38.640931Z","title":"Fairdrop: Biased edge dropout for enhancing fairness in graph representa- tion learning","venue":null,"work_id":"38ae37ed-8844-46bb-806c-667340e99aa3","year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.301438Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:158a522036a45b969fc5b2ea36d396d3e5fe53b2e3ab29c122a306cad73cded3","observation_id":"81db1826-cea3-46b6-b47c-41e489847c16","resolution":{"observed_at":"2026-08-08T05:29:38.644573Z","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":"2111.15367","last_updated":"2022-04-26T17:59:28Z","snapshot_observed_at":"2026-08-03T15:09:14.521480Z","submitted_at":"2021-11-27T02:52:10Z","title":"A Review on Graph Neural Network Methods in Financial Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.15367","snapshot_observed_at":"2026-08-08T05:29:38.304935Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.304935Z"},"links":{"cited_paper":"/paper/2111.15367","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:a51319f931172b6492bb7bf059886abe22a1d71be4ac789ba34851dbe222b0ec","observation_id":"b327eeab-00f0-4702-8a95-2297eca0a0c6","resolution":{"observed_at":"2026-08-08T05:29:38.304935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10835","last_updated":"2024-01-25T03:50:15Z","snapshot_observed_at":"2026-07-06T16:08:37.443746Z","submitted_at":"2023-08-21T16:35:19Z","title":"Enhancing Recommender Systems with Large Language Model Reasoning Graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.10835","snapshot_observed_at":"2026-08-08T05:29:38.308691Z","title":"Enhancing rec- ommender systems with large language model reasoning graphs","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.308691Z"},"links":{"cited_paper":"/paper/2308.10835","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:e4a8cc3bef01604f3d9b26bd95121cdc63080c4216e662f5e03452369fc25faf","observation_id":"0b8425a8-b22a-4229-af49-f04e95072e0c","resolution":{"observed_at":"2026-08-08T05:29:38.308691Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-08T05:29:38.312355Z","title":"Chi, Quoc V","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.312355Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:ec014681308ec0bb4fafc1072ad99e65bcf7ce38c36fc5ac30e64084facb843b","observation_id":"98cb18dc-5511-4012-9215-aaf309447f9b","resolution":{"observed_at":"2026-08-08T05:29:38.312355Z","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":"2026-08-08T05:29:38.316157Z","title":"A com- prehensive survey on graph neural networks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.316157Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:3cfceed1785c03e27ac726e449245b357cb874af0fa31a8747db4d0ae2fa00ab","observation_id":"fbf5901f-52b0-4875-9aff-75d5fda60af9","resolution":{"observed_at":"2026-08-08T05:29:38.316157Z","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":"2026-08-08T05:29:38.319454Z","title":"Graph learning: A survey","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.319454Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:014ad4f0fedb5c58497fd1e8f6e712f0113b8b6c5ab12de8ba7d483ec6e16285","observation_id":"79250cdf-94d5-4203-a17b-3839eeed13f4","resolution":{"observed_at":"2026-08-08T05:29:38.319454Z","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":"2026-08-08T05:29:38.612640Z","title":"Review of graph-based hazardous event detection meth- ods for autonomous driving systems","venue":null,"work_id":"29956216-0cae-464a-9c90-645f4c516a6a","year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.322693Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:08db5e64b662e6195e14a0b92dfffdc858663638c862cfcc6b71feda3d4d4211","observation_id":"48a5b7f8-d027-44e8-a958-e1aed6e64e68","resolution":{"observed_at":"2026-08-08T05:29:38.617191Z","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":"2026-08-08T05:29:38.599421Z","title":"Graphformers: Gnn- nested transformers for representation learning on textual graph","venue":null,"work_id":"5913da91-cb76-4998-9e1c-17f82c27cbe5","year":2021},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.327101Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:095cef49da668cf0c2aad0b2ef5720cfc58811dcceeeb06b48123cf10d0aa002","observation_id":"2faf9863-7754-46a7-a84f-8cfd23462175","resolution":{"observed_at":"2026-08-08T05:29:38.604128Z","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":"2309.17421","last_updated":"2023-10-11T05:07:37Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-29T17:34:51Z","title":"The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17421","snapshot_observed_at":"2026-08-08T05:29:38.331481Z","title":"The dawn of lmms: Preliminary explorations with gpt-4v (ision)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.331481Z"},"links":{"cited_paper":"/paper/2309.17421","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:594e6d88318b457f399f5bae9da6cc0cfddb4a1cde9d84d3bdae2475e28585f5","observation_id":"3cf14cfe-dc3b-472c-936d-65501e5d03f7","resolution":{"observed_at":"2026-08-08T05:29:38.331481Z","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":"2026-08-08T05:29:38.586875Z","title":"Fairsin: Achieving fairness in graph neural networks through sensitive information neutralization","venue":null,"work_id":"71bb74c0-782a-42ea-9742-f6c4200d0a70","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.335625Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:4585f147901297eaa10c82a422b57756f3972b11e7a7fed99c580f93c9a76932","observation_id":"d758e68c-5cf0-4203-b5c1-eef90c90e599","resolution":{"observed_at":"2026-08-08T05:29:38.591826Z","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":"2205.07424","last_updated":"2024-02-21T09:54:52Z","snapshot_observed_at":"2026-07-06T13:10:13.191724Z","submitted_at":"2022-05-16T02:21:09Z","title":"Trustworthy Graph Neural Networks: Aspects, Methods and Trends","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.07424","snapshot_observed_at":"2026-08-08T05:29:38.339147Z","title":"Drope- dge not foolproof: Effective augmentation method for signed graph neural networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.339147Z"},"links":{"cited_paper":"/paper/2205.07424","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:9bfc0c297e064c35d10375a7a8f8c61c7151fcb84be974664175ce89f740b23e","observation_id":"27475f30-36f0-4b83-aa06-042849e733d9","resolution":{"observed_at":"2026-08-08T05:29:38.339147Z","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":"2026-08-08T05:29:38.574931Z","title":"Rsgnn: A model-agnostic ap- proach for enhancing the robustness of signed graph neu- ral networks","venue":null,"work_id":"28569460-d5ba-4da8-bd4a-eeeec3158dfb","year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.343236Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:e326fb2ce9d9c80e50d6e6ddcebb51b4675edf07901806ffc37b3e1f0b6de8d3","observation_id":"3b475719-b254-4edc-b99d-7daee95f44fc","resolution":{"observed_at":"2026-08-08T05:29:38.578933Z","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":"2408.08685","last_updated":"2024-12-24T07:08:45Z","snapshot_observed_at":"2026-08-06T09:11:01.400113Z","submitted_at":"2024-08-16T11:58:34Z","title":"Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08685","snapshot_observed_at":"2026-08-08T05:29:38.346112Z","title":"[Zhang et al., 2024c] Zhongjian Zhang, Xiao Wang, Huichi Zhou, Yue Yu, Mengmei Zhang, Cheng Yang, and Chuan Shi","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.346112Z"},"links":{"cited_paper":"/paper/2408.08685","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:b47d027d72dadb7d62134e68e7f10b62171914d8d25871408cd70122da4c783a","observation_id":"98371fc0-dd1e-4710-998c-7baf31809062","resolution":{"observed_at":"2026-08-08T05:29:38.346112Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-06T23:27:24.356320Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-08T05:29:38.349514Z","title":"A survey of large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.349514Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:1ab853c0e83ffbd95882a4bc7244c7fbd3089fd2436328786775ab715e60fbb1","observation_id":"b215093e-0539-46ab-944b-f219314cd1c1","resolution":{"observed_at":"2026-08-08T05:29:38.349514Z","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":"2026-08-08T05:29:38.563820Z","title":"Fair graph representation learning via sensitive attribute disentanglement","venue":null,"work_id":"6fefbe39-7990-4efe-bdde-2cfb569bf463","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.352508Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:a2b342de989e165acd51adfd773494c1f1c5fb1494226a935d0de67a19acb750","observation_id":"3fd66ce2-b1cc-4402-a4b9-6d61d357edfa","resolution":{"observed_at":"2026-08-08T05:29:38.567617Z","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":"2026-08-08T05:29:38.755986Z","title":"Language models are few-shot learners","venue":null,"work_id":"6d0d20fa-1b97-4e58-b243-c24c35ea0152","year":2020},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.225564Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:f803b641770e5785a9352e06127f6c76136aab14df426d3ae27c234cf6226483","observation_id":"30f4cefc-5e9b-4efd-a73f-5c14e5d2e355","resolution":{"observed_at":"2026-08-08T05:29:38.760499Z","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":"2310.05845","last_updated":"2023-10-09T16:42:00Z","snapshot_observed_at":"2026-08-05T15:33:31.680807Z","submitted_at":"2023-10-09T16:42:00Z","title":"GraphLLM: Boosting Graph Reasoning Ability of Large Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05845","snapshot_observed_at":"2026-08-08T05:29:38.229288Z","title":"Graphllm: Boosting graph reasoning ability of large language model","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.229288Z"},"links":{"cited_paper":"/paper/2310.05845","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:6fb889eda7cbd62163afa2859a67fdde8cb35e259039449827dfc45d377550e1","observation_id":"44ba0182-0b6b-42d3-81ee-4a16ce84739f","resolution":{"observed_at":"2026-08-08T05:29:38.229288Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12399","last_updated":"2024-04-24T08:48:13Z","snapshot_observed_at":"2026-08-04T04:27:25.092446Z","submitted_at":"2023-11-21T07:22:48Z","title":"A Survey of Graph Meets Large Language Model: Progress and Future Directions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12399","snapshot_observed_at":"2026-08-08T05:29:38.274164Z","title":"A survey of graph meets large language model: Progress and future directions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.274164Z"},"links":{"cited_paper":"/paper/2311.12399","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:41c0443e973c0283e6c6c04875172af50368c3dd3c5445a1f4c107667c69f055","observation_id":"0f6a22d4-fcd0-4f37-b020-0bb451024868","resolution":{"observed_at":"2026-08-08T05:29:38.274164Z","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":"2026-08-08T05:29:38.730714Z","title":"Exploring the potential of large language models (llms) in learning on graphs","venue":null,"work_id":"501e3af4-664e-498b-874b-693d924cc680","year":2024},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.241757Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:721c49c3920e4e21bd61cc7f971a804bd2f0f6112546003fc48012af1d64ad89","observation_id":"d4a16f1c-5d6a-45bf-8609-9568e0ce9c78","resolution":{"observed_at":"2026-08-08T05:29:38.735096Z","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":"2026-08-08T05:29:38.743606Z","title":"Iterative deep graph learning for graph neural net- works: Better and robust node embeddings","venue":null,"work_id":"4e5bffa7-ab77-4711-a14a-d9c07d44bc9b","year":2020},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.233440Z"},"links":{"citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:8b858efaea6cf405c0a26a28979914c4f9b9e006d61bb567853d6b495a8f3ea7","observation_id":"170915b7-5df3-4f8a-b5fd-fc7355b0e335","resolution":{"observed_at":"2026-08-08T05:29:38.747758Z","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":"2301.00234","last_updated":"2024-10-05T11:47:02Z","snapshot_observed_at":"2026-07-06T14:36:25.690733Z","submitted_at":"2022-12-31T15:57:09Z","title":"A Survey on In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00234","snapshot_observed_at":"2026-08-08T05:29:38.245624Z","title":"A survey for in-context learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.245624Z"},"links":{"cited_paper":"/paper/2301.00234","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:0accef949b79c3ed79ba297dda46570da01ca956de263ce01572a5d4ed868543","observation_id":"553a8142-15f5-48d4-9fa2-357d592adb26","resolution":{"observed_at":"2026-08-08T05:29:38.245624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.19523","last_updated":"2024-03-07T02:45:36Z","snapshot_observed_at":"2026-07-06T15:35:45.200564Z","submitted_at":"2023-05-31T03:18:03Z","title":"Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.19523","snapshot_observed_at":"2026-08-08T05:29:38.261408Z","title":"Harnessing explanations: Llm-to-lm interpreter for en- hanced text-attributed graph representation learning.arXiv preprint arXiv:2305.19523,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-08T05:29:38.261408Z"},"links":{"cited_paper":"/paper/2305.19523","citing_paper":"/paper/2502.08353"},"observation_digest":"sha256:b7a1ebcf4cd7b13481d54d799c3244bbc7f2be099007b7d93389419025b973ec","observation_id":"946b5cbb-3a0c-4c42-9645-d1aeecc0cb2c","resolution":{"observed_at":"2026-08-08T05:29:38.261408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.08353","last_updated":"2025-02-12T12:28:39Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T05:33:37.475228Z","submitted_at":"2025-02-12T12:28:39Z","title":"Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":16},"total_outbound_references":36},"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 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2502.08353."}