{"as_of":"2026-08-10T06:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:89851ea91b5b662c633fd15e45048efb3a602300775425a475405134d4f202e1","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T23:54:01.046052Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2509.06286/citation-record","integrity":"/paper/2509.06286/integrity","json":"/paper/2509.06286/citation-record.json","paper":"/paper/2509.06286"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T23:54:03.540801Z","title":"Graph neural networks in recommender systems: a survey,","venue":null,"work_id":"2e043762-9a33-4047-a48c-dc314025b454","year":2022},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T23:53:59.789165Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:82ed1af234a2025c40d253cfb5644012b0f0b144cd181dc85315f015b6e118f0","observation_id":"5fa53694-1edc-4dcb-ab4e-bc6554a655ca","resolution":{"observed_at":"2026-08-04T23:54:03.568832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:03.468701Z","title":"Graph neural networks for recommender system,","venue":null,"work_id":"135a7e96-1570-41cd-87dd-220b44750e11","year":2022},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T23:53:59.823228Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:3e01d7e6b22cc9ff116f1e4a48b52489b36e91c97a35d2635ad3ca683f18d034","observation_id":"124ab0b7-943c-4c8c-bf95-b14f662d15c5","resolution":{"observed_at":"2026-08-04T23:54:03.504768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:03.351336Z","title":"Neural graph collaborative filtering,","venue":null,"work_id":"7bbd4b7d-039d-443f-8507-568e32ffa3a2","year":2019},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T23:53:59.893195Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:a6143d9bf22994599a7e43f5f545fe98fe109e54e3841c4184ccdfee90103469","observation_id":"f2c999bb-af7b-4b1a-9447-f53705a3417b","resolution":{"observed_at":"2026-08-04T23:54:03.396637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:03.225129Z","title":"Graph convolutional neural networks for web-scale recommender systems,","venue":null,"work_id":"7a193c03-e8f3-4d63-ba6e-c88fedcf9998","year":2018},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T23:53:59.928932Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:983a7eab45510ed80ce5535f1fb352c1114052771b461e52131aeaab0cf7bfa4","observation_id":"34b77462-06a2-4c77-ad1f-c04378fb28de","resolution":{"observed_at":"2026-08-04T23:54:03.283521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:03.165695Z","title":"Lightgcn: Simplifying and powering graph convolution network for recommenda- tion,","venue":null,"work_id":"2ab44ca7-9ca3-4df2-a527-91ebfe749a07","year":2020},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T23:53:59.974109Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:f33dc1b72b435217982465db035f00da4644a1f6fcd725b4a13bd490ca409f2e","observation_id":"f412a749-cd9b-4b38-a697-59b0f020e363","resolution":{"observed_at":"2026-08-04T23:54:03.192769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1205.2618","last_updated":"2012-05-09T18:25:09Z","snapshot_observed_at":"2026-07-06T02:47:58.266745Z","submitted_at":"2012-05-09T18:25:09Z","title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1205.2618","snapshot_observed_at":"2026-08-04T23:54:00.017754Z","title":"Bpr: Bayesian personalized ranking from implicit feedback,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.017754Z"},"links":{"cited_paper":"/paper/1205.2618","citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:95b079aaabd224a2ac250b7fe520df189ed869769aaada424054bf0bd9e5c72f","observation_id":"aeafdf8f-6c76-4560-ae3c-0b3deeb1ec72","resolution":{"observed_at":"2026-08-04T23:54:00.017754Z","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":"2026-08-04T23:54:03.053443Z","title":"Large language models meet collaborative filtering: An efficient all-round llm- based recommender system,","venue":null,"work_id":"a66a214c-4eab-4446-8b90-edba811b225d","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.081030Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:87fc50970325a05330a9db437c421bc104a2373d4a6a6b6df3261f3868e407c3","observation_id":"a3aa9181-560e-4b6b-9fa9-2fdd8c4242f7","resolution":{"observed_at":"2026-08-04T23:54:03.095943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:00.138932Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.138932Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:86cf74070a7ea80e2b4aee3dc7f0c6066cca808b8d664a29b2e7d2b340ae805d","observation_id":"513f97ab-e834-4c2b-a82d-e39506ca13b3","resolution":{"observed_at":"2026-08-04T23:54:00.138932Z","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":"2026-08-04T23:54:02.975043Z","title":"Unifying prediction and explanation in time-series transformers via shapley-based pretraining,","venue":null,"work_id":"e829130a-3ba2-4e1e-a62e-139871cc7f07","year":2025},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.175079Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:3e7a6770a8ea6254d7448c0804168786fb25ddfbf8e84015db673089dad6b800","observation_id":"0f94c85d-6caa-4b0b-b1b8-7bf01aef10e2","resolution":{"observed_at":"2026-08-04T23:54:03.010320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.872951Z","title":"Selective layer fine-tuning for federated health- care nlp: A cost-efficient approach,","venue":null,"work_id":"9f409168-d03b-48f4-b0a4-673156dcd089","year":2025},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.264765Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:40e73173c1ba33e0faab4e904e52a6155386baf2a2fbf6e4889c142b121d8118","observation_id":"784e2065-304e-4d1e-bc75-8a3c117eeddc","resolution":{"observed_at":"2026-08-04T23:54:02.911504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.789378Z","title":"S3-rec: Self-supervised learning for sequential recom- mendation with mutual information maximization,","venue":null,"work_id":"7f8dfdba-d15a-4243-a791-5c03d96b1916","year":2020},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.293334Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:feeca07dd81cb30edb0c70aea3eaa92c2043eb501764b95dbd601dbda776287c","observation_id":"748dc687-4ca3-4b49-810e-2747266bcf18","resolution":{"observed_at":"2026-08-04T23:54:02.822007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.729306Z","title":"Contrastive learning for sequential recommendation,","venue":null,"work_id":"39c2a8a0-6ee3-4059-85d4-5d3c487676e1","year":2022},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.325956Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:5da241bb997de3c53071f6ec4a26df173f508d608817ed349ee4390c40bcfaca","observation_id":"546c0356-cd9b-42c0-9065-18881f238e19","resolution":{"observed_at":"2026-08-04T23:54:02.758554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.619236Z","title":"Simgcl: graph con- trastive learning by finding homophily in heterophily,","venue":null,"work_id":"29a4444a-88c6-46c0-92a7-f55d9e3ab755","year":2089},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.337068Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:3c9904daabbc87caa8b334010bfef146dada6c78bf3aa7310d7b96702a73575b","observation_id":"b5576ead-664b-4373-9f2e-7186e4f36872","resolution":{"observed_at":"2026-08-04T23:54:02.685492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.551758Z","title":"Xsimgcl: Towards extremely simple graph contrastive learning for recommenda- tion,","venue":null,"work_id":"ab5c6c9b-6bbf-4ac9-9323-6f2f09485f8f","year":2023},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.367201Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:383769ae2dad7fbac38f4b8c9072a54f2bd8f2c2a0abefd100164cfd4fa90533","observation_id":"87b54d39-4d30-4178-b049-b41ea56fa786","resolution":{"observed_at":"2026-08-04T23:54:02.580965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.461249Z","title":"Joint deep modeling of users and items using reviews for recommendation,","venue":null,"work_id":"6d0f4fe9-dfb8-435d-9b09-0deeddf4ad0b","year":2017},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.406308Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:507fbf1ee635beed777e9e1b72f27e213590b1f821799493db84f19ebfae3d1d","observation_id":"d4b707b8-f1e4-4709-b17f-e997069e96e2","resolution":{"observed_at":"2026-08-04T23:54:02.516762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.341245Z","title":"Neural attentional rating regression with review-level explanations,","venue":null,"work_id":"c25da1e2-9076-4d27-bda0-3c4beff74315","year":2018},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.467322Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:49f9c1d2b11abb2946d197ef1accee5e1ff1eb727a2c2417d01fdd537ec43d81","observation_id":"0820a41c-cc67-465f-9c5c-32b6c15b47c0","resolution":{"observed_at":"2026-08-04T23:54:02.375407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.05576","last_updated":"2019-07-12T04:50:33Z","snapshot_observed_at":"2026-08-01T22:21:53.414040Z","submitted_at":"2019-07-12T04:50:33Z","title":"Neural News Recommendation with Attentive Multi-View Learning","version":1},"cited_work":{"arxiv_id":"1907.05576","doi":null,"metadata_source":"pith","pith_arxiv_id":"1907.05576","snapshot_observed_at":"2026-08-04T23:54:01.297652Z","title":"Neural News Recommendation with Attentive Multi-View Learning","venue":"cs.CL","work_id":"dbb53ab4-d8e2-4bc8-8d60-d8377ba561df","year":2019},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.496231Z"},"links":{"cited_paper":"/paper/1907.05576","citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:55805b14dd0f35c8140bfbb8cda1a358c532b58d9a08c2a5b393450dc6e67148","observation_id":"baf4d113-d733-478e-8223-0e5a37d6628f","resolution":{"observed_at":"2026-08-04T23:54:01.355049Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.264258Z","title":"Mmgcn: Multi-modal graph convolution network for personalized recommenda- tion of micro-video,","venue":null,"work_id":"c7230c13-6b9d-47b9-8963-d67a8267ef1e","year":2019},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.534734Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:14900055cbe3c69bc0ce62cb13c1c7f22342c9bb8894220f1d9653d20b57ac76","observation_id":"8378c22e-3ded-4e40-9545-4a4a5f73bbd6","resolution":{"observed_at":"2026-08-04T23:54:02.299872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.03879","last_updated":"2023-04-08T00:30:08Z","snapshot_observed_at":"2026-07-06T15:13:33.023550Z","submitted_at":"2023-04-08T00:30:08Z","title":"GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.03879","snapshot_observed_at":"2026-08-04T23:54:00.567764Z","title":"Gpt4rec: A generative framework for personalized recommendation and user interests interpretation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.567764Z"},"links":{"cited_paper":"/paper/2304.03879","citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:58a47ddcd68f0a60960a6db165efdad9e30ce5d3f5f6eb43996e08ec2eb3cd93","observation_id":"34536199-543b-48ca-b535-12c7e6e659cc","resolution":{"observed_at":"2026-08-04T23:54:00.567764Z","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":"2026-08-04T23:54:02.140794Z","title":"Recom- mendation as instruction following: A large language model empowered recommendation approach,","venue":null,"work_id":"9bd72bae-2b49-4adf-a6b5-0b16eea8cb01","year":2025},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.606945Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:1245dc86beb2b7e0517e32662cee1407645375b166047f1ab0dd2f3a921b6737","observation_id":"c6dea11d-922c-44ee-b210-44dbb81e4a9f","resolution":{"observed_at":"2026-08-04T23:54:02.173770Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:02.064501Z","title":"Large language models are zero-shot rankers for recommender systems,","venue":null,"work_id":"544cc25f-6165-4634-97d0-e3bb732caadf","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.631267Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:d94099de4476435f84c2c39571b22365bd4a230a67a61739d8e2d9b566e5e211","observation_id":"448bf59b-98e1-40e7-8902-467ddcd93be5","resolution":{"observed_at":"2026-08-04T23:54:02.104893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.979099Z","title":"Recommender systems in the era of large language models (llms),","venue":null,"work_id":"0d93a4e2-a4bb-42c9-9f8a-1cbb28549a6a","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.656038Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:9dbbc69d3e5858d8e6d2f348dbe3cb6cf030d230e504767ad4b92586665ab297","observation_id":"26937939-8d2e-4c06-a8d8-645f164999ab","resolution":{"observed_at":"2026-08-04T23:54:02.012580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.858518Z","title":"Collm: Integrating collaborative embeddings into large language models for rec- ommendation,","venue":null,"work_id":"21022903-0784-4444-9c94-62e1bd887f14","year":2025},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.690422Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:936345d4f74b19de1eb1ac7f474f8d4425d05268a824d6f7ad1b30a63a59e8d6","observation_id":"7f543167-e902-4fc3-866c-6374aed2679c","resolution":{"observed_at":"2026-08-04T23:54:01.924145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.764988Z","title":"Large language models enhanced collaborative filtering,","venue":null,"work_id":"315c8d9a-7845-4c5f-a176-99d77e92daa3","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.760372Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:61d4e034978f7aaf51610b4d0f8147d05fdbf10d062d2c1cbfe5a43536225e42","observation_id":"68086dad-4b6a-41d3-b9d2-23a78333236b","resolution":{"observed_at":"2026-08-04T23:54:01.794922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17271","last_updated":"2024-12-23T04:39:08Z","snapshot_observed_at":"2026-07-06T20:11:55.722067Z","submitted_at":"2024-12-23T04:39:08Z","title":"Multi-view Fuzzy Graph Attention Networks for Enhanced Graph Learning","version":1},"cited_work":{"arxiv_id":"2412.17271","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.17271","snapshot_observed_at":"2026-08-04T23:54:01.201920Z","title":"Multi-view Fuzzy Graph Attention Networks for Enhanced Graph Learning","venue":"cs.LG","work_id":"a9945dba-7590-42c2-8e34-395e145eae18","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.792483Z"},"links":{"cited_paper":"/paper/2412.17271","citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:0d20a3fa9cd9dd3b2460e12c2f7bf5e9257812925a10d44b7af6c6a02217a60d","observation_id":"802045bf-3187-4ef5-8fdf-d289456f3ef1","resolution":{"observed_at":"2026-08-04T23:54:01.235162Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:00.832960Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.832960Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:c19d9baac16941c84ed95f45fe0dd37746d2ea5478c17ffaa8352ff23a9031d9","observation_id":"bc3011f7-8473-4f4f-bcb7-4ba5ea2f8245","resolution":{"observed_at":"2026-08-04T23:54:00.832960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.07482","last_updated":"2025-02-01T22:42:03Z","snapshot_observed_at":"2026-07-06T19:48:49.553384Z","submitted_at":"2024-11-12T02:08:19Z","title":"Enhancing Link Prediction with Fuzzy Graph Attention Networks and Dynamic Negative Sampling","version":3},"cited_work":{"arxiv_id":"2411.07482","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.07482","snapshot_observed_at":"2026-08-04T23:54:01.106812Z","title":"Enhancing Link Prediction with Fuzzy Graph Attention Networks and Dynamic Negative Sampling","venue":"cs.LG","work_id":"38e3120a-5eeb-4e23-b6bb-6185fb67a448","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.846952Z"},"links":{"cited_paper":"/paper/2411.07482","citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:057f7bb0ed3003e1bb06894dcb700b3a4fc52dddce75a7956d9a60a609ef39ab","observation_id":"cc2e4043-ef1b-4e02-9c92-2e66006ef16f","resolution":{"observed_at":"2026-08-04T23:54:01.151499Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.688255Z","title":"Self-attentive sequential recommenda- tion,","venue":null,"work_id":"fc3af635-f424-4056-841c-7991222286c9","year":2018},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.898976Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:f54772925a283dae5d82aa7ea961b702a7ed7b24a84623cfa9931de679f7173f","observation_id":"1008e864-19ef-454b-a9f7-661aae52c391","resolution":{"observed_at":"2026-08-04T23:54:01.720246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.583434Z","title":"Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer,","venue":null,"work_id":"8ba5a676-3547-43a6-b36a-a6a00b6aca9b","year":2019},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:00.979087Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:bee2f4550dd480b8c75386b14ffe05b16ff223528f59e294c4987dd111ed50b5","observation_id":"bac5bd06-3918-47d4-87e4-586afb0b76b9","resolution":{"observed_at":"2026-08-04T23:54:01.633546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.486598Z","title":"Llmrec: Large language models with graph augmentation for recommendation,","venue":null,"work_id":"c180b18e-f9b9-4c85-a6f9-cab899a3c3dd","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:01.038021Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:85994e216dfd5509d15cf196506b3d53ea9c59329472b3b478a432c716214629","observation_id":"4cfe276b-acdf-46bc-8962-34c5d54737a0","resolution":{"observed_at":"2026-08-04T23:54:01.514092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-04T23:54:01.405868Z","title":"Enhancing sequential recommendation via llm-based semantic embedding learning,","venue":null,"work_id":"f8c1e2da-5379-4e1b-9197-40d37d97164c","year":2024},"citing_paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T23:54:01.046052Z"},"links":{"citing_paper":"/paper/2509.06286"},"observation_digest":"sha256:cc7a46c015340b1c8892535b0947b22b05dff3f38d31eedb31944546cc54da5c","observation_id":"62f821d9-88c3-4625-930f-5f889f6d8ff6","resolution":{"observed_at":"2026-08-04T23:54:01.446538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.06286","last_updated":"2025-09-08T02:15:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T00:52:28.912052Z","submitted_at":"2025-09-08T02:15:55Z","title":"RecMind: LLM-Enhanced Graph Neural Networks for Personalized Consumer Recommendations"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":3,"verified_fuzzy":24},"total_outbound_references":31},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2509.06286."}