{"as_of":"2026-08-13T13:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5dfcceeadbbd9bf04af3b67476edc030f1b2600d93eddf4fdf1c4505da4237cf","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T20:25:45.185082Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":2,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.10743","last_updated":"2024-09-26T03:38:59Z","snapshot_observed_at":"2026-08-13T07:29:36.391441Z","submitted_at":"2023-12-17T15:28:06Z","title":"A Unified Framework for Multi-Domain CTR Prediction via Large Language Models","version":4},"cited_work":{"arxiv_id":"2312.10743","doi":"10.48550/arxiv.2312.10743","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.10743","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv:2312.10743 [cs.IR]https://arxiv.org/abs/2312.10743 Vineet Gupta, Tomer Koren, and Yoram Singer","venue":"arXiv (Cornell University)","work_id":"fdf91667-67a2-4624-922a-426eb98e164e","year":2023},"citing_paper":{"arxiv_id":"2601.02366","last_updated":"2026-07-26T08:52:57Z","snapshot_observed_at":"2026-08-13T08:56:38.090616Z","submitted_at":"2025-11-25T08:36:01Z","title":"TextBridgeGNN: Pre-training Graph Neural Network for Cross-Domain Recommendation via Text-Guided Transfer","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-17T05:24:36.878045Z"},"links":{"cited_paper":"/paper/2312.10743","citing_paper":"/paper/2601.02366"},"observation_digest":"sha256:fc33e4c21761286e060fd7691c797e04232d957468b6fbd03f5c6d597790951f","observation_id":"a4e792ec-389d-4921-94d9-058236e02ddf","resolution":{"observed_at":"2026-05-17T05:29:04.621376Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10743","last_updated":"2024-09-26T03:38:59Z","snapshot_observed_at":"2026-08-13T07:29:36.391441Z","submitted_at":"2023-12-17T15:28:06Z","title":"A Unified Framework for Multi-Domain CTR Prediction via Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10743","snapshot_observed_at":"2026-08-03T20:25:45.185082Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02366","last_updated":"2026-07-26T08:52:57Z","snapshot_observed_at":"2026-08-13T08:56:38.090616Z","submitted_at":"2025-11-25T08:36:01Z","title":"TextBridgeGNN: Pre-training Graph Neural Network for Cross-Domain Recommendation via Text-Guided Transfer","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T20:25:45.185082Z"},"links":{"cited_paper":"/paper/2312.10743","citing_paper":"/paper/2601.02366"},"observation_digest":"sha256:2709ce0471106e206e210e982c0c506864c118f37e448c6be5729cda93ab608a","observation_id":"fc2f545b-41f6-41be-80ff-f5c9d0ba0553","resolution":{"observed_at":"2026-08-03T20:25:45.185082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10743","last_updated":"2024-09-26T03:38:59Z","snapshot_observed_at":"2026-08-13T07:29:36.391441Z","submitted_at":"2023-12-17T15:28:06Z","title":"A Unified Framework for Multi-Domain CTR Prediction via Large Language Models","version":4},"cited_work":{"arxiv_id":"2312.10743","doi":"10.48550/arxiv.2312.10743","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.10743","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv:2312.10743 [cs.IR]https://arxiv.org/abs/2312.10743 Vineet Gupta, Tomer Koren, and Yoram Singer","venue":"arXiv (Cornell University)","work_id":"fdf91667-67a2-4624-922a-426eb98e164e","year":2023},"citing_paper":{"arxiv_id":"2606.10243","last_updated":"2026-06-08T23:13:58Z","snapshot_observed_at":"2026-08-08T13:37:35.818714Z","submitted_at":"2026-06-08T23:13:58Z","title":"DUET -- Dual User Embedding Transformers for Offsite Conversion Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T16:56:12.040446Z"},"links":{"cited_paper":"/paper/2312.10743","citing_paper":"/paper/2606.10243"},"observation_digest":"sha256:0fabe05e2c425520f04221ad0c261c090e5ef0fde7c471599be4483a879507b0","observation_id":"d7bb634c-470a-40dd-ab2c-fa87dcb5d68a","resolution":{"observed_at":"2026-07-03T00:57:30.127274Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.10743/citation-record","integrity":"/paper/2312.10743/integrity","json":"/paper/2312.10743/citation-record.json","paper":"/paper/2312.10743"},"outbound":[],"paper":{"arxiv_id":"2312.10743","last_updated":"2024-09-26T03:38:59Z","latest_version":4,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-13T07:29:36.391441Z","submitted_at":"2023-12-17T15:28:06Z","title":"A Unified Framework for Multi-Domain CTR Prediction via Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.10743."}