{"as_of":"2026-08-09T11:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fad9e9f8a07dec4f900b50aeabfb8b8aaa490b71de1d172dc964b6c6f37a6457","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T17:06:45.938788Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-25T06:15:23.709189Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18887","snapshot_observed_at":"2026-08-08T17:06:45.938788Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06006","last_updated":"2025-02-09T19:51:00Z","snapshot_observed_at":"2026-08-08T17:00:55.205766Z","submitted_at":"2025-02-09T19:51:00Z","title":"FactIR: A Real-World Zero-shot Open-Domain Retrieval Benchmark for Fact-Checking","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T17:06:45.938788Z"},"links":{"cited_paper":"/paper/2407.18887","citing_paper":"/paper/2502.06006"},"observation_digest":"sha256:5550c95493882e30d9ac2401ef40deab3f0ae43ee85ca2245fd113db4437e52c","observation_id":"5cef859c-6470-4269-aa9b-b7af52ea4ed5","resolution":{"observed_at":"2026-08-08T17:06:45.938788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining","version":1},"cited_work":{"arxiv_id":"2407.18887","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.18887","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"NLLB Team, Marta R","venue":null,"work_id":"e65eda19-7a0c-4303-9312-e69e2d5663cd","year":2024},"citing_paper":{"arxiv_id":"2604.01960","last_updated":"2026-06-02T03:45:45Z","snapshot_observed_at":"2026-07-13T14:06:07.705156Z","submitted_at":"2026-04-02T12:22:38Z","title":"BBC: Improving Large-k Approximate Nearest Neighbor Search with a Bucket-based Result Collector","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-13T20:47:04.696419Z"},"links":{"cited_paper":"/paper/2407.18887","citing_paper":"/paper/2604.01960"},"observation_digest":"sha256:67dfc80fb3edd2a876af77d5188d529d557bd264201d75f5e04c771bd70af717","observation_id":"0345c40a-7060-4933-9a34-2ea699ad7301","resolution":{"observed_at":"2026-05-13T20:48:15.203753Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18887","snapshot_observed_at":"2026-07-13T14:06:32.542639Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.01960","last_updated":"2026-06-02T03:45:45Z","snapshot_observed_at":"2026-07-13T14:06:07.705156Z","submitted_at":"2026-04-02T12:22:38Z","title":"BBC: Improving Large-k Approximate Nearest Neighbor Search with a Bucket-based Result Collector","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-13T14:06:32.542639Z"},"links":{"cited_paper":"/paper/2407.18887","citing_paper":"/paper/2604.01960"},"observation_digest":"sha256:fd39951f6c338c574fde736590808920122952748a5ee3f38e4ad286f0a13a2c","observation_id":"76eefa24-0876-475e-82a3-7f742133d49b","resolution":{"observed_at":"2026-07-13T14:06:32.542639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining","version":1},"cited_work":{"arxiv_id":"2407.18887","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2407.18887","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"NLLB Team, Marta R","venue":null,"work_id":"e65eda19-7a0c-4303-9312-e69e2d5663cd","year":2024},"citing_paper":{"arxiv_id":"2605.23721","last_updated":"2026-05-21T08:59:11Z","snapshot_observed_at":"2026-08-02T03:03:59.081595Z","submitted_at":"2026-05-21T08:59:11Z","title":"Is a Document Educational or Just Wikipedia-Style? -- Pitfalls of Classifier-Based Quality Filtering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-25T06:12:37.854507Z"},"links":{"cited_paper":"/paper/2407.18887","citing_paper":"/paper/2605.23721"},"observation_digest":"sha256:3d1956f9abdce61d5a5dc64fc0873d7902ca098195e8ef68835e6f65b5948fac","observation_id":"c3233f94-9e4e-4cff-9bfa-4292fdb3673b","resolution":{"observed_at":"2026-05-25T06:15:23.711282Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18887","snapshot_observed_at":"2026-08-02T07:07:39.617592Z","title":"Embedding and clustering your data can improve contrastive pretraining.arXiv preprint arXiv:2407.18887,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11976","last_updated":"2026-07-26T04:17:22Z","snapshot_observed_at":"2026-08-09T00:36:09.452998Z","submitted_at":"2026-07-13T03:53:56Z","title":"LiteTopK: Exploiting the Curse of Dimensionality for a Fused Indexer-TopK Kernel in Long-Context Sparse Attention","version":3},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-02T07:07:39.617592Z"},"links":{"cited_paper":"/paper/2407.18887","citing_paper":"/paper/2607.11976"},"observation_digest":"sha256:623cd17c8b1a8b7d7115b596643da3b72818bfdfb3f857812a552dbc2a090f6b","observation_id":"9bdda9c0-075b-4a34-9df4-f87ba0108bcd","resolution":{"observed_at":"2026-08-02T07:07:39.617592Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.18887/citation-record","integrity":"/paper/2407.18887/integrity","json":"/paper/2407.18887/citation-record.json","paper":"/paper/2407.18887"},"outbound":[],"paper":{"arxiv_id":"2407.18887","last_updated":"2024-07-26T17:36:40Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T08:05:00.477139Z","submitted_at":"2024-07-26T17:36:40Z","title":"Embedding And Clustering Your Data Can Improve Contrastive Pretraining"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.18887."}