{"as_of":"2026-08-17T13:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:617474e5d480d20709cebd60eec7fb654325a48cb1bba7f88723da8dc5d6301b","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:55:36.052892Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T04:26:33.725983Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.02055","last_updated":"2024-02-03T06:29:04Z","snapshot_observed_at":"2026-08-16T23:28:49.420858Z","submitted_at":"2024-02-03T06:29:04Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02055","snapshot_observed_at":"2026-08-12T11:06:36.368647Z","title":"Variance alignment score: A simple but tough-to-beat data selection method for multimodal con- trastive learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18674","last_updated":"2025-05-05T14:25:01Z","snapshot_observed_at":"2026-08-14T14:04:12.371424Z","submitted_at":"2024-11-27T18:50:15Z","title":"Active Data Curation Effectively Distills Large-Scale Multimodal Models","version":2},"reference_index":169,"source":"pdf_text","source_observed_at":"2026-08-12T11:06:36.368647Z"},"links":{"cited_paper":"/paper/2402.02055","citing_paper":"/paper/2411.18674"},"observation_digest":"sha256:fb7a347cb63166e3d79b29a98dd0c1788d1869c829c940ea41b25e0af1ec4466","observation_id":"61047a92-409b-43e9-b060-42d5b4bfd66e","resolution":{"observed_at":"2026-08-12T11:06:36.368647Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02055","last_updated":"2024-02-03T06:29:04Z","snapshot_observed_at":"2026-08-16T23:28:49.420858Z","submitted_at":"2024-02-03T06:29:04Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02055","snapshot_observed_at":"2026-08-15T23:55:36.052892Z","title":"Variance alignment score: A simple but tough-to-beat data selection method for multimodal contrastive learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.03532","last_updated":"2025-05-06T13:41:31Z","snapshot_observed_at":"2026-08-15T23:46:54.687560Z","submitted_at":"2025-05-06T13:41:31Z","title":"Joint Generalized Cosine Similarity: A Novel Method for N-Modal Semantic Alignment Based on Contrastive Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-15T23:55:36.052892Z"},"links":{"cited_paper":"/paper/2402.02055","citing_paper":"/paper/2505.03532"},"observation_digest":"sha256:86f934c89c56a2b609091b6c0a1a1e6dda8e159ed5e48b311c672254a92002d9","observation_id":"bec2b03c-b48a-4cc0-a6fc-e85f870415c9","resolution":{"observed_at":"2026-08-15T23:55:36.052892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02055","last_updated":"2024-02-03T06:29:04Z","snapshot_observed_at":"2026-08-16T23:28:49.420858Z","submitted_at":"2024-02-03T06:29:04Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","version":1},"cited_work":{"arxiv_id":"2402.02055","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.02055","snapshot_observed_at":"2026-08-07T04:26:33.725983Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","venue":"cs.LG","work_id":"46451135-a92a-4b0f-9ed9-880739f0d5e1","year":2024},"citing_paper":{"arxiv_id":"2506.10550","last_updated":"2025-06-12T10:17:30Z","snapshot_observed_at":"2026-08-17T03:00:36.551413Z","submitted_at":"2025-06-12T10:17:30Z","title":"ContextRefine-CLIP for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2025","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T04:26:33.686867Z"},"links":{"cited_paper":"/paper/2402.02055","citing_paper":"/paper/2506.10550"},"observation_digest":"sha256:adb8bd068dedc8860409e2d8a2e4c2622d126ff8723556cb5cbe0ff31491c261","observation_id":"f2851f5d-d896-4c48-95c1-c238446bb0b0","resolution":{"observed_at":"2026-08-07T04:26:33.732440Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02055","last_updated":"2024-02-03T06:29:04Z","snapshot_observed_at":"2026-08-16T23:28:49.420858Z","submitted_at":"2024-02-03T06:29:04Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02055","snapshot_observed_at":"2026-08-15T18:16:07.849285Z","title":"arXiv preprint arXiv:2402.02055 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18616","last_updated":"2025-07-24T17:53:26Z","snapshot_observed_at":"2026-08-15T18:07:14.505762Z","submitted_at":"2025-07-24T17:53:26Z","title":"SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-15T18:16:07.849285Z"},"links":{"cited_paper":"/paper/2402.02055","citing_paper":"/paper/2507.18616"},"observation_digest":"sha256:599a972d281dfae30bb3c07cda7a8cc2800cc7fe1092b1ca6b6a0741dc6a2a75","observation_id":"2b8c12b4-dd4d-4b82-8221-77c65f727410","resolution":{"observed_at":"2026-08-15T18:16:07.849285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.02055/citation-record","integrity":"/paper/2402.02055/integrity","json":"/paper/2402.02055/citation-record.json","paper":"/paper/2402.02055"},"outbound":[],"paper":{"arxiv_id":"2402.02055","last_updated":"2024-02-03T06:29:04Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T23:28:49.420858Z","submitted_at":"2024-02-03T06:29:04Z","title":"Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.02055."}