{"as_of":"2026-08-14T09:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:17e08e2a81b0d14d69581ab37568ef63361e3edc2524048e6258e2d89d7fc76c","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":"2026-08-14T06:32:32.682623+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":"2026-08-07T05:49:53.567098Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.01564","last_updated":"2023-12-04T01:42:09Z","snapshot_observed_at":"2026-08-13T05:10:48.353513Z","submitted_at":"2023-12-04T01:42:09Z","title":"APoLLo: Unified Adapter and Prompt Learning for Vision Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.01564","snapshot_observed_at":"2026-08-07T05:49:53.567098Z","title":"Apollo: unified adapter and prompt learning for vision language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07016","last_updated":"2025-06-13T19:05:47Z","snapshot_observed_at":"2026-08-08T12:14:39.714543Z","submitted_at":"2025-06-08T06:34:29Z","title":"MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks","version":2},"reference_index":112,"source":"pdf_text","source_observed_at":"2026-08-07T05:49:53.567098Z"},"links":{"cited_paper":"/paper/2312.01564","citing_paper":"/paper/2506.07016"},"observation_digest":"sha256:bfd3d88df0921cca020a6f95c1c181eac87fe046fa01cca848e8264fd953b2b4","observation_id":"2f4dd2fc-f4a0-40c5-9108-6b5ca60f22c3","resolution":{"observed_at":"2026-08-07T05:49:53.567098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.01564","last_updated":"2023-12-04T01:42:09Z","snapshot_observed_at":"2026-08-13T05:10:48.353513Z","submitted_at":"2023-12-04T01:42:09Z","title":"APoLLo: Unified Adapter and Prompt Learning for Vision Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.01564","snapshot_observed_at":"2026-08-06T22:41:04.842354Z","title":"Apollo: unified adapter and prompt learning for vision lan- guage models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21080","last_updated":"2025-06-26T08:09:16Z","snapshot_observed_at":"2026-08-07T17:47:39.726590Z","submitted_at":"2025-06-26T08:09:16Z","title":"EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T22:41:04.842354Z"},"links":{"cited_paper":"/paper/2312.01564","citing_paper":"/paper/2506.21080"},"observation_digest":"sha256:b3043c65c5382004d554916e412b62a5b29a3aed312d96b0d081ef7b5b76e1ca","observation_id":"5e5fddc6-2751-497d-ac10-6984082d6c25","resolution":{"observed_at":"2026-08-06T22:41:04.842354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.01564","last_updated":"2023-12-04T01:42:09Z","snapshot_observed_at":"2026-08-13T05:10:48.353513Z","submitted_at":"2023-12-04T01:42:09Z","title":"APoLLo: Unified Adapter and Prompt Learning for Vision Language Models","version":1},"cited_work":{"arxiv_id":"2312.01564","doi":"10.48550/arxiv.2312.01564","metadata_source":"pith","pith_arxiv_id":"2312.01564","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"APoLLo: Unified Adapter and Prompt Learning for Vision Language Models","venue":"cs.LG","work_id":"bd0301ee-2005-4fb7-85f2-813820a07678","year":2023},"citing_paper":{"arxiv_id":"2607.19128","last_updated":"2026-07-21T14:18:25Z","snapshot_observed_at":"2026-08-13T08:31:10.764750Z","submitted_at":"2026-07-21T14:18:25Z","title":"One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-01T13:26:30.561516Z"},"links":{"cited_paper":"/paper/2312.01564","citing_paper":"/paper/2607.19128"},"observation_digest":"sha256:fd1e37a95cae242ffaf9ea0200db99bbf6d59aabedcdcaf49779ad190944a39e","observation_id":"db6cc2ec-4bc6-405b-a17e-621d98ca42eb","resolution":{"observed_at":"2026-08-01T13:29:34.650417Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.01564/citation-record","integrity":"/paper/2312.01564/integrity","json":"/paper/2312.01564/citation-record.json","paper":"/paper/2312.01564"},"outbound":[],"paper":{"arxiv_id":"2312.01564","last_updated":"2023-12-04T01:42:09Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T05:10:48.353513Z","submitted_at":"2023-12-04T01:42:09Z","title":"APoLLo: Unified Adapter and Prompt Learning for Vision 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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.01564."}