{"as_of":"2026-08-07T12:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ed1e5d5a0d10d8660bc01b96c2832de60cb437f871a29d922c7ccf1d206f5156","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:52:28.438777Z","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":"2026-05-11T23:26:13.448126Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2203.14338","last_updated":"2022-03-27T16:00:48Z","snapshot_observed_at":"2026-08-07T11:10:11.880228Z","submitted_at":"2022-03-27T16:00:48Z","title":"LibMTL: A Python Library for Multi-Task Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.14338","snapshot_observed_at":"2026-08-07T05:52:28.438777Z","title":"Libmtl: A python library for multi-task learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.06830","last_updated":"2025-06-07T15:18:43Z","snapshot_observed_at":"2026-08-07T10:51:08.878633Z","submitted_at":"2025-06-07T15:18:43Z","title":"EndoARSS: Adapting Spatially-Aware Foundation Model for Efficient Activity Recognition and Semantic Segmentation in Endoscopic Surgery","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T05:52:28.438777Z"},"links":{"cited_paper":"/paper/2203.14338","citing_paper":"/paper/2506.06830"},"observation_digest":"sha256:63f3bdd9776de72228b0bbca69ce30a370caa11ceb2ecd5ac109b8394531b461","observation_id":"392b566b-88e1-451b-a686-fc8ef6dd1c09","resolution":{"observed_at":"2026-08-07T05:52:28.438777Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.14338","last_updated":"2022-03-27T16:00:48Z","snapshot_observed_at":"2026-08-07T11:10:11.880228Z","submitted_at":"2022-03-27T16:00:48Z","title":"LibMTL: A Python Library for Multi-Task Learning","version":1},"cited_work":{"arxiv_id":"2203.14338","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2203.14338","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Libmtl: A python library for multi-task learning","venue":null,"work_id":"8820dca9-6639-4c0a-b01f-ec53dffc231d","year":2022},"citing_paper":{"arxiv_id":"2604.25131","last_updated":"2026-04-29T03:40:37Z","snapshot_observed_at":"2026-07-06T23:11:02.043135Z","submitted_at":"2026-04-28T02:09:07Z","title":"Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-07T17:04:32.741694Z"},"links":{"cited_paper":"/paper/2203.14338","citing_paper":"/paper/2604.25131"},"observation_digest":"sha256:8c18c427f7e1b779880222f5b71798e6d70a770cea170d18dcfa3dc62da85073","observation_id":"4b8dbef2-5acb-4238-819a-b253bd8e21a6","resolution":{"observed_at":"2026-05-11T23:26:13.455184Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2203.14338/citation-record","integrity":"/paper/2203.14338/integrity","json":"/paper/2203.14338/citation-record.json","paper":"/paper/2203.14338"},"outbound":[],"paper":{"arxiv_id":"2203.14338","last_updated":"2022-03-27T16:00:48Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T11:10:11.880228Z","submitted_at":"2022-03-27T16:00:48Z","title":"LibMTL: A Python Library for Multi-Task 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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.14338."}