{"as_of":"2026-08-12T08:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:59033c711ecaaacdb9fb88d277a4a205403211183bb9bd9aac0e09964bb19074","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":"2026-08-12T06:34:41.77262+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":"2026-08-12T05:33:45.864017Z","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":"2026-05-18T13:41:25.513460Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08645","snapshot_observed_at":"2026-08-12T05:33:45.864017Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00359","last_updated":"2025-05-02T04:24:25Z","snapshot_observed_at":"2026-08-12T05:25:29.626723Z","submitted_at":"2024-11-30T04:46:20Z","title":"Does Self-Attention Need Separate Weights in Transformers?","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-12T05:33:45.864017Z"},"links":{"cited_paper":"/paper/2105.08645","citing_paper":"/paper/2412.00359"},"observation_digest":"sha256:92f0c9a51f3c63ca6a7e0905c8f277f225b1a8232c7a79f54b1c4e07c1a49492","observation_id":"4b7966ec-184d-4ee2-aca1-aad55d9c8caf","resolution":{"observed_at":"2026-08-12T05:33:45.864017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08645","snapshot_observed_at":"2026-08-07T15:29:08.736186Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.15088","last_updated":"2025-05-21T04:14:35Z","snapshot_observed_at":"2026-08-10T08:27:18.497471Z","submitted_at":"2025-05-21T04:14:35Z","title":"Leveraging Large Language Models for Command Injection Vulnerability Analysis in Python: An Empirical Study on Popular Open-Source Projects","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:29:08.736186Z"},"links":{"cited_paper":"/paper/2105.08645","citing_paper":"/paper/2505.15088"},"observation_digest":"sha256:15042c655c09bf9efdc5d03e072e91578683dc1ee6577a19fbee20b8e47ccd9d","observation_id":"5ac53d72-d548-4d1f-b3f6-69daae852529","resolution":{"observed_at":"2026-08-07T15:29:08.736186Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08645","snapshot_observed_at":"2026-08-06T05:46:59.407627Z","title":"Cotext: Multi-task learning with code-text transformer","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.01233","last_updated":"2025-08-02T07:09:17Z","snapshot_observed_at":"2026-08-07T01:10:11.222770Z","submitted_at":"2025-08-02T07:09:17Z","title":"Detailed radial scale height profile of dust grains as probed by dust self-scattering in HL Tau","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T05:46:59.407627Z"},"links":{"cited_paper":"/paper/2105.08645","citing_paper":"/paper/2508.01233"},"observation_digest":"sha256:e9ab9d9277d75ff7ad36b9bfbca0ca52e21309f8d79a28a50f61e8610a3574a1","observation_id":"b558e35d-bd7e-4cd6-a278-b0a361b71492","resolution":{"observed_at":"2026-08-06T05:46:59.407627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.08645","snapshot_observed_at":"2026-08-06T05:48:16.025328Z","title":"Cotext: Multi-task learning with code-text transformer","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.01237","last_updated":"2025-08-02T07:22:51Z","snapshot_observed_at":"2026-08-10T23:46:38.796495Z","submitted_at":"2025-08-02T07:22:51Z","title":"SketchAgent: Generating Structured Diagrams from Hand-Drawn Sketches","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T05:48:16.025328Z"},"links":{"cited_paper":"/paper/2105.08645","citing_paper":"/paper/2508.01237"},"observation_digest":"sha256:20a2d19ba493a05730b9bc92e4c617ca45f4991c2bb59fcd0bb9d83160aa53dc","observation_id":"411ce69b-5a83-41f1-86ba-7c5041fb6aa8","resolution":{"observed_at":"2026-08-06T05:48:16.025328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer","version":4},"cited_work":{"arxiv_id":"2105.08645","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2105.08645","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cotext: Multi-task learning with code-text transformer.arXiv preprint arXiv:2105.08645","venue":null,"work_id":"d7415594-ea51-4cfa-b2ce-b573424f7297","year":null},"citing_paper":{"arxiv_id":"2509.21816","last_updated":"2026-04-21T08:54:13Z","snapshot_observed_at":"2026-07-31T14:12:25.799332Z","submitted_at":"2025-09-26T03:21:39Z","title":"From Task to Tutorial: An Automated GUI Framework for Excel Tutorial Document and Video Creation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-18T13:40:20.529176Z"},"links":{"cited_paper":"/paper/2105.08645","citing_paper":"/paper/2509.21816"},"observation_digest":"sha256:e99f9e990ac590927dad83195bb53005d9bad967b16e5b54f49a9348d20362e2","observation_id":"4c815d90-5711-4fc5-92dc-3c81970410c7","resolution":{"observed_at":"2026-05-18T13:41:25.516114Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2105.08645/citation-record","integrity":"/paper/2105.08645/integrity","json":"/paper/2105.08645/citation-record.json","paper":"/paper/2105.08645"},"outbound":[],"paper":{"arxiv_id":"2105.08645","last_updated":"2021-06-21T11:34:45Z","latest_version":4,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T11:10:33.637455Z","submitted_at":"2021-05-18T16:22:05Z","title":"CoTexT: Multi-task Learning with Code-Text Transformer"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2105.08645."}