{"as_of":"2026-08-13T19:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c4b03882d412a425fa888c8a84603ea811dac06117e50df6c3415596565239bb","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":"2026-08-13T06:32:02.005865+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":"2026-08-12T04:46:24.368800Z","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":"2026-05-22T15:34:57.787482Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.13044","last_updated":"2022-05-01T08:19:28Z","snapshot_observed_at":"2026-07-06T11:22:32.341852Z","submitted_at":"2021-06-24T14:17:00Z","title":"Personalized Federated Learning with Contextualized Generalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.13044","snapshot_observed_at":"2026-08-12T04:46:24.368800Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.01072","last_updated":"2024-12-02T03:18:47Z","snapshot_observed_at":"2026-08-12T22:40:51.812136Z","submitted_at":"2024-12-02T03:18:47Z","title":"When Fine-Tuning LLMs Meets Data Privacy: An Empirical Study of Federated Learning in LLM-Based Program Repair","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-12T04:46:24.368800Z"},"links":{"cited_paper":"/paper/2106.13044","citing_paper":"/paper/2412.01072"},"observation_digest":"sha256:0cd045d203c1faf6c3e8ef77251e7c84a3427c636fa12bb9d2769671bcf712fd","observation_id":"4b017b53-8b80-43bf-b168-0dd8a61662ed","resolution":{"observed_at":"2026-08-12T04:46:24.368800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.13044","last_updated":"2022-05-01T08:19:28Z","snapshot_observed_at":"2026-07-06T11:22:32.341852Z","submitted_at":"2021-06-24T14:17:00Z","title":"Personalized Federated Learning with Contextualized Generalization","version":2},"cited_work":{"arxiv_id":"2106.13044","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.13044","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Personalized federated learning with contextualized generalization","venue":null,"work_id":"d0636a6c-d237-4966-a393-d29958a1a8ad","year":2021},"citing_paper":{"arxiv_id":"2505.06907","last_updated":"2026-05-18T08:23:00Z","snapshot_observed_at":"2026-08-13T00:16:41.097127Z","submitted_at":"2025-05-11T08:57:53Z","title":"A Survey on Foundation Models for Personalized Federated Intelligence","version":2},"reference_index":269,"source":"pdf_text","source_observed_at":"2026-05-22T15:32:15.293888Z"},"links":{"cited_paper":"/paper/2106.13044","citing_paper":"/paper/2505.06907"},"observation_digest":"sha256:4adb7e44a11e4d8d8c7b1983254b768817512002d136999178ec01957dba736a","observation_id":"65038b97-0210-44e8-ab35-e9c80f36653f","resolution":{"observed_at":"2026-05-22T15:34:57.789871Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2106.13044/citation-record","integrity":"/paper/2106.13044/integrity","json":"/paper/2106.13044/citation-record.json","paper":"/paper/2106.13044"},"outbound":[],"paper":{"arxiv_id":"2106.13044","last_updated":"2022-05-01T08:19:28Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T11:22:32.341852Z","submitted_at":"2021-06-24T14:17:00Z","title":"Personalized Federated Learning with Contextualized Generalization"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.13044."}