{"as_of":"2026-08-16T23:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d365b01551a73f6d5cf70dbbec3191cb091184e9139a3f5fa994e26a5801e8f1","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":"2026-08-16T06:30:59.297886+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":"2026-08-15T18:51:57.291941Z","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":"2026-07-04T13:49:51.301248Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10655","snapshot_observed_at":"2026-08-11T20:56:33.795769Z","title":"A survey of what to share in federated learning: Perspectives on model utility, privacy leakage, and communication efficiency","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.05186","last_updated":"2024-12-06T17:05:34Z","snapshot_observed_at":"2026-08-12T18:24:03.262875Z","submitted_at":"2024-12-06T17:05:34Z","title":"One-shot Federated Learning via Synthetic Distiller-Distillate Communication","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T20:56:33.795769Z"},"links":{"cited_paper":"/paper/2307.10655","citing_paper":"/paper/2412.05186"},"observation_digest":"sha256:e6dfe16d383d243a4dc7b765b6c200c9125ef9c7421d94f9b3f05ddee63ccc23","observation_id":"aa1a9e78-e6bd-4a93-b740-aca6e36f9b3d","resolution":{"observed_at":"2026-08-11T20:56:33.795769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10655","snapshot_observed_at":"2026-08-15T18:51:57.291941Z","title":"A survey of what to share in federated learning: Perspectives on model utility, privacy leakage, and communication efficiency","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.18525","last_updated":"2025-06-23T11:27:34Z","snapshot_observed_at":"2026-08-16T12:13:45.777416Z","submitted_at":"2025-06-23T11:27:34Z","title":"Federated Learning from Molecules to Processes: A Perspective","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T18:51:57.291941Z"},"links":{"cited_paper":"/paper/2307.10655","citing_paper":"/paper/2506.18525"},"observation_digest":"sha256:b8c7c31dfcc10b64f9b4c90838f6ddb682664f75ab43d91ea18cdd86ad25990f","observation_id":"2ae71d60-1c20-49ea-a49b-fbf99995dc68","resolution":{"observed_at":"2026-08-15T18:51:57.291941Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","version":2},"cited_work":{"arxiv_id":"2307.10655","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.10655","snapshot_observed_at":"2026-07-04T13:49:51.301248Z","title":"A Survey Of What To Share In Federated Learning: Perspectives On Model Utility, Privacy Leakage, And Communication Efficiency","venue":null,"work_id":"45bc1d62-5a70-4068-b091-6a56152cc81b","year":2024},"citing_paper":{"arxiv_id":"2510.02371","last_updated":"2026-05-07T15:53:15Z","snapshot_observed_at":"2026-08-13T08:26:26.232491Z","submitted_at":"2025-09-29T08:52:30Z","title":"Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-18T13:14:16.203867Z"},"links":{"cited_paper":"/paper/2307.10655","citing_paper":"/paper/2510.02371"},"observation_digest":"sha256:f702129170759f2bc658bf42b94f114790814b795a23a402192723c1f46b8423","observation_id":"6507f1bb-02ff-48c3-90cb-0eff64f76a10","resolution":{"observed_at":"2026-05-18T13:16:24.466669Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","version":2},"cited_work":{"arxiv_id":"2307.10655","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.10655","snapshot_observed_at":"2026-07-04T13:49:51.301248Z","title":"A Survey Of What To Share In Federated Learning: Perspectives On Model Utility, Privacy Leakage, And Communication Efficiency","venue":null,"work_id":"45bc1d62-5a70-4068-b091-6a56152cc81b","year":2024},"citing_paper":{"arxiv_id":"2510.26841","last_updated":"2026-04-29T15:16:42Z","snapshot_observed_at":"2026-08-12T16:18:11.693262Z","submitted_at":"2025-10-30T07:14:55Z","title":"FedPF: Accurate Target Privacy Preserving Federated Learning Balancing Fairness and Utility","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-18T02:56:38.973027Z"},"links":{"cited_paper":"/paper/2307.10655","citing_paper":"/paper/2510.26841"},"observation_digest":"sha256:85d127b497a3acd95878b35562fdde2a09be8e6c9f83c4bb148431881bc377d2","observation_id":"40ffd2f6-f9b9-4e81-b8de-477e931e5efe","resolution":{"observed_at":"2026-05-18T03:00:48.664905Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","version":2},"cited_work":{"arxiv_id":"2307.10655","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.10655","snapshot_observed_at":"2026-07-04T13:49:51.301248Z","title":"A Survey Of What To Share In Federated Learning: Perspectives On Model Utility, Privacy Leakage, And Communication Efficiency","venue":null,"work_id":"45bc1d62-5a70-4068-b091-6a56152cc81b","year":2024},"citing_paper":{"arxiv_id":"2606.26822","last_updated":"2026-06-25T10:03:55Z","snapshot_observed_at":"2026-08-15T08:05:47.071157Z","submitted_at":"2026-06-25T10:03:55Z","title":"Quantization in Federated Learning: Methods, Challenges and Future Directions","version":1},"reference_index":108,"source":"pdf_text","source_observed_at":"2026-06-26T04:56:12.424439Z"},"links":{"cited_paper":"/paper/2307.10655","citing_paper":"/paper/2606.26822"},"observation_digest":"sha256:430626e549180cafdf6e3ee1cb80c787d1c2b9c701a538d42d157a047b919629","observation_id":"4c725e69-9a68-4137-9c93-9cd7593d3e36","resolution":{"observed_at":"2026-07-04T13:49:51.303060Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2307.10655/citation-record","integrity":"/paper/2307.10655/integrity","json":"/paper/2307.10655/citation-record.json","paper":"/paper/2307.10655"},"outbound":[],"paper":{"arxiv_id":"2307.10655","last_updated":"2024-02-18T06:16:41Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T15:14:46.568069Z","submitted_at":"2023-07-20T07:35:42Z","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.10655."}