{"as_of":"2026-08-08T22:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e16abd076867bedb5a1ce182ca057fcd3225742281bcbcbab6262a62987d948d","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T15:51:16.006252Z","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":"2026-06-30T14:04:44.436505Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.09117","last_updated":"2024-11-14T01:37:02Z","snapshot_observed_at":"2026-07-06T19:50:05.918060Z","submitted_at":"2024-11-14T01:37:02Z","title":"Efficiently learning and sampling multimodal distributions with data-based initialization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.09117","snapshot_observed_at":"2026-08-06T15:51:16.006252Z","title":"Efficiently learning and sampling multimodal distributions with data-based initialization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15173","last_updated":"2025-07-21T01:26:57Z","snapshot_observed_at":"2026-08-06T15:36:34.686535Z","submitted_at":"2025-07-21T01:26:57Z","title":"Better Models and Algorithms for Learning Ising Models from Dynamics","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T15:51:16.006252Z"},"links":{"cited_paper":"/paper/2411.09117","citing_paper":"/paper/2507.15173"},"observation_digest":"sha256:3c04c31bc18fd345f27f22a35b1c64e105d4cdbb99c51243ead2851bd5825061","observation_id":"94e273d1-0077-412a-9a40-8aa6dc8c4a0f","resolution":{"observed_at":"2026-08-06T15:51:16.006252Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.09117","last_updated":"2024-11-14T01:37:02Z","snapshot_observed_at":"2026-07-06T19:50:05.918060Z","submitted_at":"2024-11-14T01:37:02Z","title":"Efficiently learning and sampling multimodal distributions with data-based initialization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.09117","snapshot_observed_at":"2026-08-05T12:18:00.281869Z","title":"Efficiently learn- ing and sampling multimodal distributions with data-based initialization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01763","last_updated":"2025-09-01T20:49:27Z","snapshot_observed_at":"2026-08-08T15:14:10.663451Z","submitted_at":"2025-09-01T20:49:27Z","title":"A Hybrid Framework for Healing Semigroups with Machine Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T12:18:00.281869Z"},"links":{"cited_paper":"/paper/2411.09117","citing_paper":"/paper/2509.01763"},"observation_digest":"sha256:c197865a9a2a586d8ed7ea8c67b92f116b9da1705b506ccf1f681cb572d618d3","observation_id":"c0236781-430c-4169-aa28-dcf35a383e08","resolution":{"observed_at":"2026-08-05T12:18:00.281869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.09117","last_updated":"2024-11-14T01:37:02Z","snapshot_observed_at":"2026-07-06T19:50:05.918060Z","submitted_at":"2024-11-14T01:37:02Z","title":"Efficiently learning and sampling multimodal distributions with data-based initialization","version":1},"cited_work":{"arxiv_id":"2411.09117","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.09117","snapshot_observed_at":"2026-06-30T14:04:44.436505Z","title":"45 Ankur Moitra, Elchanan Mossel, and Colin P Sandon","venue":null,"work_id":"12f18ba3-2384-49a7-8486-49408d0b6d4c","year":2021},"citing_paper":{"arxiv_id":"2605.24752","last_updated":"2026-05-23T22:04:30Z","snapshot_observed_at":"2026-08-06T09:22:49.720213Z","submitted_at":"2026-05-23T22:04:30Z","title":"A computational phase transition for learning-to-sample from Ising models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-30T14:03:12.763695Z"},"links":{"cited_paper":"/paper/2411.09117","citing_paper":"/paper/2605.24752"},"observation_digest":"sha256:bb6163b4447501313a1bc7fd4969e94583a65ef59d018c588954898c0e7385da","observation_id":"77cd58f5-d4b7-48e7-be84-76d384190f27","resolution":{"observed_at":"2026-06-30T14:04:44.438039Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.09117/citation-record","integrity":"/paper/2411.09117/integrity","json":"/paper/2411.09117/citation-record.json","paper":"/paper/2411.09117"},"outbound":[],"paper":{"arxiv_id":"2411.09117","last_updated":"2024-11-14T01:37:02Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:50:05.918060Z","submitted_at":"2024-11-14T01:37:02Z","title":"Efficiently learning and sampling multimodal distributions with data-based initialization"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2411.09117."}