{"as_of":"2026-08-05T22:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5034cb8a7b572c6fb92657526b5fe9b5ac80f5cfcdf84d6df5754a3300ede99d","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":"2026-08-05T06:32:48.257954+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":"2026-05-16T23:51:50.163520Z","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":"2026-05-16T23:51:50.244403Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.10195","last_updated":"2024-06-06T13:22:25Z","snapshot_observed_at":"2026-07-06T16:33:34.184498Z","submitted_at":"2023-10-16T09:04:28Z","title":"AdaLomo: Low-memory Optimization with Adaptive Learning Rate","version":3},"cited_work":{"arxiv_id":"2310.10195","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10195","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"AdaLomo : Low-memory Optimization with Adaptive Learning Rate","venue":null,"work_id":"a5846044-bc67-49e8-8668-22b6d92f1fbd","year":2023},"citing_paper":{"arxiv_id":"2403.03507","last_updated":"2024-06-02T21:24:12Z","snapshot_observed_at":"2026-07-06T17:40:15.746482Z","submitted_at":"2024-03-06T07:29:57Z","title":"GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-05-16T23:51:50.163520Z"},"links":{"cited_paper":"/paper/2310.10195","citing_paper":"/paper/2403.03507"},"observation_digest":"sha256:ca1b8c5c6c31d4b8d867f15a60b5317747124e5fcb74f6a90c8acbdb0062fe8c","observation_id":"dd7ff94d-2d99-4b92-ac6b-21e9de83f4aa","resolution":{"observed_at":"2026-05-16T23:51:50.246992Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10195","last_updated":"2024-06-06T13:22:25Z","snapshot_observed_at":"2026-07-06T16:33:34.184498Z","submitted_at":"2023-10-16T09:04:28Z","title":"AdaLomo: Low-memory Optimization with Adaptive Learning Rate","version":3},"cited_work":{"arxiv_id":"2310.10195","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10195","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"AdaLomo : Low-memory Optimization with Adaptive Learning Rate","venue":null,"work_id":"a5846044-bc67-49e8-8668-22b6d92f1fbd","year":2023},"citing_paper":{"arxiv_id":"2604.12968","last_updated":"2026-04-14T17:01:36Z","snapshot_observed_at":"2026-07-06T23:01:05.634599Z","submitted_at":"2026-04-14T17:01:36Z","title":"Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T15:16:58.221358Z"},"links":{"cited_paper":"/paper/2310.10195","citing_paper":"/paper/2604.12968"},"observation_digest":"sha256:54006f9640979af05f7aea12b22d1127a77c7f371874b9f685c5ac20a7253740","observation_id":"c723add3-c02a-4a60-8c24-a3616bd0b310","resolution":{"observed_at":"2026-05-11T10:51:21.591474Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.10195/citation-record","integrity":"/paper/2310.10195/integrity","json":"/paper/2310.10195/citation-record.json","paper":"/paper/2310.10195"},"outbound":[],"paper":{"arxiv_id":"2310.10195","last_updated":"2024-06-06T13:22:25Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T16:33:34.184498Z","submitted_at":"2023-10-16T09:04:28Z","title":"AdaLomo: Low-memory Optimization with Adaptive Learning Rate"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.10195."}