{"as_of":"2026-08-17T22:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:08b0e0b1d21890640aba3f22925199fd64f0f06e8c65e12982eb02dfe33a2d6c","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":"2026-08-17T06:30:58.91139+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":"2026-08-15T18:34:39.408803Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-15T14:37:21.553258Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.07886","last_updated":"2024-07-15T03:54:20Z","snapshot_observed_at":"2026-08-16T14:27:21.818959Z","submitted_at":"2024-01-15T18:28:17Z","title":"Learned Best-Effort LLM Serving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.07886","snapshot_observed_at":"2026-08-15T18:34:39.408803Z","title":"Learned best-effort llm serving,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19677","last_updated":"2025-06-25T16:13:14Z","snapshot_observed_at":"2026-08-17T10:44:33.208080Z","submitted_at":"2025-06-24T14:44:33Z","title":"Adaptive Request Scheduling for CodeLLM Serving with SLA Guarantees","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-15T18:34:39.408803Z"},"links":{"cited_paper":"/paper/2401.07886","citing_paper":"/paper/2506.19677"},"observation_digest":"sha256:9df6647a76ad529f2745df54b115e33af1e29a1263b104121e0fc39e03131aff","observation_id":"651f9bd1-fc9f-4958-902d-92d799ad9696","resolution":{"observed_at":"2026-08-15T18:34:39.408803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.07886","last_updated":"2024-07-15T03:54:20Z","snapshot_observed_at":"2026-08-16T14:27:21.818959Z","submitted_at":"2024-01-15T18:28:17Z","title":"Learned Best-Effort LLM Serving","version":2},"cited_work":{"arxiv_id":"2401.07886","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.07886","snapshot_observed_at":"2026-08-15T14:37:21.553258Z","title":"Learned Best-Effort LLM Serving","venue":"cs.LG","work_id":"c3b60c76-5032-4bb8-b628-3362eec16916","year":2024},"citing_paper":{"arxiv_id":"2608.06557","last_updated":"2026-08-06T20:14:21Z","snapshot_observed_at":"2026-08-15T22:55:47.932345Z","submitted_at":"2026-08-06T20:14:21Z","title":"Cascade: Exploiting SLO-Aware latency budget for fair and high goodput LLM inference serving","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-15T14:37:20.689429Z"},"links":{"cited_paper":"/paper/2401.07886","citing_paper":"/paper/2608.06557"},"observation_digest":"sha256:ecf7a131b178654855e62ec2c36df1269d5ede868265e7b303a5eee96fbfc321","observation_id":"638bcc91-5ef2-475b-a47f-6f2599c2e29d","resolution":{"observed_at":"2026-08-15T14:37:21.557527Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2401.07886/citation-record","integrity":"/paper/2401.07886/integrity","json":"/paper/2401.07886/citation-record.json","paper":"/paper/2401.07886"},"outbound":[],"paper":{"arxiv_id":"2401.07886","last_updated":"2024-07-15T03:54:20Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T14:27:21.818959Z","submitted_at":"2024-01-15T18:28:17Z","title":"Learned Best-Effort LLM Serving"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.07886."}