{"as_of":"2026-08-08T18:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2ed26470510b3dc4ced46f7a9685e43f77b5e8d0480a58afb1477d8d457b11e5","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T14:33:13.475257Z","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":"2026-05-19T03:37:00.884337Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14318","snapshot_observed_at":"2026-08-07T14:33:13.475257Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18458","last_updated":"2025-06-01T16:00:34Z","snapshot_observed_at":"2026-08-07T20:59:19.597449Z","submitted_at":"2025-05-24T01:57:12Z","title":"A Survey of LLM $\\times$ DATA","version":3},"reference_index":276,"source":"pdf_text","source_observed_at":"2026-08-07T14:33:13.475257Z"},"links":{"cited_paper":"/paper/2411.14318","citing_paper":"/paper/2505.18458"},"observation_digest":"sha256:afc298dc409e63081fb58a661700d4f80ebe114d576e5f7fbc295351e147a04d","observation_id":"d9682801-4383-4377-945e-38929b001639","resolution":{"observed_at":"2026-08-07T14:33:13.475257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14318","snapshot_observed_at":"2026-08-07T13:33:52.387698Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21598","last_updated":"2025-05-27T16:56:54Z","snapshot_observed_at":"2026-08-07T13:26:02.241328Z","submitted_at":"2025-05-27T16:56:54Z","title":"Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T13:33:52.387698Z"},"links":{"cited_paper":"/paper/2411.14318","citing_paper":"/paper/2505.21598"},"observation_digest":"sha256:c4fe3c023a0055455f2035f63b1dd580273892321d8a1d2a3f6fb06ca40991ba","observation_id":"a8254859-93c3-45ee-ba9e-011c5d60762b","resolution":{"observed_at":"2026-08-07T13:33:52.387698Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14318","snapshot_observed_at":"2026-08-07T00:40:26.250799Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13045","last_updated":"2025-08-24T10:01:04Z","snapshot_observed_at":"2026-08-08T06:33:39.031465Z","submitted_at":"2025-06-16T02:27:25Z","title":"Continual Learning for Generative AI: From LLMs to MLLMs and Beyond","version":4},"reference_index":138,"source":"pdf_text","source_observed_at":"2026-08-07T00:40:26.250799Z"},"links":{"cited_paper":"/paper/2411.14318","citing_paper":"/paper/2506.13045"},"observation_digest":"sha256:ee15b4264a5a7b8774ce17e063c351ff564768e4fbf437b66a04809be1a9dcdd","observation_id":"14371040-232c-4852-8230-a1d4896d103c","resolution":{"observed_at":"2026-08-07T00:40:26.250799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14318","snapshot_observed_at":"2026-08-06T17:28:02.450103Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.10920","last_updated":"2025-07-15T02:26:47Z","snapshot_observed_at":"2026-08-08T00:35:44.350932Z","submitted_at":"2025-07-15T02:26:47Z","title":"HanjaBridge: Resolving Semantic Ambiguity in Korean LLMs via Hanja-Augmented Pre-Training","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T17:28:02.450103Z"},"links":{"cited_paper":"/paper/2411.14318","citing_paper":"/paper/2507.10920"},"observation_digest":"sha256:317426b06a2726a8d9bed286d19bd49a0fc5ea416d0cd791e3d72c29f115f09c","observation_id":"8de84e0c-5445-4468-bda8-ef5f12e50b2d","resolution":{"observed_at":"2026-08-06T17:28:02.450103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training","version":2},"cited_work":{"arxiv_id":"2411.14318","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.14318","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2411.14318 (2024)","venue":null,"work_id":"fd2371ca-fe70-40f1-88ec-bf67f131275b","year":2024},"citing_paper":{"arxiv_id":"2507.15640","last_updated":"2026-04-12T09:28:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-21T14:01:54Z","title":"Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-19T03:36:50.366757Z"},"links":{"cited_paper":"/paper/2411.14318","citing_paper":"/paper/2507.15640"},"observation_digest":"sha256:3c320d688d7ad0bf6b4cff54cdb48bde6bb5344a29e48b779bae7f9c754f97b9","observation_id":"87026fe1-9069-4bff-970a-1a075510265e","resolution":{"observed_at":"2026-05-19T03:37:00.887186Z","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/2411.14318/citation-record","integrity":"/paper/2411.14318/integrity","json":"/paper/2411.14318/citation-record.json","paper":"/paper/2411.14318"},"outbound":[],"paper":{"arxiv_id":"2411.14318","last_updated":"2025-05-20T15:09:35Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T07:45:33.824127Z","submitted_at":"2024-11-21T17:10:02Z","title":"Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training"},"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 5 inbound Pith citation observations for arXiv:2411.14318."}