{"as_of":"2026-08-08T05:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5079206e7f3139431055128a855ebbcafa4c42579a8f0e584abf932b1f1347d9","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:08:04.110426Z","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":"2026-05-17T00:18:43.787081Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.14656","last_updated":"2024-12-19T09:07:38Z","snapshot_observed_at":"2026-08-02T23:52:42.480802Z","submitted_at":"2024-12-19T09:07:38Z","title":"Length Controlled Generation for Black-box LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14656","snapshot_observed_at":"2026-08-07T15:08:04.110426Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16234","last_updated":"2025-06-11T02:36:18Z","snapshot_observed_at":"2026-08-08T01:49:56.190848Z","submitted_at":"2025-05-22T05:08:27Z","title":"LIFEBench: Evaluating Length Instruction Following in Large Language Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:08:04.110426Z"},"links":{"cited_paper":"/paper/2412.14656","citing_paper":"/paper/2505.16234"},"observation_digest":"sha256:dd234a037979170defcd5ea17899b7e16d54a7accd117b16d58e069b4b41434c","observation_id":"0a1bbbcf-23ea-4ed9-9ec2-9ab31402e39f","resolution":{"observed_at":"2026-08-07T15:08:04.110426Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14656","last_updated":"2024-12-19T09:07:38Z","snapshot_observed_at":"2026-08-02T23:52:42.480802Z","submitted_at":"2024-12-19T09:07:38Z","title":"Length Controlled Generation for Black-box LLMs","version":1},"cited_work":{"arxiv_id":"2412.14656","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.14656","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Length controlled generation for black-box llms","venue":null,"work_id":"e28df247-ebc0-486d-8ada-2200e1e4f4a7","year":2024},"citing_paper":{"arxiv_id":"2512.06938","last_updated":"2026-05-04T13:48:57Z","snapshot_observed_at":"2026-07-06T22:37:59.340166Z","submitted_at":"2025-12-07T17:43:18Z","title":"Progress Ratio Embeddings: An Impatience Signal for Robust Length Control in Neural Text Generation","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-17T00:17:36.043818Z"},"links":{"cited_paper":"/paper/2412.14656","citing_paper":"/paper/2512.06938"},"observation_digest":"sha256:11a1135d73ceac4d7e7e35ae9751837ad81e81a3fa31b1f2166c1bbdd3566180","observation_id":"6ee05182-8ac4-4bb4-889e-3061842e2f99","resolution":{"observed_at":"2026-05-17T00:18:43.789918Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14656","last_updated":"2024-12-19T09:07:38Z","snapshot_observed_at":"2026-08-02T23:52:42.480802Z","submitted_at":"2024-12-19T09:07:38Z","title":"Length Controlled Generation for Black-box LLMs","version":1},"cited_work":{"arxiv_id":"2412.14656","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.14656","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Length controlled generation for black-box llms","venue":null,"work_id":"e28df247-ebc0-486d-8ada-2200e1e4f4a7","year":2024},"citing_paper":{"arxiv_id":"2604.27039","last_updated":"2026-07-20T23:24:02Z","snapshot_observed_at":"2026-08-02T15:18:52.956023Z","submitted_at":"2026-04-29T17:09:21Z","title":"Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-07T10:42:27.644514Z"},"links":{"cited_paper":"/paper/2412.14656","citing_paper":"/paper/2604.27039"},"observation_digest":"sha256:e1aa5f08e5cd1b2dfeb13aa85aaa4421960c42ffe5c5ac4613dd33293c73442d","observation_id":"2ac7b93c-3c5d-4858-85e7-87d89e588f8d","resolution":{"observed_at":"2026-05-12T09:31:26.115532Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14656","last_updated":"2024-12-19T09:07:38Z","snapshot_observed_at":"2026-08-02T23:52:42.480802Z","submitted_at":"2024-12-19T09:07:38Z","title":"Length Controlled Generation for Black-box LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14656","snapshot_observed_at":"2026-08-02T15:28:11.601906Z","title":"Length controlled generation for black-box llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.27039","last_updated":"2026-07-20T23:24:02Z","snapshot_observed_at":"2026-08-02T15:18:52.956023Z","submitted_at":"2026-04-29T17:09:21Z","title":"Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-02T15:28:11.601906Z"},"links":{"cited_paper":"/paper/2412.14656","citing_paper":"/paper/2604.27039"},"observation_digest":"sha256:f2db470558ab479779feb6c5b7808720c094bc39e0e1eaad3a663c05bd3943a4","observation_id":"45c48c4c-0fcf-41b7-b899-9bc77ee71dfa","resolution":{"observed_at":"2026-08-02T15:28:11.601906Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.14656/citation-record","integrity":"/paper/2412.14656/integrity","json":"/paper/2412.14656/citation-record.json","paper":"/paper/2412.14656"},"outbound":[],"paper":{"arxiv_id":"2412.14656","last_updated":"2024-12-19T09:07:38Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-02T23:52:42.480802Z","submitted_at":"2024-12-19T09:07:38Z","title":"Length Controlled Generation for Black-box LLMs"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2412.14656."}