{"as_of":"2026-08-16T05:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:90c38dd4745382b4636fb77c3dba070bca0655ce99f3de7c85043565c9227016","coverage":[{"denominator":7,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T08:28:02.270283Z","state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2601.16946/citation-record","integrity":"/paper/2601.16946/integrity","json":"/paper/2601.16946/citation-record.json","paper":"/paper/2601.16946"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:28:02.270283Z","title":"PER\">Lina Berg</entity> joined <entity type=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.270283Z"},"links":{"citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:713902b6836cfcc7d274875b6cde7d7b48d814ee7c0529b4f6cbb096ae8e7e08","observation_id":"f5b5ddef-7d9c-40a4-8307-0806c7ee0950","resolution":{"observed_at":"2026-08-03T08:28:02.270283Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:28:02.262454Z","title":"We Need Structured Output","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.262454Z"},"links":{"citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:23f9941bdfcaef4e71b076bafa2cbbb23789ac8bb223149abca81bb589dd9138","observation_id":"b6a39b55-b45a-4dda-bc5d-bf080116cd58","resolution":{"observed_at":"2026-08-03T08:28:02.262454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:28:02.247342Z","title":"InProceed- ings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 4, V olume 1: Long Papers, pages 793–805, Vancouver, Canada","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.247342Z"},"links":{"citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:9225be4319bf1423ebd445fd55cf4127d2327b1012a1213e72c30da129e69893","observation_id":"74ee72dd-0a7a-4913-a478-0e5f3d62c5b8","resolution":{"observed_at":"2026-08-03T08:28:02.247342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:28:02.252237Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.252237Z"},"links":{"citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:63612d0d246c6c49666f41e0ec0c6bac9670ce96c5449ed9f72a90c80736243f","observation_id":"f6f5b985-fd74-460a-80ea-71917bd82aa1","resolution":{"observed_at":"2026-08-03T08:28:02.252237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09702","last_updated":"2023-08-19T21:27:51Z","snapshot_observed_at":"2026-08-09T04:46:02.275866Z","submitted_at":"2023-07-19T01:14:49Z","title":"Efficient Guided Generation for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09702","snapshot_observed_at":"2026-08-03T08:28:02.266163Z","title":"}▷Allow next input token or closing quote 12:t next ←sample fromM(Y)constrained toV copy 13:Appendt next toY 14:ift next is","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.266163Z"},"links":{"cited_paper":"/paper/2307.09702","citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:5efa3083eecfc31aaa991ec55e90e2dcc8495b9e6ae0c9db138bdad94c75daa6","observation_id":"5b1bb5bd-e949-4bb2-87ce-130475b52be2","resolution":{"observed_at":"2026-08-03T08:28:02.266163Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18626","last_updated":"2024-12-19T22:47:08Z","snapshot_observed_at":"2026-08-14T15:38:29.382000Z","submitted_at":"2024-12-19T22:47:08Z","title":"Why Do Large Language Models (LLMs) Struggle to Count Letters?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18626","snapshot_observed_at":"2026-08-03T08:28:02.255694Z","title":"InProceedings of the 2024 Conference on Empirical Methods in Natural Language Process- ing, EMNLP 2024, Miami, FL, pages 3017–3026, USA","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.255694Z"},"links":{"cited_paper":"/paper/2412.18626","citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:9dbfbbc4e25a016e5336572377065a16b0452dc64846734138881ae370204c51","observation_id":"ccb224bd-6820-4335-a0b7-bca1a7f03d8f","resolution":{"observed_at":"2026-08-03T08:28:02.255694Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T08:28:02.259289Z","title":"Zdenˇek Kasner and Ondˇrej Dušek","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T08:28:02.259289Z"},"links":{"citing_paper":"/paper/2601.16946"},"observation_digest":"sha256:bfcdd86ad10d68a62234698f98baf381455407220f669847d49b51e2cd1c5e62","observation_id":"8dbb3efb-be03-4cf5-a6a6-6f1cd37443ac","resolution":{"observed_at":"2026-08-03T08:28:02.259289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.16946","last_updated":"2026-07-08T13:26:38Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T14:44:40.215464Z","submitted_at":"2026-01-23T18:03:10Z","title":"Strategies for Span Labeling with Large Language Models"},"reference_resolution":{"displayed":7,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":7},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2601.16946."}