{"as_of":"2026-08-10T09:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54416e8d7c6257b0beef60e0244f9ab6e56cb49c85a0ab1a5d7536d74d669ef8","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:35:54.202665Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":11,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-06T14:35:54.202665Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18546","last_updated":"2025-07-24T16:11:14Z","snapshot_observed_at":"2026-08-09T11:06:31.124414Z","submitted_at":"2025-07-24T16:11:14Z","title":"GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T14:35:54.202665Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2507.18546"},"observation_digest":"sha256:a5ee6be1ae58018da59ac2db6038858309ba521694b4ea55de7a15521a8e8e84","observation_id":"d3b2ad4d-476b-4c80-8271-06a02f4ec6a3","resolution":{"observed_at":"2026-08-06T14:35:54.202665Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-04T12:59:00.357170Z","title":"Building efficient universal classifiers with natural language inference","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.01427","last_updated":"2026-07-30T00:32:01Z","snapshot_observed_at":"2026-08-04T12:58:57.066330Z","submitted_at":"2025-10-01T20:06:48Z","title":"A Tale of LLMs and Induced Small Proxies: Scalable Small Language Models for Knowledge Mining","version":4},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-04T12:59:00.357170Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2510.01427"},"observation_digest":"sha256:a045ec31a0289c4fffb66aabd0678238a561c7f05e46f54618bcc7f888097a49","observation_id":"f039a53d-3fc9-49a6-8bf5-e03114e1ffe0","resolution":{"observed_at":"2026-08-04T12:59:00.357170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":"2312.17543","doi":"10.48550/arxiv.2312.17543","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Building Efficient Universal Classifiers with Natural Language Inference; 2023","venue":"arXiv (Cornell University)","work_id":"cadb2fe3-fdae-484f-aa36-1bb1c8573d72","year":2023},"citing_paper":{"arxiv_id":"2605.01180","last_updated":"2026-05-02T01:06:17Z","snapshot_observed_at":"2026-07-06T23:14:29.125042Z","submitted_at":"2026-05-02T01:06:17Z","title":"Ideological discrepancy between publishers and news content is linked with audience engagement and consensus on Facebook","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-10T15:53:40.024017Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2605.01180"},"observation_digest":"sha256:6baacaf6548b68f2ead52d1a998024172d68b4a59c47de45d647ee88eb62ca02","observation_id":"5dfa93a9-2996-45cf-9132-9b134cb63b01","resolution":{"observed_at":"2026-05-10T15:55:35.002402Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":"2312.17543","doi":"10.48550/arxiv.2312.17543","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Building Efficient Universal Classifiers with Natural Language Inference; 2023","venue":"arXiv (Cornell University)","work_id":"cadb2fe3-fdae-484f-aa36-1bb1c8573d72","year":2023},"citing_paper":{"arxiv_id":"2606.08457","last_updated":"2026-06-07T05:14:26Z","snapshot_observed_at":"2026-08-01T23:34:27.733911Z","submitted_at":"2026-06-07T05:14:26Z","title":"The Consistency Illusion: How Multi-Agent Debate Hides Reasoning Misalignment","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-06-27T17:56:09.877800Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2606.08457"},"observation_digest":"sha256:85b8b7777079610e7c33088ea65400579bafa836f3a320134f4b7878a835d90f","observation_id":"f867a682-9ded-4997-9678-7f6266a8cf69","resolution":{"observed_at":"2026-07-02T23:47:27.590359Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":"2312.17543","doi":"10.48550/arxiv.2312.17543","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Building Efficient Universal Classifiers with Natural Language Inference; 2023","venue":"arXiv (Cornell University)","work_id":"cadb2fe3-fdae-484f-aa36-1bb1c8573d72","year":2023},"citing_paper":{"arxiv_id":"2606.10126","last_updated":"2026-06-08T19:57:13Z","snapshot_observed_at":"2026-08-04T20:33:47.662321Z","submitted_at":"2026-06-08T19:57:13Z","title":"Pareto-Guided Teacher Alignment for Fair Personalized Text Generation","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-06-27T16:06:58.653836Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2606.10126"},"observation_digest":"sha256:4cb2d0742920309066475c1ada7c99df5cfaa310bc0870acbe6334d83840860c","observation_id":"c534f402-e0c2-4bf4-9f18-cf48e071f136","resolution":{"observed_at":"2026-06-27T16:41:03.662875Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":"2312.17543","doi":"10.48550/arxiv.2312.17543","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Building Efficient Universal Classifiers with Natural Language Inference; 2023","venue":"arXiv (Cornell University)","work_id":"cadb2fe3-fdae-484f-aa36-1bb1c8573d72","year":2023},"citing_paper":{"arxiv_id":"2606.19819","last_updated":"2026-06-18T05:48:37Z","snapshot_observed_at":"2026-08-08T10:44:10.560424Z","submitted_at":"2026-06-18T05:48:37Z","title":"CREDENCE: Claim Reduction for Decomposition & Enhanced Credibility -- Semantic Metrics and Convergence Analysis","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-06-26T17:56:54.438723Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2606.19819"},"observation_digest":"sha256:2431922b4b8c17fd089b62c1c540f6fe6de080b74ef9230751cf181848113d48","observation_id":"ffe8ef5b-a7b7-410c-a934-1eacaab9295c","resolution":{"observed_at":"2026-07-04T03:29:31.361584Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":"2312.17543","doi":"10.48550/arxiv.2312.17543","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Building Efficient Universal Classifiers with Natural Language Inference; 2023","venue":"arXiv (Cornell University)","work_id":"cadb2fe3-fdae-484f-aa36-1bb1c8573d72","year":2023},"citing_paper":{"arxiv_id":"2606.24734","last_updated":"2026-06-23T15:58:46Z","snapshot_observed_at":"2026-07-06T23:59:18.313042Z","submitted_at":"2026-06-23T15:58:46Z","title":"Task Decomposition for Efficient Annotation","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-06-26T00:00:16.588823Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2606.24734"},"observation_digest":"sha256:c88d38bf479aa2bebd3563fe1ff966169cd6ce03e8654e182b82cdd4cedd433e","observation_id":"ac8b724f-431b-4435-8aeb-63cdad1cec5f","resolution":{"observed_at":"2026-07-04T16:59:58.922859Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17543","snapshot_observed_at":"2026-07-11T04:43:58.910824Z","title":"Building efficient universal classifiers with natu- ral language inference","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.05626","last_updated":"2026-07-06T20:33:13Z","snapshot_observed_at":"2026-08-02T14:22:09.009888Z","submitted_at":"2026-07-06T20:33:13Z","title":"Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T04:43:58.910824Z"},"links":{"cited_paper":"/paper/2312.17543","citing_paper":"/paper/2607.05626"},"observation_digest":"sha256:61b2f4ffe64216fed723fa2ef6f0621e1a0951914f094937b97f555150953430","observation_id":"ee4eacc1-ff29-4d5d-b3e7-911bb7bb4e25","resolution":{"observed_at":"2026-07-11T04:43:58.910824Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2312.17543/citation-record","integrity":"/paper/2312.17543/integrity","json":"/paper/2312.17543/citation-record.json","paper":"/paper/2312.17543"},"outbound":[],"paper":{"arxiv_id":"2312.17543","last_updated":"2024-03-22T17:12:49Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T23:31:53.993242Z","submitted_at":"2023-12-29T10:18:36Z","title":"Building Efficient Universal Classifiers with Natural Language Inference"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2312.17543."}