{"as_of":"2026-08-08T12:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4b76f6b9283675a4724d62b797d5268597b1aee5c4266fd7e5b284e626f2f588","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T10:27:28.018193Z","state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2509.05375/citation-record","integrity":"/paper/2509.05375/integrity","json":"/paper/2509.05375/citation-record.json","paper":"/paper/2509.05375"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:27:28.214595Z","title":"Language models are few-shot learners","venue":null,"work_id":"376a636d-605b-472a-8027-542b3e4bc331","year":1901},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.963857Z"},"links":{"citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:89961cd5a1ad2246bcdfe53a813447e80e2e1875a104855b36f6c56b4e810be6","observation_id":"017bfff1-9391-4ab3-9022-83c557e42153","resolution":{"observed_at":"2026-08-05T10:27:28.219509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06608","last_updated":"2025-02-26T18:59:01Z","snapshot_observed_at":"2026-07-06T18:28:24.821865Z","submitted_at":"2024-06-06T18:10:11Z","title":"The Prompt Report: A Systematic Survey of Prompt Engineering Techniques","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06608","snapshot_observed_at":"2026-08-05T10:27:27.993881Z","title":"The prompt report: A systematic sur- vey of prompt engineering techniques","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.993881Z"},"links":{"cited_paper":"/paper/2406.06608","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:4e15c88e4cbb54d56ea160456ddc5b897c17bf624122389a9297eaf1fb4eef47","observation_id":"cc1364d2-e983-4273-bb7b-393115185194","resolution":{"observed_at":"2026-08-05T10:27:27.993881Z","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":"2026-08-05T10:27:27.998844Z","title":"Taylor Sorensen, Joshua Robinson, Christo- pher Michael Rytting, et al","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.998844Z"},"links":{"citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:ddd30a5f2240e6ff69ca6a9339895bda971760a9d96a31348fee53265a37b3d1","observation_id":"385ea147-3bc0-47bb-8ded-7f23f9c1165a","resolution":{"observed_at":"2026-08-05T10:27:27.998844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.09261","last_updated":"2022-10-17T17:08:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-17T17:08:26Z","title":"Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.09261","snapshot_observed_at":"2026-08-05T10:27:28.003259Z","title":"Challenging big- bench tasks and whether chain-of-thought can solve them","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:28.003259Z"},"links":{"cited_paper":"/paper/2210.09261","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:018827f3f189e6b116705524c3b181a38dcf3d7eddffa82f0b29cbcb4524d7e8","observation_id":"c6b5da37-861f-45cb-bf0b-e9872a54811d","resolution":{"observed_at":"2026-08-05T10:27:28.003259Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:27:28.198644Z","title":"Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, and Tom Goldstein","venue":null,"work_id":"726b2821-7ad5-4cf2-8570-59d5e4acea70","year":2021},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.978789Z"},"links":{"citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:bcfd5e54abc9af29460f29207c9056a2c7263ff1f2c3a5218fc9911d7e9571ef","observation_id":"ea3624d3-6f52-4837-aacf-942b3fd89c04","resolution":{"observed_at":"2026-08-05T10:27:28.203645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09690","last_updated":"2021-06-10T18:20:59Z","snapshot_observed_at":"2026-08-04T17:24:45.675795Z","submitted_at":"2021-02-19T00:23:59Z","title":"Calibrate Before Use: Improving Few-Shot Performance of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09690","snapshot_observed_at":"2026-08-05T10:27:28.012925Z","title":"Calibrate before use: Improving few-shot performance of language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:28.012925Z"},"links":{"cited_paper":"/paper/2102.09690","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:4940869b394a18c9b108ab175f3077bf9fae8b1b8147bf2f3338861c77b1ac79","observation_id":"553866de-7244-428a-9558-ca78112819e6","resolution":{"observed_at":"2026-08-05T10:27:28.012925Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07910","last_updated":"2024-08-20T00:28:45Z","snapshot_observed_at":"2026-08-05T04:16:54.399572Z","submitted_at":"2023-12-13T05:58:34Z","title":"PromptBench: A Unified Library for Evaluation of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.07910","snapshot_observed_at":"2026-08-05T10:27:28.018193Z","title":"Promptbench: A unified library for evaluation of large language models.arXiv preprint arXiv:2312.07910,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:28.018193Z"},"links":{"cited_paper":"/paper/2312.07910","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:ef53d865e98fa4f6e02cfbba89b9b1f4096c3781f1b9dd2cb8a127bb664cf447","observation_id":"05aaff4a-e3e7-4ee0-ba8a-84952cae68f1","resolution":{"observed_at":"2026-08-05T10:27:28.018193Z","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":"10.1016/s0022-5193(89","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:27:28.069703Z","title":"Joel Lehman and Kenneth O Stanley","venue":null,"work_id":"394e03e4-ee93-4ea1-a90b-72e105e06c2a","year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":1989,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.974023Z"},"links":{"citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:bc4a2c67d5b38566c7f510b050c877f7c85e95dc8aa136d660b0c02a29da0e8f","observation_id":"bbbec2ed-972b-4139-b980-958e596643ff","resolution":{"observed_at":"2026-08-05T10:27:28.076578Z","resolver_source":"doi","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"}},{"citation":{"cited_paper":{"arxiv_id":"2111.01584","last_updated":"2021-11-02T13:20:01Z","snapshot_observed_at":"2026-07-06T12:04:35.968417Z","submitted_at":"2021-11-02T13:20:01Z","title":"Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems","version":1},"cited_work":{"arxiv_id":"2111.01584","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.01584","snapshot_observed_at":"2026-08-05T10:27:28.122157Z","title":"Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems","venue":"cs.LG","work_id":"7f2d2de7-ae22-4db7-b0d6-9ad925805f83","year":2021},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":1990,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:28.008198Z"},"links":{"cited_paper":"/paper/2111.01584","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:ac5939aa556711b084aa3e441865a3c6aa35171eb8564847776b70ce2085b2e8","observation_id":"dca3ad3b-d079-491d-80c7-8a362ee1e37b","resolution":{"observed_at":"2026-08-05T10:27:28.127813Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16797","last_updated":"2023-09-28T19:01:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-28T19:01:07Z","title":"Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16797","snapshot_observed_at":"2026-08-05T10:27:27.969158Z","title":"Promptbreeder: Self-referential self- improvement via prompt evolution","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.969158Z"},"links":{"cited_paper":"/paper/2309.16797","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:ad8db9780721de053fe86b192bc4774c83a58a41098dc9aaa2390af9b43bc4a7","observation_id":"86bfd0bf-7b02-408c-9ded-5cd7074d2500","resolution":{"observed_at":"2026-08-05T10:27:27.969158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1504.04909","last_updated":"2015-04-20T01:17:00Z","snapshot_observed_at":"2026-07-06T04:15:24.342522Z","submitted_at":"2015-04-20T01:17:00Z","title":"Illuminating search spaces by mapping elites","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1504.04909","snapshot_observed_at":"2026-08-05T10:27:27.983962Z","title":"Jean-Baptiste Mouret and Jeff Clune","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.983962Z"},"links":{"cited_paper":"/paper/1504.04909","citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:d21b728c362a0095cf99b0b4cfe770f81b1e3c7fb045301ae342babb3135cd12","observation_id":"da1af78f-6edc-4152-92ca-a5044569d92d","resolution":{"observed_at":"2026-08-05T10:27:27.983962Z","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":"2026-08-05T10:27:27.989065Z","title":"Stuart Russell and Peter Norvig","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T10:27:27.989065Z"},"links":{"citing_paper":"/paper/2509.05375"},"observation_digest":"sha256:4a7a21c4be0982995ef7ad449b18c11b8b01003ff4ea8fa5cc1a86d59675f3a8","observation_id":"4f2b4608-09bc-426b-a268-9f73e7c5bf8d","resolution":{"observed_at":"2026-08-05T10:27:27.989065Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.05375","last_updated":"2025-09-04T11:52:19Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-05T10:27:27.089203Z","submitted_at":"2025-09-04T11:52:19Z","title":"Characterizing Fitness Landscape Structures in Prompt Engineering"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":2,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":2},"total_outbound_references":12},"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 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2509.05375."}