{"as_of":"2026-08-08T08:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e891b68934e22347c35db02bd134740bce81cb5027265eda650395f1148be152","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:14:06.963550Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T14:30:41.299562Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.09782","last_updated":"2024-04-02T17:16:40Z","snapshot_observed_at":"2026-07-06T16:48:33.164024Z","submitted_at":"2023-11-16T11:02:49Z","title":"More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09782","snapshot_observed_at":"2026-08-07T15:14:06.963550Z","title":"More samples or more prompts? exploring effective in-context sampling for llm few-shot prompt engineering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15741","last_updated":"2025-05-21T16:48:28Z","snapshot_observed_at":"2026-08-07T23:11:28.276089Z","submitted_at":"2025-05-21T16:48:28Z","title":"Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:14:06.963550Z"},"links":{"cited_paper":"/paper/2311.09782","citing_paper":"/paper/2505.15741"},"observation_digest":"sha256:cd39857dbdf7def6ccd9edda07a1074ee67f4a299f9e135321aa364259da83b3","observation_id":"25e69010-ce46-43a0-8026-5f0c74a526b6","resolution":{"observed_at":"2026-08-07T15:14:06.963550Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09782","last_updated":"2024-04-02T17:16:40Z","snapshot_observed_at":"2026-07-06T16:48:33.164024Z","submitted_at":"2023-11-16T11:02:49Z","title":"More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering","version":2},"cited_work":{"arxiv_id":"2311.09782","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.09782","snapshot_observed_at":"2026-08-07T14:30:41.299562Z","title":"More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering","venue":"cs.CL","work_id":"2dea7453-dbd2-4657-9de2-4dd9ae0161bb","year":2023},"citing_paper":{"arxiv_id":"2505.18754","last_updated":"2025-05-24T15:43:25Z","snapshot_observed_at":"2026-08-07T21:46:23.554024Z","submitted_at":"2025-05-24T15:43:25Z","title":"Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:30:37.891118Z"},"links":{"cited_paper":"/paper/2311.09782","citing_paper":"/paper/2505.18754"},"observation_digest":"sha256:f376b943c89ccee36e7de58889904a109c9c978b842a7dfcf3eb840748b5d117","observation_id":"2e3166c0-0ad9-4ada-a9c4-7fdcbda0040c","resolution":{"observed_at":"2026-08-07T14:30:41.303995Z","resolver_source":"local_arxiv","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/2311.09782/citation-record","integrity":"/paper/2311.09782/integrity","json":"/paper/2311.09782/citation-record.json","paper":"/paper/2311.09782"},"outbound":[],"paper":{"arxiv_id":"2311.09782","last_updated":"2024-04-02T17:16:40Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T16:48:33.164024Z","submitted_at":"2023-11-16T11:02:49Z","title":"More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering"},"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 2 inbound Pith citation observations for arXiv:2311.09782."}