{"as_of":"2026-08-18T13:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:90bc920b812afab4c09e068863b2981477b92e8135645152116e7c7e9d3d6eba","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:44:34.392483Z","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":5,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-10T18:01:38.632847Z","title":"Available: https://arxiv.org/abs/2409.08775","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.11709","last_updated":"2025-02-25T18:32:14Z","snapshot_observed_at":"2026-08-18T12:08:33.475479Z","submitted_at":"2025-01-20T19:41:42Z","title":"Towards Detecting Prompt Knowledge Gaps for Improved LLM-guided Issue Resolution","version":3},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-10T18:01:38.632847Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2501.11709"},"observation_digest":"sha256:9e4e1e9fe76f1bca8d01b023d33ff73cbecc2b91d1a7ee877dc0cdc9a0aa00b8","observation_id":"373e1eb8-8857-4959-806b-ea2147af7d4b","resolution":{"observed_at":"2026-08-10T18:01:38.632847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-16T11:44:34.392483Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.14764","last_updated":"2025-04-20T23:35:41Z","snapshot_observed_at":"2026-08-18T03:47:41.322963Z","submitted_at":"2025-04-20T23:35:41Z","title":"Steering Semantic Data Processing With DocWrangler","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:34.392483Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2504.14764"},"observation_digest":"sha256:b6ffbc65dcdb4ace8448db5caedc56769959058a7b6c67635b434ae93e6a7430","observation_id":"c55cb9b1-8948-4d1f-a267-b0aaef0e29b4","resolution":{"observed_at":"2026-08-16T11:44:34.392483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-16T10:07:00.798748Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.19037","last_updated":"2025-04-26T22:12:16Z","snapshot_observed_at":"2026-08-18T12:09:48.626868Z","submitted_at":"2025-04-26T22:12:16Z","title":"\"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T10:07:00.798748Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2504.19037"},"observation_digest":"sha256:7a37538f92c5847cf0e8621821dc93818155da1924dd3672b1576f43db7b656c","observation_id":"36c95f29-c502-440b-b495-5a0857dc77db","resolution":{"observed_at":"2026-08-16T10:07:00.798748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-15T23:39:20.477208Z","title":"arXiv preprint arXiv:2409.08775 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.04260","last_updated":"2026-07-25T04:59:07Z","snapshot_observed_at":"2026-08-17T04:55:06.353411Z","submitted_at":"2025-05-07T09:10:51Z","title":"Steerable Chatbots: Exploring Personalization Control Interfaces via LLM Activation Steering","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T23:39:20.477208Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2505.04260"},"observation_digest":"sha256:63a928c58176338646da7c72f0b7c9364ef184c7e11c98c5262c1d820af040e2","observation_id":"f4ee2232-c976-4c02-9873-a47688f21a07","resolution":{"observed_at":"2026-08-15T23:39:20.477208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-15T22:08:19.494724Z","title":"arXiv preprint arXiv:2409.08775 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.08063","last_updated":"2025-05-12T21:03:42Z","snapshot_observed_at":"2026-08-18T03:17:42.871358Z","submitted_at":"2025-05-12T21:03:42Z","title":"Who's the Leader? Analyzing Novice Workflows in LLM-Assisted Debugging of Machine Learning Code","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-15T22:08:19.494724Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2505.08063"},"observation_digest":"sha256:69cc3220292a9893ea19fbec9834dbd68bf2d0a956651066e45b114b801ffb1e","observation_id":"1633fada-4a8a-404a-b5b1-d59f88851230","resolution":{"observed_at":"2026-08-15T22:08:19.494724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-06T19:56:41.089970Z","title":"https://doi.org/10.48550/arXiv.2409.08775 arXiv:2409.08775 [cs]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.04185","last_updated":"2025-07-05T23:36:05Z","snapshot_observed_at":"2026-08-15T05:41:45.515211Z","submitted_at":"2025-07-05T23:36:05Z","title":"From Legal Text to Tech Specs: Generative AI's Interpretation of Consent in Privacy Law","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T19:56:41.089970Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2507.04185"},"observation_digest":"sha256:0fd8cd329d888d2aab73ffefae1fad90d49c8e5d9f33c60190f08791c143aa70","observation_id":"3269100d-8b72-4d52-9314-98151827520f","resolution":{"observed_at":"2026-08-06T19:56:41.089970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-06T16:09:18.973771Z","title":"What you say= what you want? teaching humans to articulate requirements for llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14418","last_updated":"2025-07-19T00:15:05Z","snapshot_observed_at":"2026-08-15T17:41:28.508110Z","submitted_at":"2025-07-19T00:15:05Z","title":"Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T16:09:18.973771Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2507.14418"},"observation_digest":"sha256:769d1724f9e1e615faf82f0f0243661092983fb74fe168e1851228d6d7385d23","observation_id":"83ef8830-eb2a-407b-922b-9c8f6c304d26","resolution":{"observed_at":"2026-08-06T16:09:18.973771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-06T05:46:52.659780Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.01279","last_updated":"2025-08-02T09:19:16Z","snapshot_observed_at":"2026-08-16T14:41:12.545453Z","submitted_at":"2025-08-02T09:19:16Z","title":"ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User Prompts","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T05:46:52.659780Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2508.01279"},"observation_digest":"sha256:4cc33291c93069f0707cc41eeeeb19381d4d9c3f927ecd0b83734faa27f35f81","observation_id":"fc0795e7-6612-49e2-ba90-189b793226dc","resolution":{"observed_at":"2026-08-06T05:46:52.659780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":"2409.08775","doi":"10.48550/arxiv.2409.08775","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.2409.08775 arXiv:2409.08775 [cs]","venue":"arXiv (Cornell University)","work_id":"1e67cb1c-498d-4539-a8a9-205a388cd719","year":2024},"citing_paper":{"arxiv_id":"2601.11848","last_updated":"2026-04-06T02:33:13Z","snapshot_observed_at":"2026-08-14T16:41:13.619020Z","submitted_at":"2026-01-17T00:34:32Z","title":"Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-16T14:09:33.786576Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2601.11848"},"observation_digest":"sha256:b8e8c236560bf9e17e6631c191db7c688b49ffe558336cc6b405bb1d2c0efacd","observation_id":"c8a8af8b-27cc-4599-bf07-fe854a1595ee","resolution":{"observed_at":"2026-06-30T02:16:06.474189Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use","version":3},"cited_work":{"arxiv_id":"2409.08775","doi":"10.48550/arxiv.2409.08775","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.08775","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.2409.08775 arXiv:2409.08775 [cs]","venue":"arXiv (Cornell University)","work_id":"1e67cb1c-498d-4539-a8a9-205a388cd719","year":2024},"citing_paper":{"arxiv_id":"2605.11240","last_updated":"2026-05-11T20:58:09Z","snapshot_observed_at":"2026-08-16T19:29:47.137363Z","submitted_at":"2026-05-11T20:58:09Z","title":"When to Ask a Question: Understanding Communication Strategies in Generative AI Tools","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-13T01:12:50.314892Z"},"links":{"cited_paper":"/paper/2409.08775","citing_paper":"/paper/2605.11240"},"observation_digest":"sha256:290ec43fee243b05de6d472a547924798491f00d93315201e0a4a831b2eee2de","observation_id":"f631af5d-1bfd-4d44-912b-6a0f61b19107","resolution":{"observed_at":"2026-06-30T02:16:06.474189Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.08775/citation-record","integrity":"/paper/2409.08775/integrity","json":"/paper/2409.08775/citation-record.json","paper":"/paper/2409.08775"},"outbound":[],"paper":{"arxiv_id":"2409.08775","last_updated":"2025-04-28T16:07:05Z","latest_version":3,"primary_category":"cs.HC","snapshot_observed_at":"2026-08-16T13:18:49.760992Z","submitted_at":"2024-09-13T12:34:14Z","title":"What Should We Engineer in Prompts? Training Humans in Requirement-Driven LLM Use"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2409.08775."}