{"as_of":"2026-08-17T16:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:101e8d043d59937c0877800587c01b05d0d1b9fe02626a59a706bf6cd85834c1","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:44:43.595206Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T08:49:53.601807Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.05706","last_updated":"2025-01-10T04:32:19Z","snapshot_observed_at":"2026-08-16T12:59:23.941017Z","submitted_at":"2025-01-10T04:32:19Z","title":"Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05706","snapshot_observed_at":"2026-08-06T19:44:43.595206Z","title":"doi:10.1145/arXiv.2501.05706","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.05305","last_updated":"2025-07-07T08:03:49Z","snapshot_observed_at":"2026-08-17T15:55:40.512814Z","submitted_at":"2025-07-07T08:03:49Z","title":"Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T19:44:43.595206Z"},"links":{"cited_paper":"/paper/2501.05706","citing_paper":"/paper/2507.05305"},"observation_digest":"sha256:9c2ab2b98d7e3c2423806708b9b84829642e7f88331485edbff91df5a022c306","observation_id":"c091cb50-3bfd-4777-9b09-6d3f9741ba1b","resolution":{"observed_at":"2026-08-06T19:44:43.595206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05706","last_updated":"2025-01-10T04:32:19Z","snapshot_observed_at":"2026-08-16T12:59:23.941017Z","submitted_at":"2025-01-10T04:32:19Z","title":"Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness","version":1},"cited_work":{"arxiv_id":"2501.05706","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05706","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"4c150814-714e-4e80-87a3-383422a3923f","year":2025},"citing_paper":{"arxiv_id":"2604.18309","last_updated":"2026-05-20T11:27:05Z","snapshot_observed_at":"2026-08-13T21:36:42.500902Z","submitted_at":"2026-04-20T14:16:39Z","title":"From Program Slices to Causal Clarity: Evaluating Faithful, Actionable LLM-Generated Failure Explanations via Context Partitioning and LLM-as-a-Judge","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T04:31:10.547340Z"},"links":{"cited_paper":"/paper/2501.05706","citing_paper":"/paper/2604.18309"},"observation_digest":"sha256:510b63889a6c975d6146ea1e0a35d2c01a150c8bad85cc8e85a56ee4ea86767b","observation_id":"9e9f14b2-af60-4010-9123-2a6db7bb4726","resolution":{"observed_at":"2026-05-11T11:51:04.096652Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05706","last_updated":"2025-01-10T04:32:19Z","snapshot_observed_at":"2026-08-16T12:59:23.941017Z","submitted_at":"2025-01-10T04:32:19Z","title":"Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness","version":1},"cited_work":{"arxiv_id":"2501.05706","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05706","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"4c150814-714e-4e80-87a3-383422a3923f","year":2025},"citing_paper":{"arxiv_id":"2604.18309","last_updated":"2026-05-20T11:27:05Z","snapshot_observed_at":"2026-08-13T21:36:42.500902Z","submitted_at":"2026-04-20T14:16:39Z","title":"From Program Slices to Causal Clarity: Evaluating Faithful, Actionable LLM-Generated Failure Explanations via Context Partitioning and LLM-as-a-Judge","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-21T08:47:46.121108Z"},"links":{"cited_paper":"/paper/2501.05706","citing_paper":"/paper/2604.18309"},"observation_digest":"sha256:9531f258e957c97fbaf6d8a223afdbcb01e1e2124036968db00edfdead8c5d93","observation_id":"0ede6b3f-0f9f-43f9-8404-eb753f865c31","resolution":{"observed_at":"2026-05-21T08:49:53.603489Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.05706/citation-record","integrity":"/paper/2501.05706/integrity","json":"/paper/2501.05706/citation-record.json","paper":"/paper/2501.05706"},"outbound":[],"paper":{"arxiv_id":"2501.05706","last_updated":"2025-01-10T04:32:19Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-16T12:59:23.941017Z","submitted_at":"2025-01-10T04:32:19Z","title":"Debugging Without Error Messages: How LLM Prompting Strategy Affects Programming Error Explanation Effectiveness"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.05706."}