{"as_of":"2026-08-15T15:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:60f799027ce78317e541abc09f8fd20e3f16498887ead4093829272383cf230f","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":"2026-08-15T06:32:42.880941+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":"2026-08-12T18:10:37.040032Z","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":"2026-05-11T11:21:01.558506Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-12T18:10:37.040032Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.11829","last_updated":"2024-11-18T18:48:13Z","snapshot_observed_at":"2026-08-15T11:24:31.176844Z","submitted_at":"2024-11-18T18:48:13Z","title":"Tackling prediction tasks in relational databases with LLMs","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-12T18:10:37.040032Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2411.11829"},"observation_digest":"sha256:250ee9537d1fa0826b253374cbf067d70ab51ecfb4f039c806632eb767c7c196","observation_id":"55c977a2-c076-41d8-8b93-a8852f0e8f80","resolution":{"observed_at":"2026-08-12T18:10:37.040032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-08T17:40:15.242573Z","title":"Tabular representation, noisy operators, and impacts on table structure understanding tasks in llms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05878","last_updated":"2025-06-07T00:43:58Z","snapshot_observed_at":"2026-08-14T20:18:20.115012Z","submitted_at":"2025-02-09T12:26:05Z","title":"Retrieval-augmented Large Language Models for Financial Time Series Forecasting","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T17:40:15.242573Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2502.05878"},"observation_digest":"sha256:185894725772f602870b92794829dd5c02b5892838912b5c499be453ff8fefcf","observation_id":"11ecca52-16d4-4cd5-8f9b-21f69daa54e3","resolution":{"observed_at":"2026-08-08T17:40:15.242573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-07T14:34:11.569793Z","title":"arXiv preprint arXiv:2310.10358 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.18485","last_updated":"2025-05-24T03:19:36Z","snapshot_observed_at":"2026-08-14T14:41:43.527231Z","submitted_at":"2025-05-24T03:19:36Z","title":"The Prompt is Mightier than the Example","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:34:11.569793Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2505.18485"},"observation_digest":"sha256:bb7d23a8f4e2b2c8cdf216faa13af209515c9b63310080e46022f51ec8481a46","observation_id":"67b9fef7-e84a-4dd9-867f-4456ce43361b","resolution":{"observed_at":"2026-08-07T14:34:11.569793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-07T12:19:34.684720Z","title":"arXiv:2310.10358 [cs.CL] https://arxiv.org/abs/ 2310.10358","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.24716","last_updated":"2025-05-30T15:36:56Z","snapshot_observed_at":"2026-08-11T10:36:09.411298Z","submitted_at":"2025-05-30T15:36:56Z","title":"Towards Scalable Schema Mapping using Large Language Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T12:19:34.684720Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2505.24716"},"observation_digest":"sha256:4a6de87fb70b87a0113d181c4a39c1b830953fda477a430e9383c0011fe5d84c","observation_id":"9b85ecf9-d07e-4e01-9502-3fb47dfc197f","resolution":{"observed_at":"2026-08-07T12:19:34.684720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-07T10:19:11.854718Z","title":"Ananya Singha, José Cambronero, Sumit Gulwani, Vu Le, and Chris Parnin","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.05725","last_updated":"2025-06-06T04:07:55Z","snapshot_observed_at":"2026-08-15T11:22:56.115261Z","submitted_at":"2025-06-06T04:07:55Z","title":"Large Language Models are Good Relational Learners","version":1},"reference_index":607,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:11.854718Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2506.05725"},"observation_digest":"sha256:15f1bacff0b70cdd7760ccdf6f3f1f0728cf3478c60dbffbaa00546cbb64d593","observation_id":"00044d68-2d9b-49ad-ba13-558df667336f","resolution":{"observed_at":"2026-08-07T10:19:11.854718Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-06T21:26:14.856955Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.00152","last_updated":"2025-06-30T18:04:36Z","snapshot_observed_at":"2026-08-14T14:54:47.234685Z","submitted_at":"2025-06-30T18:04:36Z","title":"Table Understanding and (Multimodal) LLMs: A Cross-Domain Case Study on Scientific vs. Non-Scientific Data","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T21:26:14.856955Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2507.00152"},"observation_digest":"sha256:cde65c478dac7687f86b2ce580d32dca3fd96b3348b622ab5bdefcaba8e97f08","observation_id":"d4c0e185-d6b7-4c11-8635-216272cbf42c","resolution":{"observed_at":"2026-08-06T21:26:14.856955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-06T14:58:05.552491Z","title":"Tabular representa- tion, noisy operators, and impacts on table structure understanding tasks in llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17259","last_updated":"2025-07-23T06:56:34Z","snapshot_observed_at":"2026-08-14T05:10:17.092965Z","submitted_at":"2025-07-23T06:56:34Z","title":"Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T14:58:05.552491Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2507.17259"},"observation_digest":"sha256:9a5c4e8a93d248b515b666be3fdee54bafe0b313d013ea73426b2d0a3c22e3c9","observation_id":"d90d2a82-18ab-4457-8d0b-3e39a57d1bf5","resolution":{"observed_at":"2026-08-06T14:58:05.552491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-05T14:21:48.226509Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.21512","last_updated":"2025-08-29T10:51:41Z","snapshot_observed_at":"2026-08-08T23:50:08.737946Z","submitted_at":"2025-08-29T10:51:41Z","title":"Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-05T14:21:48.226509Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2508.21512"},"observation_digest":"sha256:ccf61e48576ff0f2bd07152da942e87e9fb754f058b97c0ecb05d70230c5b0af","observation_id":"bae76b8f-ea0b-4283-a4e4-79b6996b628d","resolution":{"observed_at":"2026-08-05T14:21:48.226509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-08-03T08:58:51.132309Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.15251","last_updated":"2026-06-28T17:05:49Z","snapshot_observed_at":"2026-08-14T13:24:00.714774Z","submitted_at":"2026-01-21T18:33:15Z","title":"The Effect of Scripts and Formats on LLM Numeracy","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-03T08:58:51.132309Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2601.15251"},"observation_digest":"sha256:b81288cda8cf6d4f76cc7a4fcb7032e4bfdca9f0379606c5bb41d9a4012d45b7","observation_id":"54f916f6-5538-474a-9c03-88708ea077d0","resolution":{"observed_at":"2026-08-03T08:58:51.132309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs","version":1},"cited_work":{"arxiv_id":"2310.10358","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.10358","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tabular representation, noisy operators, and impacts on table structure understanding tasks in LLM s","venue":null,"work_id":"dde535b7-655b-4714-b861-5cfa1b716420","year":2023},"citing_paper":{"arxiv_id":"2604.12491","last_updated":"2026-04-14T09:16:53Z","snapshot_observed_at":"2026-08-15T01:45:28.676413Z","submitted_at":"2026-04-14T09:16:53Z","title":"Calibrated Confidence Estimation for Tabular Question Answering","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-05-10T15:00:46.646913Z"},"links":{"cited_paper":"/paper/2310.10358","citing_paper":"/paper/2604.12491"},"observation_digest":"sha256:fe2f1f19f8f1cb3ced4d911f8d05fb640ae5fbfbb5502a48d8c4ddcc4d9782c5","observation_id":"f4ee7ddc-7127-409f-93a1-59e0c1019c31","resolution":{"observed_at":"2026-05-11T11:21:01.568629Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.10358/citation-record","integrity":"/paper/2310.10358/integrity","json":"/paper/2310.10358/citation-record.json","paper":"/paper/2310.10358"},"outbound":[],"paper":{"arxiv_id":"2310.10358","last_updated":"2023-10-16T12:51:24Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T05:48:31.008589Z","submitted_at":"2023-10-16T12:51:24Z","title":"Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2310.10358."}