{"as_of":"2026-08-06T20:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aff198594ffe68ccf3689182375f9d3ed760d3d84e31eebf953d4e26acf2b7d5","coverage":[{"denominator":8,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T11:58:36.326809Z","state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T02:01:14.533941Z","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":"2026-05-11T23:01:15.317143Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"cited_work":{"arxiv_id":"2604.22335","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.22335","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","venue":"cs.CL","work_id":"39e71206-5b9f-4312-bf12-aa5150fd883e","year":2026},"citing_paper":{"arxiv_id":"2604.24608","last_updated":"2026-04-27T15:36:54Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T15:36:54Z","title":"Learning to Route Queries to Heads for Attention-based Re-ranking with Large Language Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-08T02:01:14.533941Z"},"links":{"cited_paper":"/paper/2604.22335","citing_paper":"/paper/2604.24608"},"observation_digest":"sha256:c98c5c582d823e29c4502631cb487514cf3fa4bad153658271efc1f8c9519c0e","observation_id":"cf0ea998-20b4-44e5-abb8-b6b16f77ab27","resolution":{"observed_at":"2026-05-11T23:01:15.320226Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2604.22335/citation-record","integrity":"/paper/2604.22335/integrity","json":"/paper/2604.22335/citation-record.json","paper":"/paper/2604.22335"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.06356","last_updated":"2024-05-19T12:24:40Z","snapshot_observed_at":"2026-07-31T23:51:34.493531Z","submitted_at":"2023-10-10T06:49:43Z","title":"A Semantic Invariant Robust Watermark for Large Language Models","version":3},"cited_work":{"arxiv_id":"2310.06356","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.06356","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A semantic invariant robust watermark for large language models.arXiv preprint arXiv:2310.06356","venue":null,"work_id":"d144cbc1-db79-4033-bf53-70e1ab41f15c","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"cited_paper":"/paper/2310.06356","citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:051407927e848c8fafd905e74939b23906bdbf1d3f1134eed28cc0be5aee6f5a","observation_id":"ef863d8d-af3c-4ac7-8685-b5cdc9314501","resolution":{"observed_at":"2026-05-11T19:26:09.035196Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03727","last_updated":"2025-04-24T22:33:02Z","snapshot_observed_at":"2026-07-06T19:28:01.764884Z","submitted_at":"2024-09-30T06:27:53Z","title":"FaithEval: Can Your Language Model Stay Faithful to Context, Even If \"The Moon is Made of Marshmallows\"","version":3},"cited_work":{"arxiv_id":"2410.03727","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.03727","snapshot_observed_at":"2026-07-03T15:08:33.398684Z","title":"Faitheval: Can your language model stay faithful to context, even if” the moon is made of marshmallows”.arXiv preprint arXiv:2410.03727","venue":null,"work_id":"5adc793e-4326-4694-ac4f-ffad61186121","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"cited_paper":"/paper/2410.03727","citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:00a0c3d726470a64ada9f7aaa1e67c9bebcc60713ecf88ede9ed3f0fd02cbda5","observation_id":"2bbb8105-898e-4c2e-80f6-019dd37271c0","resolution":{"observed_at":"2026-05-11T19:26:09.030214Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Shashi Narayan, Shay B","venue":null,"work_id":"68874bfd-1b6c-4ad4-8e82-88c48b4f984b","year":null},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:03616c17080e889d0ea45f790528ac967ba17bb86f3547c7e49669139516033b","observation_id":"93bd03ca-295c-48ec-bfc7-cf08a0afd7c3","resolution":{"observed_at":"2026-05-26T13:47:49.255807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"InProceedings of the 2018 Conference on Empirical Methods in Natural Lan- guage Processing, pages 1797–1807, Brussels, Bel- gium","venue":null,"work_id":"18013df4-283e-4b70-97ee-9ae0e36ff3a3","year":2018},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:cbbb8aa9bbb3f8601e5e85384b1e90f25eef894acb5b210173775d61339ffcc5","observation_id":"40bcf780-cbc1-452e-9d1c-e2ecd9d95824","resolution":{"observed_at":"2026-05-26T13:47:49.252384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17519","last_updated":"2025-02-17T07:07:19Z","snapshot_observed_at":"2026-07-06T18:36:42.830927Z","submitted_at":"2024-06-25T12:59:38Z","title":"Entropy-Based Decoding for Retrieval-Augmented Large Language Models","version":2},"cited_work":{"arxiv_id":"2406.17519","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.17519","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"337d9e89-ac17-4270-8bb1-b4a64ab0e384","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"cited_paper":"/paper/2406.17519","citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:a6fe7c63149849f08b6871b398a92b8d8000d3c0c316d42b397374df7b3f12b0","observation_id":"2f77a6d7-c3ac-470d-b53b-3eb316df9519","resolution":{"observed_at":"2026-05-11T19:26:09.017507Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"InProceedings of the 55th An- nual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1073– 1083, Vancouver, Canada","venue":null,"work_id":"849db4a7-665a-4820-ac6a-916245ceefdd","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:df3c9edb502062ff9d1137365513d4e1a6344041546bcec8c486e5236d82440f","observation_id":"c8633b02-a421-436d-9a69-1f1c7e99610a","resolution":{"observed_at":"2026-05-26T13:47:49.247862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.01313","last_updated":"2024-01-08T16:19:17Z","snapshot_observed_at":"2026-07-06T17:10:56.398607Z","submitted_at":"2024-01-02T17:56:30Z","title":"A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models","version":3},"cited_work":{"arxiv_id":"2401.01313","doi":"10.48550/arxiv.2401.01313","metadata_source":"pith","pith_arxiv_id":"2401.01313","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models","venue":"cs.CL","work_id":"e402e6ab-d714-4f4d-a865-0ac91b5ca92d","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"cited_paper":"/paper/2401.01313","citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:2b199b5937136de0b675590d901c6e6de4918fcf93a5d05edc86e7de7c92a9cb","observation_id":"dbaca172-215d-4fe4-9d3c-f7cb034c823d","resolution":{"observed_at":"2026-05-15T19:15:13.402482Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-05-20T09:57:43.198793+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-20T09:57:43.198793+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.10790","last_updated":"2024-09-16T23:52:41Z","snapshot_observed_at":"2026-07-06T19:16:28.014017Z","submitted_at":"2024-09-16T23:52:41Z","title":"Model Tells Itself Where to Attend: Faithfulness Meets Automatic Attention Steering","version":1},"cited_work":{"arxiv_id":"2409.10790","doi":"10.48550/arxiv.2409.10790","metadata_source":"arxiv_reference","pith_arxiv_id":"2409.10790","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"2024 , eprint =","venue":"arXiv (Cornell University)","work_id":"699f3a34-c015-4983-96c7-94fb101c668d","year":2024},"citing_paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T11:58:36.326809Z"},"links":{"cited_paper":"/paper/2409.10790","citing_paper":"/paper/2604.22335"},"observation_digest":"sha256:f639b1012ec950240f443effff1e2a146ca6baee68ef59cc6878ecb0638a2c5b","observation_id":"eb24bd27-3deb-44fa-bd7a-1d62965856d2","resolution":{"observed_at":"2026-05-11T19:26:09.026153Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.22335","last_updated":"2026-04-24T08:07:58Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-31T12:41:55.323609Z","submitted_at":"2026-04-24T08:07:58Z","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding"},"reference_resolution":{"displayed":8,"state_counts":{"malformed_identifier":1,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":3},"total_outbound_references":8},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 1 inbound Pith citation observation for arXiv:2604.22335."}