{"as_of":"2026-08-09T06:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8cfbed37daaeaa5224c36c5c72d4f3d045f07364eff2e5413d92cef0d50341d5","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:07:40.923831Z","state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2502.08972/citation-record","integrity":"/paper/2502.08972/integrity","json":"/paper/2502.08972/citation-record.json","paper":"/paper/2502.08972"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:07:41.259240Z","title":"In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 13376–13390, Miami, Florida, USA","venue":null,"work_id":"725a1351-d0ac-40d6-8ccf-f9e0f19ca951","year":2024},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.840237Z"},"links":{"citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:927359c0da60ed8f7b29026e1c660e18a378fe8accf06fc88074e8884dd0345a","observation_id":"641b8ece-4aaa-4b02-b6fc-c8e914a036e0","resolution":{"observed_at":"2026-08-07T23:07:41.264693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:07:41.242196Z","title":"In The Twelfth Inter- national Conference on Learning Representations","venue":null,"work_id":"a9c9ef38-83ae-4ba9-a3b3-12df50bfaba0","year":2022},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.855008Z"},"links":{"citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:85f80ac65f06d3e321c778d2a509dd36a7f1bb1a3eb9c73a6d3121e6c7a4dbf3","observation_id":"e2d2df39-5190-4f31-b5d5-d15fbc146669","resolution":{"observed_at":"2026-08-07T23:07:41.247323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T23:07:41.225445Z","title":"Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E","venue":null,"work_id":"ded5c957-8ec3-4312-9e6d-07b1e9072e26","year":2023},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.861237Z"},"links":{"citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:d81b535880c4df65599b545c55f6c7350dabbb72b83077cbdac825cffd8dfef1","observation_id":"c4a79962-530d-4219-8c44-4d70c4f4262e","resolution":{"observed_at":"2026-08-07T23:07:41.230553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00267","last_updated":"2024-09-03T14:01:54Z","snapshot_observed_at":"2026-07-06T16:13:07.384791Z","submitted_at":"2023-09-01T05:53:33Z","title":"RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.00267","snapshot_observed_at":"2026-08-07T23:07:40.868032Z","title":"arXiv preprint arXiv:2309.00267","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.868032Z"},"links":{"cited_paper":"/paper/2309.00267","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:22a50305a9cbaa8221fb65fedba95c1b7da6ace42c7e0311cdcd0f9bf20977cd","observation_id":"47f23677-47d1-4924-8b29-dc910f864c3a","resolution":{"observed_at":"2026-08-07T23:07:40.868032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.11406","last_updated":"2024-06-05T03:29:31Z","snapshot_observed_at":"2026-07-06T15:18:45.940190Z","submitted_at":"2023-04-22T13:42:04Z","title":"LaMP: When Large Language Models Meet Personalization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.11406","snapshot_observed_at":"2026-08-07T23:07:40.889831Z","title":"Advances in Neu- ral Information Processing Systems, 36","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.889831Z"},"links":{"cited_paper":"/paper/2304.11406","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:dce7700a891472aba9cf24380887ae11f21385835ad338a8f59e1479470db41f","observation_id":"d284903a-5020-442a-aff8-315d4f529b1d","resolution":{"observed_at":"2026-08-07T23:07:40.889831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:07:41.198865Z","title":"In Pro- ceedings of the 7th Workshop on Representation Learning for NLP, pages 249–268, Dublin, Ireland","venue":null,"work_id":"090defbf-e72d-413a-b74a-96557ea6f496","year":2022},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.903708Z"},"links":{"citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:fb432e265d8d1a6ff7deb8871a7e6591e9e04b450af3df016880833ddd094e01","observation_id":"a5a27234-2aa8-4424-9b2b-63e87c5dacf5","resolution":{"observed_at":"2026-08-07T23:07:41.204902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07496","last_updated":"2024-06-11T17:32:21Z","snapshot_observed_at":"2026-07-06T18:29:04.294349Z","submitted_at":"2024-06-11T17:32:21Z","title":"TextGrad: Automatic \"Differentiation\" via Text","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07496","snapshot_observed_at":"2026-08-07T23:07:40.911008Z","title":"differentiation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.911008Z"},"links":{"cited_paper":"/paper/2406.07496","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:f3da3e2840e2b863f922da03e59df5bb5f4fa287e6ad4177ec84278bd2e5234b","observation_id":"ed0e6c6b-cf02-4142-b7ae-c2261268d6f7","resolution":{"observed_at":"2026-08-07T23:07:40.911008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05685","last_updated":"2023-12-24T02:01:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-09T05:55:52Z","title":"Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05685","snapshot_observed_at":"2026-08-07T23:07:40.918048Z","title":"arXiv preprint arXiv:2306.05685","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.918048Z"},"links":{"cited_paper":"/paper/2306.05685","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:a36bee4086c4b8073ee67cc77d7f9a149ef2ab5023bf70d728aba3930ad07a94","observation_id":"01d35325-085b-4855-86a2-76a52588ddae","resolution":{"observed_at":"2026-08-07T23:07:40.918048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:07:41.171730Z","title":"Write a news article that starts with the following sentence : article’s first sentence","venue":null,"work_id":"18c82aed-ba45-4199-bccd-74040ef26a23","year":2022},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.923831Z"},"links":{"citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:73a639c6de5e799d05d1a90b165420be8b8e97c53a7ad0074f4186a6074c08f9","observation_id":"72cd689f-68b9-4794-961b-b312ee44c94b","resolution":{"observed_at":"2026-08-07T23:07:41.180323Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.00747","last_updated":"2022-07-02T06:20:57Z","snapshot_observed_at":"2026-08-07T08:07:20.750026Z","submitted_at":"2022-07-02T06:20:57Z","title":"Rationale-Augmented Ensembles in Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.00747","snapshot_observed_at":"2026-08-07T23:07:40.896770Z","title":"Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":908,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.896770Z"},"links":{"cited_paper":"/paper/2207.00747","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:d224bc1f27512ff4c34c39644269faa6a7242dc7c999e5037f46f3010d06e78f","observation_id":"d46fd773-45ce-4497-b615-0a092f0d0b14","resolution":{"observed_at":"2026-08-07T23:07:40.896770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09180","last_updated":"2024-11-05T03:34:10Z","snapshot_observed_at":"2026-07-06T16:48:05.271182Z","submitted_at":"2023-11-15T18:19:58Z","title":"Pearl: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09180","snapshot_observed_at":"2026-08-07T23:07:40.874811Z","title":"Political Analysis, 16(4):372–403","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":2008,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.874811Z"},"links":{"cited_paper":"/paper/2311.09180","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:b5edf99c10caafe5cf9cbef4432e807375ab1a20b858142487772e76e30946c3","observation_id":"737765d3-0cbe-4f4f-a32c-327d523195ed","resolution":{"observed_at":"2026-08-07T23:07:40.874811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.09391","last_updated":"2022-04-20T11:12:53Z","snapshot_observed_at":"2026-08-05T03:17:20.264917Z","submitted_at":"2022-04-20T11:12:53Z","title":"You Are What You Write: Preserving Privacy in the Era of Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.09391","snapshot_observed_at":"2026-08-07T23:07:40.882804Z","title":"arXiv preprint arXiv:2204.09391","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.882804Z"},"links":{"cited_paper":"/paper/2204.09391","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:75ff0c166f3174b145899e76ef7369191857bebf8b0890083272985496d8d56a","observation_id":"b18839db-bf4e-4029-b66f-17873f25cda7","resolution":{"observed_at":"2026-08-07T23:07:40.882804Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.11564","last_updated":"2023-10-17T20:22:13Z","snapshot_observed_at":"2026-07-06T16:34:42.650324Z","submitted_at":"2023-10-17T20:22:13Z","title":"Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.11564","snapshot_observed_at":"2026-08-07T23:07:40.848965Z","title":"arXiv preprint arXiv:2310.11564","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.848965Z"},"links":{"cited_paper":"/paper/2310.11564","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:9c279314ca44243e57ab6472359f49a73537656cfc3b476b85ba5a964a91359f","observation_id":"679285f3-0603-4d59-a4c8-1b392630a1cc","resolution":{"observed_at":"2026-08-07T23:07:40.848965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08998","last_updated":"2023-08-21T10:23:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-17T14:12:48Z","title":"Reinforced Self-Training (ReST) for Language Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08998","snapshot_observed_at":"2026-08-07T23:07:40.833548Z","title":"Ritam Dutt, Kasturi Bhattacharjee, Rashmi Gangadhara- iah, Dan Roth, and Carolyn Rose","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning","version":3},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T23:07:40.833548Z"},"links":{"cited_paper":"/paper/2308.08998","citing_paper":"/paper/2502.08972"},"observation_digest":"sha256:ad4d2507d29bc970f8ebb96c6f47f70dda1d7a1166a81d2bedbdbc22622738ba","observation_id":"19e70be1-28df-4a21-a010-186b044c5d8c","resolution":{"observed_at":"2026-08-07T23:07:40.833548Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.08972","last_updated":"2025-04-05T11:57:48Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T23:00:39.818799Z","submitted_at":"2025-02-13T05:20:21Z","title":"Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":4},"total_outbound_references":14},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2502.08972."}