{"as_of":"2026-08-16T00:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dffa40be14ed556a66f46b15209c0590cf96fa8f4f776bea75201f661ddda05b","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T19:29:18.384567Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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":"2026-05-13T04:50:43.547037Z","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":"2026-05-13T04:52:16.682660Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"cited_work":{"arxiv_id":"2501.10150","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.10150","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2501.10150 , year=","venue":null,"work_id":"0c3e6483-9652-4cde-b08f-fb4c0b3cfe15","year":null},"citing_paper":{"arxiv_id":"2605.12299","last_updated":"2026-05-12T15:52:30Z","snapshot_observed_at":"2026-08-14T22:35:48.833458Z","submitted_at":"2026-05-12T15:52:30Z","title":"GKnow: Measuring the Entanglement of Gender Bias and Factual Gender","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-05-13T04:50:43.547037Z"},"links":{"cited_paper":"/paper/2501.10150","citing_paper":"/paper/2605.12299"},"observation_digest":"sha256:c8bca45a34fcdef6184cdb0a1959ec9ffffecc51baafa2c46c17ac6dd78b5793","observation_id":"c8f5c3bc-9248-4fdf-ba30-c6e0e9884192","resolution":{"observed_at":"2026-05-13T04:52:16.684278Z","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/2501.10150/citation-record","integrity":"/paper/2501.10150/integrity","json":"/paper/2501.10150/citation-record.json","paper":"/paper/2501.10150"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.184741Z","title":"URL: \" 'urlintro :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.184741Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:f07cad5649f0a24bffd9a35e424d6a6747cce833b7d119d92e1e588c6829f302","observation_id":"774c1f8d-d9ba-49d0-9046-fac266a8c5d6","resolution":{"observed_at":"2026-08-10T19:29:18.184741Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.190869Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.190869Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:7273413c333bd7f5b9d2c56a8d5ec2ec2a5cea35d14f52ce32d8180b3d82d087","observation_id":"01b3440d-4f94-4333-930f-cc28bfdec7b5","resolution":{"observed_at":"2026-08-10T19:29:18.190869Z","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":"2026-08-10T19:29:19.066926Z","title":null,"venue":null,"work_id":"223eff1c-ad63-4145-a65d-55f7e3acad52","year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.196032Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:efd1e7a777285e1628d52a8f2b1e8d1971744f35a767a4864cb7807eeacfd825","observation_id":"aa47acd4-82d5-466d-b6c9-cea2e71b55ca","resolution":{"observed_at":"2026-08-10T19:29:19.071827Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:19.050774Z","title":"Zou, Venkatesh Saligrama, and Adam Tauman Kalai","venue":null,"work_id":"bb0f447c-3ad0-4fea-8786-4a68c500183b","year":2016},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.201090Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:7fb9b817818042e07dda523cb3fcb245f2131383e9286ee0ec003ec946512be7","observation_id":"988e57cf-42f7-41b2-8740-557725d2beb3","resolution":{"observed_at":"2026-08-10T19:29:19.055776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05457","last_updated":"2018-03-14T18:04:21Z","snapshot_observed_at":"2026-08-14T19:36:07.505691Z","submitted_at":"2018-03-14T18:04:21Z","title":"Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.05457","snapshot_observed_at":"2026-08-10T19:29:18.205518Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.205518Z"},"links":{"cited_paper":"/paper/1803.05457","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:0de035adc795f54bc4707d719e19c704bd72ea8d25a110685b0ec47538d59010","observation_id":"b77e0486-a28f-444a-b11b-671610cfb39f","resolution":{"observed_at":"2026-08-10T19:29:18.205518Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.210619Z","title":"Wallach, Jennifer T","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.210619Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:9f319ea43f8a2160f4c978caa4254484d6e23ec3fb6607b5f3a496b9220c756d","observation_id":"036ff404-13b9-48d5-b971-6437bb2212ba","resolution":{"observed_at":"2026-08-10T19:29:18.210619Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.215158Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.215158Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:d050579f7d80087b8fd46e72b2e643350e18d41ad6ce959a01c6282e75aa1d91","observation_id":"d9db25e0-11af-4de8-854c-0cd87564e760","resolution":{"observed_at":"2026-08-10T19:29:18.215158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-10T19:29:18.219702Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.219702Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:89ed1e6582200a2fc9e4bb51dd02b0cef074f4ac83bcafc3f1a4e952065f9e29","observation_id":"f71fecd2-ec47-460f-b8aa-7a0967e2fa3c","resolution":{"observed_at":"2026-08-10T19:29:18.219702Z","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":"2026-08-10T19:29:19.035546Z","title":null,"venue":null,"work_id":"4b8d626c-034f-4d45-9f15-fae36da68823","year":1983},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.224762Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:b494fbd36575b5fd6d1ba4206987b2a52642e177613786a7dc9501d843d611eb","observation_id":"05e6dbd9-0dd7-4548-8d73-6919e32300d8","resolution":{"observed_at":"2026-08-10T19:29:19.040365Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2022.findings-naacl.199","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.601418Z","title":null,"venue":null,"work_id":"64ad1a20-d0a8-4a96-8db6-0b8f85eb8dbb","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.229042Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:ee294baf119046e405a5f0d22f0e3925c957a55a9fb3d0525a8daab5686f8b10","observation_id":"93425c80-66e3-4ed6-a085-c978f1bc75c7","resolution":{"observed_at":"2026-08-10T19:29:18.605886Z","resolver_source":"doi","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.233423Z","title":"Gallegos, Ryan A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.233423Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:ff4c93bd800e58b6f215c3ae44452d994d36ac45c35bdccf3c057cc3a0c7760f","observation_id":"d87cedd1-8a0c-4633-b024-e04342fb02eb","resolution":{"observed_at":"2026-08-10T19:29:18.233423Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.238512Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.238512Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:e85adef30290020e8808039509dc79a4ce10e6a0fa8094d8267b327146ef780e","observation_id":"83029774-4f58-4ef7-a32b-2eb7e6b49bb1","resolution":{"observed_at":"2026-08-10T19:29:18.238512Z","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":"2026-08-10T19:29:19.019595Z","title":null,"venue":null,"work_id":"4b8aac92-e9a6-4d56-a778-05d28fe5cfd8","year":2002},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.243433Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:8851924c59883b61e77babaf3552595195358253281f9570308e2d05fca768e8","observation_id":"6a3f7834-37c0-4c48-a35a-e767b17e87c8","resolution":{"observed_at":"2026-08-10T19:29:19.024389Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.248304Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.248304Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:d4a576a9ffd6776cb3629dea7c22786fee85e0a40e5cf378e597582d083e6d07","observation_id":"d0ed2610-cbfe-433a-a021-192fdaca7564","resolution":{"observed_at":"2026-08-10T19:29:18.248304Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.253072Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.253072Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:bac6a9d1a03832dc58fb8604ca2f7bcd4e567d3b97799d7d3bd446354992553e","observation_id":"4eb31b4f-a951-4639-ac30-8ae75a697a20","resolution":{"observed_at":"2026-08-10T19:29:18.253072Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.257860Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.257860Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:9856c492bbc8ab0597ec84fbf0502791ec35ece6adfc4d4fdafa88e990c63647","observation_id":"baa5e5fb-a856-43cd-a31e-f568291da78a","resolution":{"observed_at":"2026-08-10T19:29:18.257860Z","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":"2026-08-10T19:29:18.984345Z","title":null,"venue":null,"work_id":"803df2a7-159e-4871-bf57-6b1523bc7f2c","year":2020},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.262536Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:f9376a91c2e20591f023c594c08685c7cab4a238d3cf5dee26767db6d8810379","observation_id":"44774643-1ce8-48ad-8171-a59de37a2594","resolution":{"observed_at":"2026-08-10T19:29:18.989349Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.970877Z","title":null,"venue":null,"work_id":"bdf28891-51ad-4a61-a2a8-0f78235ae7f4","year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.267098Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:9672358546403e8c90516023442db8bdcb0b775ac28d9669aa9a460b815544e1","observation_id":"93425822-f890-4c17-aaa2-29e1103544f2","resolution":{"observed_at":"2026-08-10T19:29:18.975086Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.271544Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.271544Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:dbf50996dabe02f9d5bc9f70957984472f55331eb275f61a1f3cae67b58cd8ff","observation_id":"1aa94e39-3d88-47a0-b757-0be6d825f437","resolution":{"observed_at":"2026-08-10T19:29:18.271544Z","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":"10.18653/v1/2022.gebnlp-1.3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.548266Z","title":null,"venue":null,"work_id":"8ff9433c-0cff-415f-acef-bf60de864440","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.276389Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:b9bb6792bd9ac2132c652839029f3c4e1cdc9a760098ab3f2749edf3bd989682","observation_id":"3c7322c6-b6c2-4968-9b85-b6958c3a1b19","resolution":{"observed_at":"2026-08-10T19:29:18.552748Z","resolver_source":"doi","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.280574Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.280574Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:e8093532dd1fd81554a61e013152de6111c6a5cfb1c4a6a7d982da15f33e3a38","observation_id":"768c7fe8-45eb-41a6-b73b-4fb8baa9f61d","resolution":{"observed_at":"2026-08-10T19:29:18.280574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08747","last_updated":"2025-01-05T04:09:00Z","snapshot_observed_at":"2026-08-16T00:12:56.001802Z","submitted_at":"2023-08-17T02:53:23Z","title":"An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08747","snapshot_observed_at":"2026-08-10T19:29:18.284608Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.284608Z"},"links":{"cited_paper":"/paper/2308.08747","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:f8bea7408316377ff8520ceabda215c5840385b0b7081e80e19d07048e5f8ca7","observation_id":"badb1221-f442-4e8a-8538-a1d76134580c","resolution":{"observed_at":"2026-08-10T19:29:18.284608Z","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":"2026-08-10T19:29:18.946518Z","title":null,"venue":null,"work_id":"1aa2bb0d-849d-4858-af5a-b8dce7774050","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.288991Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:5a15a64df135e1623a04e09fbbf2e22cf853fbb6454c73da63988cb48fd1fb01","observation_id":"a818bb9d-1a28-4b21-bdcc-645de2049d8f","resolution":{"observed_at":"2026-08-10T19:29:18.951345Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.929847Z","title":"Andonian, Yonatan Belinkov, and David Bau","venue":null,"work_id":"07298fd2-279b-4530-9cd5-d5f7640d2d20","year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.293153Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:2edb72b0ff7314d038ef358bef7b818c618ddb0dc4d18f15e6472c84191e2ba7","observation_id":"da437765-b4ed-4e18-9358-cf7bea9b68ad","resolution":{"observed_at":"2026-08-10T19:29:18.935223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07843","last_updated":"2016-09-26T04:06:13Z","snapshot_observed_at":"2026-07-06T05:12:10.387914Z","submitted_at":"2016-09-26T04:06:13Z","title":"Pointer Sentinel Mixture Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07843","snapshot_observed_at":"2026-08-10T19:29:18.297410Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.297410Z"},"links":{"cited_paper":"/paper/1609.07843","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:1f6fcc371f89fc151e255b3ac58d08ed50b38e6c0b650bb993b416434591b5f3","observation_id":"e3175dc8-dccc-4b20-a5e9-431d6d99356c","resolution":{"observed_at":"2026-08-10T19:29:18.297410Z","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":"2026-08-10T19:29:18.913631Z","title":null,"venue":null,"work_id":"05a40296-a28c-46c4-8750-54d07acf65a1","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.301765Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:6d8f6f5915495946043355c50445ceb49b2d9e75a53e7e34d394ed67b74d86b7","observation_id":"00f71aa4-0548-4c52-b27b-b0594bae741d","resolution":{"observed_at":"2026-08-10T19:29:18.919361Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.305765Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.305765Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:890102b1b66e96700cc2c0a88525871add3dafb2a47e52b3fc414b547a219db0","observation_id":"0fb7f323-2f96-496c-8e24-f226611877e7","resolution":{"observed_at":"2026-08-10T19:29:18.305765Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.310727Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.310727Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:5b292183d80e8bf81bde5cc644c956232c04e21dcb67e05d21de98da451006c9","observation_id":"9fa93072-2385-4c86-946c-214db0e39d2c","resolution":{"observed_at":"2026-08-10T19:29:18.310727Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.314929Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.314929Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:d3362a916257e48054ef1ad1bf4c4c4a1c97eb420ef71a2ff8e0a113cd1fdbf6","observation_id":"0c6c6a77-8178-486d-a7fe-44d842d4f235","resolution":{"observed_at":"2026-08-10T19:29:18.314929Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.319143Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.319143Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:3ab94f42d56233603b405dd79ec471d11636eef2fc9aea1e55ec5fcce53116f6","observation_id":"a6a8119b-5f14-4275-9cc4-eae16b9847e5","resolution":{"observed_at":"2026-08-10T19:29:18.319143Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.323449Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.323449Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:09b92702d0f2fc7bf435c3d8bb60b308da299481ea65d2dfca715a21dc68da2f","observation_id":"a5a312eb-8cd9-4cfe-b9c6-ef8acd7702a6","resolution":{"observed_at":"2026-08-10T19:29:18.323449Z","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":"2026-08-10T19:29:18.889715Z","title":null,"venue":null,"work_id":"77a2931a-c983-4005-9dd8-f0431ae94596","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.328130Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:86d0fbc2dd5945e2c587a42b322817ae53879bed332412c80a0218f2cce9820b","observation_id":"134cd8d5-81c2-4249-be4f-6b07087e6ad1","resolution":{"observed_at":"2026-08-10T19:29:18.894083Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.332587Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.332587Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:e69a6face82a3ce83951bbcd740e2391b108648cf5382e80db959a20c9715c42","observation_id":"5930972f-e603-4a16-8ab7-237e92c80816","resolution":{"observed_at":"2026-08-10T19:29:18.332587Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.336847Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.336847Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:75027801692c95a1ccbbbb939f99fe7e7212e1462c8546bf0f68384d87a8265a","observation_id":"4602873d-cd5e-44d6-aef2-c505d300161b","resolution":{"observed_at":"2026-08-10T19:29:18.336847Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.341249Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.341249Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:c0489f5f4873394d7fc13ffa8ee22122ff39c66b57b495167a4efa19a77af976","observation_id":"691ad0bf-4196-4d0e-a4ad-4ae09e226509","resolution":{"observed_at":"2026-08-10T19:29:18.341249Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.14168","last_updated":"2021-12-28T14:54:18Z","snapshot_observed_at":"2026-08-13T17:07:43.440246Z","submitted_at":"2021-12-28T14:54:18Z","title":"A Survey on Gender Bias in Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.14168","snapshot_observed_at":"2026-08-10T19:29:18.345569Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.345569Z"},"links":{"cited_paper":"/paper/2112.14168","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:e9d61750e5f493556a9eb21209eb1afd8e8d7c3db3a6d3463ed39218275aaca4","observation_id":"e87bfb0c-e37c-4e86-8a43-b8546d5ad68a","resolution":{"observed_at":"2026-08-10T19:29:18.345569Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.350807Z","title":"Smith, and Luke Zettlemoyer","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.350807Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:a511bed6879fda508cc81da4a1fedcdbd4d5f2f6077b35fafed0fb187c8b1369","observation_id":"86660984-06ee-4b69-81d2-33325052e7c3","resolution":{"observed_at":"2026-08-10T19:29:18.350807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-10T19:29:18.355443Z","title":"Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, D","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.355443Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:10d64574c4b94b4e44f0c7c6d7a9941b8bf326150a387497b3ebb49a9cd29497","observation_id":"e893a6b9-bea2-4e0a-9201-9466b06b0221","resolution":{"observed_at":"2026-08-10T19:29:18.355443Z","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":"10.18653/v1/2022.gebnlp-1.8","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.447743Z","title":null,"venue":null,"work_id":"a7bfd7e9-0793-40e2-8947-8ccfb22cf86c","year":2022},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.360602Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:d21bbe9083e5e46e5aea92ebf166d7ccb03ebdf14cc1b116caed023be7804924","observation_id":"d582b6ee-4fc7-4802-aefc-509ff4199301","resolution":{"observed_at":"2026-08-10T19:29:18.453247Z","resolver_source":"doi","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"}},{"citation":{"cited_paper":{"arxiv_id":"2004.12265","last_updated":"2020-11-22T07:58:08Z","snapshot_observed_at":"2026-08-10T09:04:33.884910Z","submitted_at":"2020-04-26T01:53:03Z","title":"Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.12265","snapshot_observed_at":"2026-08-10T19:29:18.365361Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.365361Z"},"links":{"cited_paper":"/paper/2004.12265","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:553ab657be497e406fc2b82cd82eb09f304765d303409ffb5d9f076a6d19026c","observation_id":"53326970-c505-44ae-b9f4-3c5f042fd5ba","resolution":{"observed_at":"2026-08-10T19:29:18.365361Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.370327Z","title":"Zuidema, and Katrin Schulz","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.370327Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:0cc5d0ab07cb3007ab2e48d325381b4d90d7456eb56b249fe6c67ed404b84720","observation_id":"6438961c-7faf-4565-86cc-fc604a986cc4","resolution":{"observed_at":"2026-08-10T19:29:18.370327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08417","last_updated":"2024-06-03T01:28:06Z","snapshot_observed_at":"2026-08-15T00:44:06.600935Z","submitted_at":"2024-01-16T15:04:51Z","title":"Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.08417","snapshot_observed_at":"2026-08-10T19:29:18.374960Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.374960Z"},"links":{"cited_paper":"/paper/2401.08417","citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:78b6aee14fda3a2b31867a2a2f290e7e048f27ffdb53fb7c14a95269c808f19a","observation_id":"bd9a1e8a-8250-4b8d-b6e8-6327f3393ef7","resolution":{"observed_at":"2026-08-10T19:29:18.374960Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.379763Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.379763Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:76452a4109141179e4ee7bd619b61df2cd6b3c4058f026630cc07aada2ababdb","observation_id":"56bc6fb0-342d-4b5d-bc94-2547fd7cbb00","resolution":{"observed_at":"2026-08-10T19:29:18.379763Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T19:29:18.384567Z","title":"Mielke, Hanna Wallach, and Ryan Cotterell","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T19:29:18.384567Z"},"links":{"citing_paper":"/paper/2501.10150"},"observation_digest":"sha256:92880f28f2dd52e4d4deed3983bfb4110239edaf2af06d14c03836facd71ee48","observation_id":"ed0d613f-9333-4bb7-a2a7-54e8fb79ecb5","resolution":{"observed_at":"2026-08-10T19:29:18.384567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.10150","last_updated":"2025-01-30T20:11:45Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-15T14:35:37.401068Z","submitted_at":"2025-01-17T12:23:30Z","title":"Dual Debiasing: Remove Stereotypes and Keep Factual Gender for Fair Language Modeling and Translation"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":39,"verified_exact":3,"verified_fuzzy":2},"total_outbound_references":44},"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 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2501.10150."}