{"as_of":"2026-08-11T12:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:528b7a7899689b71cfa788f57f8feaa86a2e2fc1594f99cc77abcec108c68b38","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T04:25:52.636009Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2412.18904/citation-record","integrity":"/paper/2412.18904/integrity","json":"/paper/2412.18904/citation-record.json","paper":"/paper/2412.18904"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:25:52.403739Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.403739Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:f8bb6ae4bae0095f0fbd50896f25dd5a5762bb47f4810a4422ec6f536e208172","observation_id":"6cb52d0d-b6ed-4bfe-b982-f7a57aaece49","resolution":{"observed_at":"2026-08-11T04:25:52.403739Z","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":"2026-08-11T04:25:52.411041Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.411041Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:a9036d5a82c0afc74ea03c7f01b26a96026e2e22f807780b1ffc4183fa36137b","observation_id":"fd365682-e7c1-444a-af48-a98ee84c8048","resolution":{"observed_at":"2026-08-11T04:25:52.411041Z","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":"2026-08-11T04:25:52.417325Z","title":"L.; Zippo, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.417325Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:8edda4e8ace8470b9cc848a789f9c05c063d062c776de0f3763b56295609e66c","observation_id":"55a7b7c8-810e-49b9-9714-5d2e2dd094a7","resolution":{"observed_at":"2026-08-11T04:25:52.417325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.01097","last_updated":"2019-12-09T20:02:37Z","snapshot_observed_at":"2026-08-06T00:22:10.318064Z","submitted_at":"2018-12-03T21:59:41Z","title":"LEAF: A Benchmark for Federated Settings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.01097","snapshot_observed_at":"2026-08-11T04:25:52.423409Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.423409Z"},"links":{"cited_paper":"/paper/1812.01097","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:3085ce1f6e1912e0a3f00a00b5359bd3a904a725096cb644bdbc9f2c2ba6d279","observation_id":"74adc55f-7bd5-4fbf-a450-fc40ead6d48b","resolution":{"observed_at":"2026-08-11T04:25:52.423409Z","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":"2026-08-11T04:25:52.429883Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.429883Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:a5ef43b9db97ec2ea7d54ddaaacf553bd98305690399101222c995cf8e13ab9a","observation_id":"65f60afc-4f2f-4a0c-8c87-ba1d3e004e03","resolution":{"observed_at":"2026-08-11T04:25:52.429883Z","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":"2026-08-11T04:25:53.318058Z","title":null,"venue":null,"work_id":"cc7f54a6-33e6-4ec9-a3dc-eaec00e78f51","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.435791Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:d805463746379b64b509823cc821b314058391d0562a6e4b2075929a85a03d2a","observation_id":"132bd143-c522-43d7-8399-bd93d163d107","resolution":{"observed_at":"2026-08-11T04:25:53.322667Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.303456Z","title":null,"venue":null,"work_id":"cd69e28b-5102-4e0f-8fb1-224c1af29a41","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.442094Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:c8259c2c53cda87703871279719011c5f8cdecd9a3f8eadaaefef14591ee8ff6","observation_id":"bb053711-84ab-43c7-b737-01918ab08513","resolution":{"observed_at":"2026-08-11T04:25:53.307987Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.287422Z","title":"S.; and Cheng, J","venue":null,"work_id":"a7e20d95-1439-42d4-9ab1-09bd279c37d7","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.447937Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:6c4ffc9cac6d8a51cbfa216fd9346b95fb5bc2509c6b3fa95a5a5e20c1c4371a","observation_id":"f5a45c7f-b090-4c44-ae63-296d4647fb4a","resolution":{"observed_at":"2026-08-11T04:25:53.292775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.271676Z","title":null,"venue":null,"work_id":"dfdc0573-577d-4b8b-be6e-7f5272bcec7c","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.453934Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:6b29c91704b8c8ec71f3f78e346822cd7d6207530214f50883e469c413882840","observation_id":"02a343a7-71eb-4674-af38-440f92846c41","resolution":{"observed_at":"2026-08-11T04:25:53.276720Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.255824Z","title":null,"venue":null,"work_id":"1e089e7f-00c6-48f5-bdfc-1de53d0d492f","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.458780Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:f8d8f2315d152018a7fe4bb494c5fa7bd7488ddc4422368d7a0ec28db00529fb","observation_id":"7b3a93df-ca84-4e8e-85c0-7ff00c179de2","resolution":{"observed_at":"2026-08-11T04:25:53.260969Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.239139Z","title":null,"venue":null,"work_id":"d4cd3ed8-ff41-4132-9d08-fa26e88f5827","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.463868Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:59f34c5283c2eca258ba9cba67005a7ad127b4bc927a761f60663d859cdb1c13","observation_id":"09a383be-3572-40fd-be80-f7d96371a1a6","resolution":{"observed_at":"2026-08-11T04:25:53.243801Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.222905Z","title":null,"venue":null,"work_id":"f5d6b222-2902-4fc0-b42f-53a01998f3a9","year":2009},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.469427Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:e4d8d5a70b4c46488bc7348a51da0a1cb9a26c55884c911b72dcedbd3d3a9e63","observation_id":"e8b591b5-6274-4fdf-bec1-6470b0d252d0","resolution":{"observed_at":"2026-08-11T04:25:53.227765Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.206766Z","title":null,"venue":null,"work_id":"0e24734e-3bed-4d01-a837-629508bd0a04","year":2024},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.473932Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:750004b08ed53ebee1ce62f2e201659fc12f511fc296fb579903236364cc7f70","observation_id":"61c204da-6e2b-4ec0-ac47-9e5566488846","resolution":{"observed_at":"2026-08-11T04:25:53.211785Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.191264Z","title":"J.; Chen, C.; and Duke, L","venue":null,"work_id":"94cc6315-a8d5-48d0-a9a8-bb21ab886a80","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.478210Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:18153b728af531e2c1316bde874abfe439d896cc4c903075887827e63768db2e","observation_id":"059960b2-7f5e-4671-a3b5-e66bf7f88cc2","resolution":{"observed_at":"2026-08-11T04:25:53.196368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.175401Z","title":null,"venue":null,"work_id":"302fc11b-3479-4054-b442-b8b40ac04c63","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.483886Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:5e1be079d900b6fd42cacc143aef2c67076cd8aec69114d16f7425af979d7710","observation_id":"26eebe5c-4a75-416c-ac6d-648c93c351ac","resolution":{"observed_at":"2026-08-11T04:25:53.180412Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.489049Z","title":"P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.489049Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:e06c5e5d2c51f59cfcaf5ce7ec6f9df108e0aa79f8923311b9a6dbd16495500f","observation_id":"197c40b8-e003-471d-a1db-ad8bbe4bf5c1","resolution":{"observed_at":"2026-08-11T04:25:52.489049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1610.05492","last_updated":"2017-10-30T20:52:14Z","snapshot_observed_at":"2026-07-06T05:15:00.158639Z","submitted_at":"2016-10-18T09:11:51Z","title":"Federated Learning: Strategies for Improving Communication Efficiency","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.05492","snapshot_observed_at":"2026-08-11T04:25:52.494033Z","title":"B.; Yu, F","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.494033Z"},"links":{"cited_paper":"/paper/1610.05492","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:54977966e6e3a2c185b2f42677481dbfeb01bd182543df67781313a9e0d0ef23","observation_id":"655ce55b-2527-43a4-bce6-e1ba86d0d104","resolution":{"observed_at":"2026-08-11T04:25:52.494033Z","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":"2026-08-11T04:25:52.500160Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.500160Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:c524c53aa1f7d397ed220a624e9e438fe4a278c39815e5d94f418dde4fbbb687","observation_id":"8dbdb067-1b3b-4cde-b647-ddc03a893c6a","resolution":{"observed_at":"2026-08-11T04:25:52.500160Z","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":"2026-08-11T04:25:53.139614Z","title":null,"venue":null,"work_id":"35cfb8d2-6bb2-45c2-8ab0-1cf81dc21366","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.505535Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:85fd09c0bd386de3ff41a56b2a2a79dfa89f04eb573fa19dd925aced553073f9","observation_id":"bc564874-c55c-4e01-b99d-2c9571b3be0d","resolution":{"observed_at":"2026-08-11T04:25:53.144984Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13263","last_updated":"2024-04-08T09:31:33Z","snapshot_observed_at":"2026-07-06T15:45:47.517122Z","submitted_at":"2023-06-23T02:19:52Z","title":"Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity","version":2},"cited_work":{"arxiv_id":"2306.13263","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.13263","snapshot_observed_at":"2026-08-11T04:25:52.730493Z","title":"Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity","venue":"cs.LG","work_id":"5b4f88d7-c56c-48e8-9c90-662b5100df08","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.511400Z"},"links":{"cited_paper":"/paper/2306.13263","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:35c89ab550a78cf177e8db54030631d5b595b640859a783e1b9fe4d282a9cc05","observation_id":"d12027da-8137-4d77-8a1d-a176329153c9","resolution":{"observed_at":"2026-08-11T04:25:52.735798Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.122919Z","title":"N.; Alstr m, T","venue":null,"work_id":"1dded487-296f-4bb1-a66a-16523878826c","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.517248Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:2e6bb0c50946f628ae1f203a8a7b115997f6b76a75decd0349a406187290f972","observation_id":"f99c0c97-69af-4f8e-8140-4aaad49b95f5","resolution":{"observed_at":"2026-08-11T04:25:53.128359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.106963Z","title":null,"venue":null,"work_id":"94e84eb5-b5d4-4884-841b-bce7ae316bb7","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.522369Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:9fdf2153844ed3f5a14fd13a1c07c73829ff1ae29ba12180e708d62fd9fe132c","observation_id":"dff8a13e-5943-4fbc-91a2-5443e4c65504","resolution":{"observed_at":"2026-08-11T04:25:53.111987Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.089064Z","title":null,"venue":null,"work_id":"26b16522-ee53-451f-ba4d-cd56bf91b49a","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.526789Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:8b4c70f3d389ae65e0e2127aca2117162d00655620f9d006e4c354ed35fa8422","observation_id":"d7e8fcaa-662b-41be-8110-8f1d0efb8dc4","resolution":{"observed_at":"2026-08-11T04:25:53.095394Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.072042Z","title":"K.; Talwalkar, A.; and Smith, V","venue":null,"work_id":"f4010cd1-eb97-4379-8d45-553192b5f20a","year":2020},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.532501Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:c22ce2197c1d0ae8cb0155c86bdfd5ca89f0c1278031a68c281ed14e21bcab9c","observation_id":"c4fb13a7-c691-498d-a333-cc87c367def5","resolution":{"observed_at":"2026-08-11T04:25:53.077004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.054797Z","title":"K.; Zaheer, M.; Sanjabi, M.; Talwalkar, A.; and Smith, V","venue":null,"work_id":"3cfd6e2c-bcbc-46a1-adf7-61dd12d4e0c1","year":2020},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.537117Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:a439106d7f47e5bd5a6dfd8bb2fccc13abae9715f12ed85f31dff01ee9c4bd51","observation_id":"cc33fc03-0b5d-4490-93cf-cd94742f12a2","resolution":{"observed_at":"2026-08-11T04:25:53.060390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10497","last_updated":"2020-02-14T22:48:28Z","snapshot_observed_at":"2026-08-06T20:49:35.004399Z","submitted_at":"2019-05-25T01:47:41Z","title":"Fair Resource Allocation in Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10497","snapshot_observed_at":"2026-08-11T04:25:52.541644Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.541644Z"},"links":{"cited_paper":"/paper/1905.10497","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:8b0d010570915065567d666c58ca8b1dddd47e846d26d7ce262943d43f9688a4","observation_id":"19960392-a9d7-4776-afbc-bdd0b2869d09","resolution":{"observed_at":"2026-08-11T04:25:52.541644Z","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":"2026-08-11T04:25:53.039468Z","title":null,"venue":null,"work_id":"96189552-c6b7-495d-a035-b17501754bb5","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.547080Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:bbb3ae8acf2bdfdd76ce0282d9aed74ed6b70365ae6850a44e5c85b43c97833b","observation_id":"62280101-ea02-44eb-b277-e6046b5d89ed","resolution":{"observed_at":"2026-08-11T04:25:53.044515Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.024121Z","title":null,"venue":null,"work_id":"2b6e1b7b-9136-43d0-beac-a0c91f782cc7","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.552402Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:c49049e5fc61f0f8595c422b5542b1817e453861173b23acacaf96304c40fe8d","observation_id":"a9104d8b-054a-421b-9bb8-843f6e0b8e0c","resolution":{"observed_at":"2026-08-11T04:25:53.029079Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:53.009022Z","title":null,"venue":null,"work_id":"a7a1fe70-a67d-450b-84cb-ebede9ca862e","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.556896Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:8608a96fa3f6406cb4e6c35ef0439b275f122e66a140b5a8d969451a0c223c62","observation_id":"93d8dd1c-fe66-4a6e-9fff-f265207f384f","resolution":{"observed_at":"2026-08-11T04:25:53.013708Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.561563Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.561563Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:90d9fdee9111604b6d4252ec78d84f77a9b74fa321a8b9d56c45c1edc359c5f8","observation_id":"dd5c9866-8a72-4d45-bb5a-5864118c3723","resolution":{"observed_at":"2026-08-11T04:25:52.561563Z","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":"2026-08-11T04:25:52.982510Z","title":null,"venue":null,"work_id":"7e7121f2-682f-4e49-a53c-16e17177323c","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.567195Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:eed04e06544482de995c9118cbadd6300c9eea8dc29a6c7c39fb0a1d78c47e36","observation_id":"0e419434-8cd1-4a33-8efb-c9afc9ce94af","resolution":{"observed_at":"2026-08-11T04:25:52.987392Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.966465Z","title":null,"venue":null,"work_id":"3dd0aa79-e04b-4b88-9480-e1e9e25d10a5","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.571767Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:150ed3e07fda97d9f8e6cdb057c8ba78dc6433ea88c2d0d020146f7c66a17307","observation_id":"99d99e1e-7bf5-4ff3-9df7-728d37d7c33a","resolution":{"observed_at":"2026-08-11T04:25:52.971365Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.948979Z","title":"R.; Dey, E.; Roy, N.; and Gangopadhyay, A","venue":null,"work_id":"57e0deef-60a2-4839-9a20-f59be7bf5833","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.576037Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:7646204c6247b3dd9e54de3dde8c65253d1cda879caf29ba91890e4c86e422fd","observation_id":"98a0a60d-2c36-4e7d-8070-86bbcf6b01d6","resolution":{"observed_at":"2026-08-11T04:25:52.954250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.933001Z","title":"P.; Xia, Y.; Wang, F.; Adeli, E.; Fei-Fei, L.; and Rubin, D","venue":null,"work_id":"5df5b621-17d4-410f-b58c-a9fe5d6b700d","year":2022},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.580398Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:b4b0881beb910c1a7e6408d1aecdacf62c9d8baa2f402124dd7b1163c6f06e15","observation_id":"03e0ad97-b0cf-4931-b44c-dc9aa212a8d6","resolution":{"observed_at":"2026-08-11T04:25:52.937744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.01275","last_updated":"2023-09-03T21:33:15Z","snapshot_observed_at":"2026-08-11T10:00:00.278657Z","submitted_at":"2023-09-03T21:33:15Z","title":"A Comparative Evaluation of FedAvg and Per-FedAvg Algorithms for Dirichlet Distributed Heterogeneous Data","version":1},"cited_work":{"arxiv_id":"2309.01275","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.01275","snapshot_observed_at":"2026-08-11T04:25:52.690715Z","title":"A Comparative Evaluation of FedAvg and Per-FedAvg Algorithms for Dirichlet Distributed Heterogeneous Data","venue":"cs.LG","work_id":"d8643fd4-f41b-4834-bace-9b41a0086041","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.584876Z"},"links":{"cited_paper":"/paper/2309.01275","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:104f1319e02c282eab4f1713c8d8e0af8869d5028d1d09753ea12612ed46557a","observation_id":"7cac9bad-4529-4e17-bf83-406502ea6598","resolution":{"observed_at":"2026-08-11T04:25:52.697999Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.916408Z","title":null,"venue":null,"work_id":"b5ddbf9c-3c8a-445b-b636-74daaf635c2a","year":2020},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.590065Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:512f780ffcf95cae4ca54d978e13ef95509939a7b97b5c3453e69a887a8de43c","observation_id":"966c7dd1-a018-4217-ad86-57b53a32e2bb","resolution":{"observed_at":"2026-08-11T04:25:52.922068Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.901211Z","title":null,"venue":null,"work_id":"22cd9700-ca3d-4d63-8a97-e5e26004cbd3","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.594671Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:47ba6df341bda2c189348bfac5521f4445b3043bf79446d422d8f6e6b441a83d","observation_id":"8691956b-3a1a-4881-891c-ef3f522360ea","resolution":{"observed_at":"2026-08-11T04:25:52.905978Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.884998Z","title":null,"venue":null,"work_id":"42fd6934-a156-4bc5-b1a7-c8316b4af7c3","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.599118Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:8d5075b232b37fe0769b76fefdc972c9cefff9c9ccf442390227b08257a70c87","observation_id":"cba937f0-33bc-427e-8bc7-c21df0f389d9","resolution":{"observed_at":"2026-08-11T04:25:52.890518Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.00233","last_updated":"2021-07-01T06:14:51Z","snapshot_observed_at":"2026-08-10T02:20:13.893413Z","submitted_at":"2021-07-01T06:14:51Z","title":"FedMix: Approximation of Mixup under Mean Augmented Federated Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.00233","snapshot_observed_at":"2026-08-11T04:25:52.603665Z","title":"J.; and Yang, E","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.603665Z"},"links":{"cited_paper":"/paper/2107.00233","citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:2e2de9a7591a76fe982755207ebaf956c5660787054677bd2789dd2463db8b45","observation_id":"07d902da-9894-46bb-945d-1dd1c8682c50","resolution":{"observed_at":"2026-08-11T04:25:52.603665Z","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":"2026-08-11T04:25:52.868762Z","title":null,"venue":null,"work_id":"648a9b10-e690-45d4-9863-f7dcc3a233e3","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.608723Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:760ee946dbc8d74ecfb02ef8285241b1080c1dd2a62b81180d1f632c78ded2dd","observation_id":"4a6f911b-5c2e-4655-ab59-51e9ffde299d","resolution":{"observed_at":"2026-08-11T04:25:52.873574Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.853373Z","title":null,"venue":null,"work_id":"805af74c-8ecc-4b4c-8e75-7c8f852f1e99","year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.613157Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:71e4b146ae73cd1da870f8a0336811c2e05580155f13c29c4c84b89dd1acefe9","observation_id":"2462039f-eff2-400d-965b-0910cf1ffa8e","resolution":{"observed_at":"2026-08-11T04:25:52.858141Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.837701Z","title":null,"venue":null,"work_id":"57a4992b-a417-45bb-8fe1-47c4b5d0650f","year":2020},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.617612Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:28876e0864c4879a1b191697ee8cdf89578cb5bcada5c51cce6d5693e51eacdf","observation_id":"a9ccc7e7-59bf-4c8f-9803-ed1092a1e2eb","resolution":{"observed_at":"2026-08-11T04:25:52.842700Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.821729Z","title":null,"venue":null,"work_id":"33dff10a-ec69-4549-8fe3-d5d919a460b0","year":2024},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.622105Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:314afbceb6f32c525063d77b479f81872d1d296abf3fd91e51c6b6f9f7a381b5","observation_id":"a5aef149-2834-49b0-b51b-d6ee0b7c7cbe","resolution":{"observed_at":"2026-08-11T04:25:52.826421Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.805586Z","title":"C.; Elkordy, A","venue":null,"work_id":"e8ae6572-0e9f-43e8-9037-33e9fcbe9310","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.626938Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:909ffb38eaff18a479480c0c3e13d19bdcad2bbde981247502ac48259f8da67b","observation_id":"323e0288-7d1d-4dda-856a-29e777d34704","resolution":{"observed_at":"2026-08-11T04:25:52.810657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T04:25:52.631418Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.631418Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:3f27e891e43b88308325065a76b6f850350d5dcf4b34ebf34102c40dcf1b8511","observation_id":"9ecd5ab6-85c0-4dcf-9c26-4024214e04e8","resolution":{"observed_at":"2026-08-11T04:25:52.631418Z","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":"2026-08-11T04:25:52.778612Z","title":null,"venue":null,"work_id":"207ff5d5-9627-449a-8eb6-724df891e57b","year":2023},"citing_paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-11T04:25:52.636009Z"},"links":{"citing_paper":"/paper/2412.18904"},"observation_digest":"sha256:ad02a9a36423971090ad3e382a6faf09cfff8ebfc7075fc69059fed734ebe32d","observation_id":"03ddae1d-b035-4a3c-8cb2-2d2e571e8892","resolution":{"observed_at":"2026-08-11T04:25:52.783483Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.18904","last_updated":"2024-12-25T13:35:54Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-11T04:18:45.768435Z","submitted_at":"2024-12-25T13:35:54Z","title":"FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":36,"verified_exact":2,"verified_fuzzy":8},"total_outbound_references":46},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2412.18904."}