{"as_of":"2026-08-09T02:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:02176c1d4bf2cf863eab97d96402edef203db836632bb09890b7c53c4f69984a","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":18,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T20:15:13.898263Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":5,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2403.03952","last_updated":"2026-04-20T06:05:54Z","snapshot_observed_at":"2026-08-03T00:56:47.399756Z","submitted_at":"2024-03-06T18:56:36Z","title":"Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-24T03:03:51.053556Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2403.03952"},"observation_digest":"sha256:0a09b189c22785af2ba232587207f67b148d8d28e4f1232753ac33046c38cb37","observation_id":"c5de8e78-a1e6-4589-b1cb-6a5a8f0f1c3a","resolution":{"observed_at":"2026-05-24T03:05:57.013142Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-07T20:15:13.898263Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.09888","last_updated":"2025-08-28T01:40:30Z","snapshot_observed_at":"2026-08-07T20:07:17.154568Z","submitted_at":"2025-02-14T03:25:09Z","title":"Climber: Toward Efficient Scaling Laws for Large Recommendation Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T20:15:13.898263Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2502.09888"},"observation_digest":"sha256:8bcf45de6f253caa6c5a16a0b0fdb809971770de9ed3a74017777323edab1142","observation_id":"0eaff254-29a4-4e20-af6d-1c10c879ed4c","resolution":{"observed_at":"2026-08-07T20:15:13.898263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-07T13:16:32.448740Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22238","last_updated":"2025-06-01T19:48:42Z","snapshot_observed_at":"2026-08-07T13:09:54.522611Z","submitted_at":"2025-05-28T11:12:57Z","title":"Yambda-5B -- A Large-Scale Multi-modal Dataset for Ranking And Retrieval","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:16:32.448740Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2505.22238"},"observation_digest":"sha256:ab42e77fbe570dc609476903fd46411ed5364391d94fca92442c22bb98256078","observation_id":"63f5e723-ff33-46d2-b7d7-9c89741a65e3","resolution":{"observed_at":"2026-08-07T13:16:32.448740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-07T11:02:28.271026Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03699","last_updated":"2025-08-11T03:29:10Z","snapshot_observed_at":"2026-08-07T10:54:58.901890Z","submitted_at":"2025-06-04T08:31:33Z","title":"Scaling Transformers for Discriminative Recommendation via Generative Pretraining","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:02:28.271026Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2506.03699"},"observation_digest":"sha256:8ef4e31c6ec2017a97c1189117de9baf76756a9215a02a7c7542a06e87e7db5b","observation_id":"1cf080d7-0482-44e9-85d5-a35f581f68d9","resolution":{"observed_at":"2026-08-07T11:02:28.271026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-06T15:35:48.319669Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.15551","last_updated":"2025-07-26T02:01:33Z","snapshot_observed_at":"2026-08-06T15:26:48.151250Z","submitted_at":"2025-07-21T12:28:55Z","title":"RankMixer: Scaling Up Ranking Models in Industrial Recommenders","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:35:48.319669Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2507.15551"},"observation_digest":"sha256:0f2d24ee8f91777d530d7865d3d2d921a8a0c16ae8af5a31ef3f2198792161eb","observation_id":"e8ddbd45-87db-4413-8c1c-b36efb2acc1c","resolution":{"observed_at":"2026-08-06T15:35:48.319669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T20:25:11.815668Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.10615","last_updated":"2025-08-14T13:12:29Z","snapshot_observed_at":"2026-08-06T19:53:35.593518Z","submitted_at":"2025-08-14T13:12:29Z","title":"FuXi-\\beta: Towards a Lightweight and Fast Large-Scale Generative Recommendation Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T20:25:11.815668Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2508.10615"},"observation_digest":"sha256:ac04feaea8eb1c471e56d6b0b5d84708623b10cf4d63307a1f6c15a5bab678f2","observation_id":"7dd2dbc1-3193-4ccf-964e-ca89ebf425f0","resolution":{"observed_at":"2026-08-05T20:25:11.815668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2509.24244","last_updated":"2026-05-11T07:55:31Z","snapshot_observed_at":"2026-08-08T08:18:46.512703Z","submitted_at":"2025-09-29T03:36:55Z","title":"Model Merging Scaling Laws in Large Language Models","version":4},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T13:32:33.009367Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2509.24244"},"observation_digest":"sha256:54525a6c83cdcba6c6f8878ad42418041754201d5e78ff5010010799ba71fc5e","observation_id":"faa18328-6f12-4f42-be36-559a57149044","resolution":{"observed_at":"2026-05-18T13:32:37.728406Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2511.14881","last_updated":"2026-05-08T05:02:43Z","snapshot_observed_at":"2026-07-06T22:36:13.287872Z","submitted_at":"2025-11-18T20:00:19Z","title":"SilverTorch: A Unified Model-based System to Democratize Large-Scale Recommendation on GPUs","version":5},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-17T20:21:31.266176Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2511.14881"},"observation_digest":"sha256:9952e931b462ccf80e41a2d4480a51bbca721f45ad7eae23a4750a4a1920ecab","observation_id":"2a2a5740-4f3a-4ca9-bc41-e70663c460f5","resolution":{"observed_at":"2026-05-17T20:22:04.560240Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-03T00:06:24.016376Z","title":"Understanding scaling laws for recommendation models.arXiv preprint arXiv:2208.08489, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2602.11799","last_updated":"2026-05-26T08:19:05Z","snapshot_observed_at":"2026-08-03T00:06:22.655689Z","submitted_at":"2026-02-12T10:26:15Z","title":"Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T00:06:24.016376Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2602.11799"},"observation_digest":"sha256:52731a65372a56543003363f1e02013fdf8c1f76605e9f7a26a956b8655c7426","observation_id":"0282bc5f-1a1e-4bbc-9116-f1443ea30743","resolution":{"observed_at":"2026-08-03T00:06:24.016376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2604.12965","last_updated":"2026-04-14T16:59:03Z","snapshot_observed_at":"2026-08-06T12:38:28.688700Z","submitted_at":"2026-04-14T16:59:03Z","title":"Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T14:25:53.909672Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2604.12965"},"observation_digest":"sha256:8a9fc4bc69a5606fabeab5973adc9b434dd746189fe10437f5421f0767d38cee","observation_id":"b7ecbe37-0666-472d-b140-b23be1c1a593","resolution":{"observed_at":"2026-05-10T14:30:30.294337Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2604.17878","last_updated":"2026-05-12T11:43:26Z","snapshot_observed_at":"2026-07-06T23:04:55.190916Z","submitted_at":"2026-04-20T06:40:27Z","title":"RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T04:30:22.404616Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2604.17878"},"observation_digest":"sha256:3d529c2e93c40498bd9caff203d2d3d504e53c55231123b9c2d033b10460fc3b","observation_id":"8791dda3-0097-4185-8eb5-a3895db2fa80","resolution":{"observed_at":"2026-05-11T11:56:04.889366Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2604.17878","last_updated":"2026-05-12T11:43:26Z","snapshot_observed_at":"2026-07-06T23:04:55.190916Z","submitted_at":"2026-04-20T06:40:27Z","title":"RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T07:14:03.733251Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2604.17878"},"observation_digest":"sha256:14b3ad8ca16f8d947c1d5f82789b64b33310851b455472ba48eeeb61d72564fc","observation_id":"32bf1375-a8c1-4e0b-ad73-d3ac043a0a1e","resolution":{"observed_at":"2026-05-13T07:17:29.441108Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2605.10886","last_updated":"2026-07-09T02:30:06Z","snapshot_observed_at":"2026-07-12T23:17:31.243229Z","submitted_at":"2026-05-11T17:32:29Z","title":"LoKA: Low-precision Kernel Applications for Recommendation Models At Scale","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-12T04:33:41.411292Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2605.10886"},"observation_digest":"sha256:dd59b3a4986b3cdc1327ac6c79562863cc5be1a97de5e8cdb36ff65b5ee87150","observation_id":"c714227a-3384-44d0-904e-a302cd28450c","resolution":{"observed_at":"2026-05-12T06:06:28.040117Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2605.10886","last_updated":"2026-07-09T02:30:06Z","snapshot_observed_at":"2026-07-12T23:17:31.243229Z","submitted_at":"2026-05-11T17:32:29Z","title":"LoKA: Low-precision Kernel Applications for Recommendation Models At Scale","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-15T04:55:01.973832Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2605.10886"},"observation_digest":"sha256:941016f9242f35624bb7a69580faf852f3866430530c7ecbe529e7ae72c2436c","observation_id":"67b51849-b0ce-4d43-96db-e58afce6b6b4","resolution":{"observed_at":"2026-05-15T04:59:46.247134Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":"2208.08489","doi":"10.48550/arxiv.2208.08489","metadata_source":"arxiv_reference","pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Under- standing scaling laws for recommendation models","venue":"arXiv (Cornell University)","work_id":"c7285975-3f78-40d1-80b1-8e6c546dadbd","year":2022},"citing_paper":{"arxiv_id":"2606.05257","last_updated":"2026-06-03T15:59:25Z","snapshot_observed_at":"2026-08-01T23:32:43.113406Z","submitted_at":"2026-06-03T15:59:25Z","title":"Scaling Laws for Behavioral Foundation Models over User Event Sequences","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-28T06:49:25.517510Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2606.05257"},"observation_digest":"sha256:92a410d7ed3b6bf6e5b40fc0a789017e341d1ae1ac88d1130520746e946ea191","observation_id":"3a2aba71-4b66-406d-b134-4083bccad3e1","resolution":{"observed_at":"2026-07-02T07:36:45.306367Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-01T19:18:41.341694Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17017","last_updated":"2026-08-02T05:56:26Z","snapshot_observed_at":"2026-08-06T23:24:49.167446Z","submitted_at":"2026-07-19T00:59:09Z","title":"WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T19:18:41.341694Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2607.17017"},"observation_digest":"sha256:88817f86b24dc04c644f63fd2411994b52de8828d4a2a71dab336311d41d83a3","observation_id":"b797cf67-154e-4a0c-9065-27a5000714a1","resolution":{"observed_at":"2026-08-01T19:18:41.341694Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-04T04:17:56.347904Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17017","last_updated":"2026-08-02T05:56:26Z","snapshot_observed_at":"2026-08-06T23:24:49.167446Z","submitted_at":"2026-07-19T00:59:09Z","title":"WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T04:17:56.347904Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2607.17017"},"observation_digest":"sha256:d7eef3d63724e3f3a23d9609b30d771291ac7497c3f260a74af4bbea4d58bc1c","observation_id":"f867e7eb-a5b7-49fc-a4be-fbea4383dba8","resolution":{"observed_at":"2026-08-04T04:17:56.347904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.08489","snapshot_observed_at":"2026-08-01T02:11:13.200065Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27744","last_updated":"2026-07-30T06:33:50Z","snapshot_observed_at":"2026-08-04T10:27:17.545382Z","submitted_at":"2026-07-30T06:33:50Z","title":"ROCS: Request-Oriented Compute Sharing for Efficient Large-Scale Recommendation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T02:11:13.200065Z"},"links":{"cited_paper":"/paper/2208.08489","citing_paper":"/paper/2607.27744"},"observation_digest":"sha256:dbe043de0e1f8f74ed80315f777e4c1a89f2011ff5330d005fce01726b287f62","observation_id":"9440b6c3-714f-48ed-862a-313333e16ccc","resolution":{"observed_at":"2026-08-01T02:11:13.200065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2208.08489/citation-record","integrity":"/paper/2208.08489/integrity","json":"/paper/2208.08489/citation-record.json","paper":"/paper/2208.08489"},"outbound":[],"paper":{"arxiv_id":"2208.08489","last_updated":"2022-08-17T19:13:17Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-03T18:34:33.961760Z","submitted_at":"2022-08-17T19:13:17Z","title":"Understanding Scaling Laws for Recommendation Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2208.08489."}