{"as_of":"2026-08-22T17:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9d0347dc60f96e43b2d63ff938763feadad57fc280cf0e1a547cd2637d602e6c","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:40:06.137460Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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/2608.11519/citation-record","integrity":"/paper/2608.11519/integrity","json":"/paper/2608.11519/citation-record.json","paper":"/paper/2608.11519"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2107.14795","last_updated":"2022-03-15T22:37:19Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-07-30T17:53:34Z","title":"Perceiver IO: A General Architecture for Structured Inputs & Outputs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.14795","snapshot_observed_at":"2026-08-16T00:40:06.087336Z","title":"Perceiver IO: A general architecture for structured inputs & outputs.arXiv preprint arXiv:2107.14795, 2021a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.087336Z"},"links":{"cited_paper":"/paper/2107.14795","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:550f6177c332864d1b3f37db884e006758ec66cd0300a3d84b29bcf4afd2dceb","observation_id":"9132671a-543c-43ce-9760-8d972214467d","resolution":{"observed_at":"2026-08-16T00:40:06.087336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.04451","last_updated":"2020-02-18T16:01:18Z","snapshot_observed_at":"2026-07-06T08:50:12.690900Z","submitted_at":"2020-01-13T18:38:28Z","title":"Reformer: The Efficient Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.04451","snapshot_observed_at":"2026-08-16T00:40:06.092553Z","title":"Reformer: The efficient transformer.arXiv preprint arXiv:2001.04451,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.092553Z"},"links":{"cited_paper":"/paper/2001.04451","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:2d8a0b2b701f1aaf20f8c40d2b617fca4c15f1459a3e5be51da67bbc6640ccaa","observation_id":"d6ddfccd-b48f-456e-be09-0f8b4b20ad4a","resolution":{"observed_at":"2026-08-16T00:40:06.092553Z","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":"2026-08-16T00:40:06.102546Z","title":"Lu Lu, Pengzhan Jin, Guofei Pang, Zhongqiang Zhang, and George Em Karniadakis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.102546Z"},"links":{"citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:aa9c0d58dfc044ec2df105a0f60bfc199d260c5138a41d5775e1bfaeec40129d","observation_id":"dddebeaf-8d72-4058-8192-2bedf6967171","resolution":{"observed_at":"2026-08-16T00:40:06.102546Z","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":"2026-08-16T00:40:06.111173Z","title":"NVIDIA PhysicsNeMo Team","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.111173Z"},"links":{"citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:016cb0dd23224b0e62109e1d46408ae20ddabdd60b7e6d8eec7573cfeb0502c3","observation_id":"6080b142-7d60-41b3-b583-fd0463eec223","resolution":{"observed_at":"2026-08-16T00:40:06.111173Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03923","last_updated":"2024-12-20T01:47:32Z","snapshot_observed_at":"2026-08-21T15:30:56.547540Z","submitted_at":"2024-06-06T10:04:53Z","title":"Latent Neural Operator for Solving Forward and Inverse PDE Problems","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03923","snapshot_observed_at":"2026-08-16T00:40:06.125168Z","title":"Latent neural operator for solving forward and inverse pde problems","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.125168Z"},"links":{"cited_paper":"/paper/2406.03923","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:4b5fc8754cc81055856d250ef0417c046800a8e0927ae258b452357ac1efa508","observation_id":"b08537e7-dee6-4fb7-a3b5-00775505e505","resolution":{"observed_at":"2026-08-16T00:40:06.125168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02366","last_updated":"2024-06-01T15:33:37Z","snapshot_observed_at":"2026-08-18T09:48:19.058609Z","submitted_at":"2024-02-04T06:37:38Z","title":"Transolver: A Fast Transformer Solver for PDEs on General Geometries","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02366","snapshot_observed_at":"2026-08-16T00:40:06.129243Z","title":"Transolver: A fast transformer solver for pdes on general geometries.arXiv preprint arXiv:2402.02366,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.129243Z"},"links":{"cited_paper":"/paper/2402.02366","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:92be6063e24f1388c69cb2c9387f66b995f204dcb9a1148c78cc23a061b5f3ee","observation_id":"fb1a4011-468b-40cf-b3e1-f97f9b9cf346","resolution":{"observed_at":"2026-08-16T00:40:06.129243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04347","last_updated":"2024-02-06T19:31:26Z","snapshot_observed_at":"2026-08-16T14:20:52.366502Z","submitted_at":"2024-02-06T19:31:26Z","title":"The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04347","snapshot_observed_at":"2026-08-16T00:40:06.133514Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.133514Z"},"links":{"cited_paper":"/paper/2402.04347","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:43fe9cc5b6cd0596a1d60eb4ca0cf45825adfe9d5cbc916963a1a5a5a166afea","observation_id":"32a569bc-a8f9-44cd-ae82-5756461be089","resolution":{"observed_at":"2026-08-16T00:40:06.133514Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.04940","last_updated":"2026-06-29T09:52:43Z","snapshot_observed_at":"2026-08-20T01:02:33.531610Z","submitted_at":"2026-02-04T16:52:44Z","title":"Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.04940","snapshot_observed_at":"2026-08-16T00:40:06.137460Z","title":"Transolver-3: Scaling up transformer solvers to industrial-scale geometries","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.137460Z"},"links":{"cited_paper":"/paper/2602.04940","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:04e3adf753972f8865f8c7a2fac400a04d416a7d152923be2619f25146392123","observation_id":"ecb91b07-9c73-4dfc-bf45-c86c97bf71d9","resolution":{"observed_at":"2026-08-16T00:40:06.137460Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.04768","last_updated":"2020-06-14T08:15:54Z","snapshot_observed_at":"2026-07-06T09:27:03.809621Z","submitted_at":"2020-06-08T17:37:52Z","title":"Linformer: Self-Attention with Linear Complexity","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.04768","snapshot_observed_at":"2026-08-16T00:40:06.121088Z","title":"Linformer: Self-attention with linear complexity.arXiv preprint arXiv:2006.04768,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.121088Z"},"links":{"cited_paper":"/paper/2006.04768","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:6dbb456e829a4913e0559ee0c5b704cd0b06956468e526f486b26633c9b86453","observation_id":"9cd9d5ea-2f07-4a13-9a87-e0c5dd76a1a9","resolution":{"observed_at":"2026-08-16T00:40:06.121088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.03740","last_updated":"2018-02-15T20:04:02Z","snapshot_observed_at":"2026-08-12T13:00:33.339808Z","submitted_at":"2017-10-10T17:42:04Z","title":"Mixed Precision Training","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.03740","snapshot_observed_at":"2026-08-16T00:40:06.106614Z","title":"Pablo Miralles-González, Javier Huertas-Tato, Alejandro Martín, and David Camacho","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.106614Z"},"links":{"cited_paper":"/paper/1710.03740","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:e085c731ddc27fa5ed5e8d8a81b4aebd884a03c25e004f538058ce1c1b750a20","observation_id":"1d157ae3-6e1e-448c-9c92-a20d70b7d882","resolution":{"observed_at":"2026-08-16T00:40:06.106614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.08895","last_updated":"2021-05-17T03:12:33Z","snapshot_observed_at":"2026-08-14T20:53:04.124337Z","submitted_at":"2020-10-18T00:34:21Z","title":"Fourier Neural Operator for Parametric Partial Differential Equations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.08895","snapshot_observed_at":"2026-08-16T00:40:06.097106Z","title":"Fourier neural operator for parametric partial differential equations","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.097106Z"},"links":{"cited_paper":"/paper/2010.08895","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:1fafe9bd6c81bd2ed176987133a53f8d697f16da403cb6f8fdee7644a58c4a5a","observation_id":"530f4f5f-950d-4d15-a42c-bf1208155be6","resolution":{"observed_at":"2026-08-16T00:40:06.097106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.03236","last_updated":"2020-06-05T05:16:23Z","snapshot_observed_at":"2026-08-20T02:54:58.849046Z","submitted_at":"2020-06-05T05:16:23Z","title":"Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.03236","snapshot_observed_at":"2026-08-16T00:40:06.078440Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.078440Z"},"links":{"cited_paper":"/paper/2006.03236","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:8ed569ceaf5a11436a7d56ffe6fda95ced1716245c7c3ca7b4747064f27c5c18","observation_id":"0915fee4-6802-43a7-bb1f-01bd89e07a70","resolution":{"observed_at":"2026-08-16T00:40:06.078440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.10509","last_updated":"2019-04-23T19:29:47Z","snapshot_observed_at":"2026-08-16T10:03:03.268538Z","submitted_at":"2019-04-23T19:29:47Z","title":"Generating Long Sequences with Sparse Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.10509","snapshot_observed_at":"2026-08-16T00:40:06.067262Z","title":"Generating long sequences with sparse transformers.arXiv preprint arXiv:1904.10509,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.067262Z"},"links":{"cited_paper":"/paper/1904.10509","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:87219510290e098f30c79362411ec56255c1206b88b066fe315507a37d303fef","observation_id":"5769aa56-4400-482f-86e2-7e4a5b2565e4","resolution":{"observed_at":"2026-08-16T00:40:06.067262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.14794","last_updated":"2022-11-19T12:45:21Z","snapshot_observed_at":"2026-08-12T04:58:34.201421Z","submitted_at":"2020-09-30T17:09:09Z","title":"Rethinking Attention with Performers","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.14794","snapshot_observed_at":"2026-08-16T00:40:06.072961Z","title":"Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.072961Z"},"links":{"cited_paper":"/paper/2009.14794","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:351410f16ccd00ecf0cba96d6835d0169202b61a1825e874c0e56922bccf493f","observation_id":"e4a7f5e9-9168-4ce5-93c1-0f4531755f8f","resolution":{"observed_at":"2026-08-16T00:40:06.072961Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.00396","last_updated":"2022-08-05T17:54:38Z","snapshot_observed_at":"2026-08-14T01:02:41.198730Z","submitted_at":"2021-10-31T03:32:18Z","title":"Efficiently Modeling Long Sequences with Structured State Spaces","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.00396","snapshot_observed_at":"2026-08-16T00:40:06.083128Z","title":"Efficiently modeling long sequences with structured state spaces.arXiv preprint arXiv:2111.00396,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.083128Z"},"links":{"cited_paper":"/paper/2111.00396","citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:67eb9821ddd092a8c7507f2b05500241a7760357491a5b711fce5cb1d6da2055","observation_id":"9db632cc-acbc-4227-9f43-6091c45b2afe","resolution":{"observed_at":"2026-08-16T00:40:06.083128Z","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":"2026-08-16T00:40:06.062597Z","title":"Iz Beltagy, Matthew E","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.062597Z"},"links":{"citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:0ae641500ce1c8aab0e25fe6b8c38fcc9d584e4afb97980c7cc900748d4829fb","observation_id":"08ddeb45-4d04-4058-9f58-f1858adfb07d","resolution":{"observed_at":"2026-08-16T00:40:06.062597Z","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":"2026-08-16T00:40:06.116586Z","title":"Zhen Qin, Xiaodong Han, Weixuan Sun, Dongxu Li, Lingpeng Kong, Nick Barnes, and Yiran Zhong","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-16T00:40:06.116586Z"},"links":{"citing_paper":"/paper/2608.11519"},"observation_digest":"sha256:04228b360785a355b9208f56719bc1150370117c376ef6eb72c2b607c28abfed","observation_id":"e1d1d805-3a6d-4afd-ad30-4a732536a293","resolution":{"observed_at":"2026-08-16T00:40:06.116586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.11519","last_updated":"2026-08-12T00:16:46Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T21:35:08.562187Z","submitted_at":"2026-08-12T00:16:46Z","title":"FLARE++: Low-rank attention with dynamic attention routing"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":17},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2608.11519."}