{"as_of":"2026-08-14T12:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ed6ce3e6dba3eabd0525a59957614038dea409281dcd42cb8b07809a4c61788b","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":"2026-08-06T20:31:48.003056Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T19:45:12.482381Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-01T18:45:58.257917Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"cited_work":{"arxiv_id":"2507.02754","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.02754","snapshot_observed_at":"2026-07-01T18:45:58.257917Z","title":"arXiv preprint arXiv:2507.02754 , year=","venue":null,"work_id":"f6ff7317-63e7-4a51-883f-f799ce38ff99","year":2025},"citing_paper":{"arxiv_id":"2605.10905","last_updated":"2026-05-14T17:37:37Z","snapshot_observed_at":"2026-08-12T18:29:20.670719Z","submitted_at":"2026-05-11T17:46:01Z","title":"TLX: Hardware-Native, Evolvable MIMW GPU Compiler for Large-scale Production Environments","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-12T03:55:15.475044Z"},"links":{"cited_paper":"/paper/2507.02754","citing_paper":"/paper/2605.10905"},"observation_digest":"sha256:ae3277b4d385297f118b9637a199a304cda167f48fa1c3dd969867c3a278a4e3","observation_id":"efe69367-f1cc-4101-9158-10098582d9df","resolution":{"observed_at":"2026-05-12T03:56:21.773147Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"cited_work":{"arxiv_id":"2507.02754","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.02754","snapshot_observed_at":"2026-07-01T18:45:58.257917Z","title":"arXiv preprint arXiv:2507.02754 , year=","venue":null,"work_id":"f6ff7317-63e7-4a51-883f-f799ce38ff99","year":2025},"citing_paper":{"arxiv_id":"2605.10905","last_updated":"2026-05-14T17:37:37Z","snapshot_observed_at":"2026-08-12T18:29:20.670719Z","submitted_at":"2026-05-11T17:46:01Z","title":"TLX: Hardware-Native, Evolvable MIMW GPU Compiler for Large-scale Production Environments","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-15T05:08:56.760052Z"},"links":{"cited_paper":"/paper/2507.02754","citing_paper":"/paper/2605.10905"},"observation_digest":"sha256:01bce7dfbf185cc0bcc358fedcbe2ab9269e716d06eb336bec6f1e4e61020bb8","observation_id":"b79e26a7-55a5-43c7-8f36-65502312a56e","resolution":{"observed_at":"2026-05-15T05:09:44.705534Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"cited_work":{"arxiv_id":"2507.02754","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.02754","snapshot_observed_at":"2026-07-01T18:45:58.257917Z","title":"arXiv preprint arXiv:2507.02754 , year=","venue":null,"work_id":"f6ff7317-63e7-4a51-883f-f799ce38ff99","year":2025},"citing_paper":{"arxiv_id":"2606.28122","last_updated":"2026-06-26T14:22:30Z","snapshot_observed_at":"2026-08-02T20:41:14.915089Z","submitted_at":"2026-06-26T14:22:30Z","title":"Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-06-29T01:49:08.216819Z"},"links":{"cited_paper":"/paper/2507.02754","citing_paper":"/paper/2606.28122"},"observation_digest":"sha256:7680a698b79db88935849463fd24f7eb92b7eea1ba7c4bafdcdb63adeaeaca9d","observation_id":"d4ed6c44-3b7e-48f2-a18e-c2f7402a604c","resolution":{"observed_at":"2026-07-01T18:45:58.259504Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.02754","snapshot_observed_at":"2026-08-11T19:45:12.482381Z","title":"arXiv preprint arXiv:2507.02754 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.09307","last_updated":"2026-08-10T08:53:30Z","snapshot_observed_at":"2026-08-13T23:42:57.891702Z","submitted_at":"2026-08-10T08:53:30Z","title":"Linearized 2-Simplicial Attention","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-11T19:45:12.482381Z"},"links":{"cited_paper":"/paper/2507.02754","citing_paper":"/paper/2608.09307"},"observation_digest":"sha256:528f9edc8ad9434136de71283bb3c95d6b1cdd1de964ba9279c159eb9d01e6e4","observation_id":"245dc3a0-35ab-45f4-9473-e9397413bd63","resolution":{"observed_at":"2026-08-11T19:45:12.482381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.02754/citation-record","integrity":"/paper/2507.02754/integrity","json":"/paper/2507.02754/citation-record.json","paper":"/paper/2507.02754"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T20:31:47.279796Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.279796Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:f208778e80943a3e1236fa09b34c34462f808306c81da417887170790eea7e5c","observation_id":"4d71038d-1818-4c1e-9606-bde8cfe3d333","resolution":{"observed_at":"2026-08-06T20:31:47.279796Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13245","last_updated":"2023-12-23T17:55:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-22T17:16:38Z","title":"GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13245","snapshot_observed_at":"2026-08-06T20:31:47.332972Z","title":"Gqa: Training generalized multi-query transformer models from multi-head checkpoints","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.332972Z"},"links":{"cited_paper":"/paper/2305.13245","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:87b78cebe37c00790d6d0026aaf09dce7812eebfbf0ca730eafcd02d10479da0","observation_id":"26f31ce2-e56f-4824-a351-c7007b99f718","resolution":{"observed_at":"2026-08-06T20:31:47.332972Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07732","last_updated":"2021-08-16T03:57:30Z","snapshot_observed_at":"2026-08-02T19:23:53.535075Z","submitted_at":"2021-08-16T03:57:30Z","title":"Program Synthesis with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07732","snapshot_observed_at":"2026-08-06T20:31:47.413537Z","title":"Program synthesis with large language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.413537Z"},"links":{"cited_paper":"/paper/2108.07732","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:691ecc1d19beec607410afa908d8d8e961439133c7e21f058cebbd86dad3705b","observation_id":"3487f141-73db-4bc4-953c-691206c276e1","resolution":{"observed_at":"2026-08-06T20:31:47.413537Z","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":"2026-08-06T20:31:48.738545Z","title":"Explaining neural scaling laws","venue":null,"work_id":"f14d3644-5f29-47a7-babf-50c0652d2c2b","year":2024},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.525998Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:bec67d805c7c81a833c863bcdcc4f74782fac3f750afafe86e3a8c0945468813","observation_id":"1a55b8dd-209d-48a1-836f-067391f31903","resolution":{"observed_at":"2026-08-06T20:31:48.742807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:48.727230Z","title":"Systematic generalization with edge transformers","venue":null,"work_id":"718ed011-8363-4cd9-8023-4d1a63807e5a","year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.581513Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:235d5a19a194068bd00997a77fc3619b05b2b7af0fd2d94b66f002ce52bb082c","observation_id":"cace0b4e-ac7b-4e81-bbdd-77198cf53445","resolution":{"observed_at":"2026-08-06T20:31:48.730842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12925","last_updated":"2024-11-19T23:23:16Z","snapshot_observed_at":"2026-08-14T09:22:00.801189Z","submitted_at":"2024-11-19T23:23:16Z","title":"Loss-to-Loss Prediction: Scaling Laws for All Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12925","snapshot_observed_at":"2026-08-06T20:31:47.679967Z","title":"Loss-to-loss prediction: Scaling laws for all datasets","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.679967Z"},"links":{"cited_paper":"/paper/2411.12925","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:00d311b91d554eec76289035047a657ad2b30f0d59812ae55a9160aa5d054384","observation_id":"7f6d9595-27b7-498f-bc6f-105d6625a25d","resolution":{"observed_at":"2026-08-06T20:31:47.679967Z","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":"2026-08-06T20:31:47.764549Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.764549Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:8debed446757e209acd2f9e774affe9ab179d44d7a8411d1542f3ff0ba82103d","observation_id":"1361d9f1-1229-4ba0-8034-28e3ec8c3367","resolution":{"observed_at":"2026-08-06T20:31:47.764549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.00668","last_updated":"2019-09-02T11:11:35Z","snapshot_observed_at":"2026-08-14T05:37:53.870104Z","submitted_at":"2019-09-02T11:11:35Z","title":"Logic and the $2$-Simplicial Transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.00668","snapshot_observed_at":"2026-08-06T20:31:47.863926Z","title":"Logic and the 2 -simplicial transformer","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.863926Z"},"links":{"cited_paper":"/paper/1909.00668","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:f0a420837b825a2442106c56cb1914a6097b89d5c4246a93b8829d1e20a815c5","observation_id":"0595b5d2-7b5f-46f4-a0f7-703bf88c1c54","resolution":{"observed_at":"2026-08-06T20:31:47.863926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-06T20:31:47.868300Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.868300Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:2f3bed0519fa2020c0112db3385db28df894ebea75d790e88460009836b9a09b","observation_id":"8932e247-1acf-4c51-8330-12fedff90499","resolution":{"observed_at":"2026-08-06T20:31:47.868300Z","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":"2026-08-06T20:31:47.872465Z","title":"Flashattention: Fast and memory-efficient exact attention with io-awareness","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.872465Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:3def2d4445ff147576e74393bce8884b35b447c21a3f3b1129a4197128669d54","observation_id":"c52182ce-c3be-4338-9491-525706a39185","resolution":{"observed_at":"2026-08-06T20:31:47.872465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03819","last_updated":"2019-03-05T16:46:19Z","snapshot_observed_at":"2026-08-13T07:34:17.550838Z","submitted_at":"2018-07-10T18:39:15Z","title":"Universal Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.03819","snapshot_observed_at":"2026-08-06T20:31:47.876295Z","title":"Universal transformers","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.876295Z"},"links":{"cited_paper":"/paper/1807.03819","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:bcf3e09e8cb8a55aa26450939fedf9dc049c90da9b74f8f66bc4288c67356e03","observation_id":"93d1f437-cf8d-4e63-8be3-8c3f65402352","resolution":{"observed_at":"2026-08-06T20:31:47.876295Z","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":"status/1925665","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:31:48.435483Z","title":"Observation on scaling laws, May 2025","venue":null,"work_id":"ff8f4a8c-e518-40b1-a4f0-21713fc23060","year":2025},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.880210Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:a3598caa688ebc282f5fc7566e95ea645b3c372f94eba3102da5002b556c5295","observation_id":"406ebcc6-3588-47c9-a304-295ba6f9595d","resolution":{"observed_at":"2026-08-06T20:31:48.443815Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-06T20:31:47.884864Z","title":"Mamba: Linear-time sequence modeling with selective state spaces","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.884864Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:0e3d1fcd1d1952c05c70b05e71dcb24222a7b7eb598dd3cca29d7f23f245a885","observation_id":"4002c051-2c80-480e-a493-7b6ee471d278","resolution":{"observed_at":"2026-08-06T20:31:47.884864Z","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":"2026-08-06T20:31:48.700289Z","title":"Array programming with numpy","venue":null,"work_id":"b0977aab-1669-4e74-ab34-2c731a7f47e7","year":2020},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.888566Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:4d1b84e3c22fd9e68ad8fd620fc31e8e5bde0316265d5779909326892d162d5c","observation_id":"4c514223-5d96-4024-becc-8bfcd87ce561","resolution":{"observed_at":"2026-08-06T20:31:48.703801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.03300","last_updated":"2021-01-12T18:57:11Z","snapshot_observed_at":"2026-08-13T20:44:28.824685Z","submitted_at":"2020-09-07T17:59:25Z","title":"Measuring Massive Multitask Language Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.03300","snapshot_observed_at":"2026-08-06T20:31:47.892175Z","title":"Measuring massive multitask language understanding","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.892175Z"},"links":{"cited_paper":"/paper/2009.03300","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:6bbe54736aa0c4d42e2f78705cfab3046cf31760921bb95bcf3610431c9076bc","observation_id":"4fdb58ff-8252-4600-8029-4acf51ec3f0c","resolution":{"observed_at":"2026-08-06T20:31:47.892175Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.00409","last_updated":"2017-12-01T17:13:14Z","snapshot_observed_at":"2026-08-14T02:46:56.838057Z","submitted_at":"2017-12-01T17:13:14Z","title":"Deep Learning Scaling is Predictable, Empirically","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.00409","snapshot_observed_at":"2026-08-06T20:31:47.896182Z","title":"Deep learning scaling is predictable, empirically","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.896182Z"},"links":{"cited_paper":"/paper/1712.00409","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:bce26e8acb30152b6ae08a8f020200e4b381ea0c2f4a3543151633f92109af91","observation_id":"376662f9-ce1a-4eff-a1b6-398b00adfed2","resolution":{"observed_at":"2026-08-06T20:31:47.896182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-08-09T19:52:33.533277Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-06T20:31:47.900090Z","title":"Training compute-optimal large language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.900090Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:18bd91c159d2c1d83a9fe9ee744a551e881c13cac102906246980b4568f57996","observation_id":"13036418-3af6-4cc3-afd8-77753e7ca1f7","resolution":{"observed_at":"2026-08-06T20:31:47.900090Z","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":"2026-08-06T20:31:47.903756Z","title":"Gpipe: Efficient training of giant neural networks using pipeline parallelism","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.903756Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:d5acd3e71d242ba8a34a74a485a9e4f21004f28c1df6dfb97d9723216fd299b9","observation_id":"aa2cb402-81a2-49e2-a6c6-a22fbf0238a5","resolution":{"observed_at":"2026-08-06T20:31:47.903756Z","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":"2026-08-06T20:31:47.907332Z","title":"Hierarchical mixtures of experts and the em algorithm","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.907332Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:4a8dc1eca5b5c13829b00f43b1b88b11d13504d917ed7038508f0dbe723fe6b7","observation_id":"f74d41ae-9f75-40f5-8469-8ffdf781a5d9","resolution":{"observed_at":"2026-08-06T20:31:47.907332Z","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":"2026-08-06T20:31:47.910669Z","title":"Highly accurate protein structure prediction with alphafold","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.910669Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:a93964fc6d1c1b8fa44b9e55ae58816a692369d53600b73a006fe83d3fc35c72","observation_id":"d1e28537-9b05-40cc-ab23-a18704ba6fde","resolution":{"observed_at":"2026-08-06T20:31:47.910669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-06T20:31:47.913958Z","title":"Scaling laws for neural language models","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.913958Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:b9224b5376e77ab60802b04aeea56dc05ca043fbdc1cfc7ec37912bfca7cbe27","observation_id":"1a5b0c91-caab-4467-bb19-e891a840abca","resolution":{"observed_at":"2026-08-06T20:31:47.913958Z","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":"2026-08-06T20:31:48.663676Z","title":"Transformers are rnns: fast autoregressive transformers with linear attention","venue":null,"work_id":"710b29c3-fd5e-438c-9224-724b3e7911f7","year":2020},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.917978Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:70f036cb8c51871de78f7a61a9f8501c3f4fdd54fdd1161ca1a146a69853edbf","observation_id":"cbaf4031-3885-4590-b9fd-02197c6f2046","resolution":{"observed_at":"2026-08-06T20:31:48.667478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.921753Z","title":"Strassen attention: Unlocking compositional abilities in transformers based on a new lower bound method","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.921753Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:0442330ae621c657eaed84b196c4c5376f05807ea3785fa2feaab5f76edc92a8","observation_id":"69a3d88a-2181-42f3-9a96-0f1573a004b0","resolution":{"observed_at":"2026-08-06T20:31:47.921753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-09T20:34:52.923500Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-06T20:31:47.925509Z","title":"Fixing weight decay regularization in adam","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.925509Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:e835d49db94a12de0d3a6de412b17454354f6aff7f5cfca932317162e2adbe46","observation_id":"1f0d2026-bec1-4d54-baa4-cba9a41b96f9","resolution":{"observed_at":"2026-08-06T20:31:47.925509Z","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":"2026-08-06T20:31:47.929662Z","title":"Devanur, Gregory R","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.929662Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:b6533880677e33d18e24e775a2adfd637dcc2378ae3624483c3219b95ef86dfe","observation_id":"dbab16ea-a0fa-4f35-93fc-82d5fe2344cf","resolution":{"observed_at":"2026-08-06T20:31:47.929662Z","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":"2026-08-06T20:31:48.651545Z","title":"Image transformer","venue":null,"work_id":"542aee7e-297a-4999-a5c9-560d6d07d8d1","year":2018},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.933422Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:d255a2fd9fc56b88e80852d6fbb8ad044204ba3c6d0e233573a653c30eab25c6","observation_id":"05c211e6-ce1f-4e3a-a243-75e3904e0f3c","resolution":{"observed_at":"2026-08-06T20:31:48.655195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.936863Z","title":"Efficient content-based sparse attention with routing transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.936863Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:5d39a8f310a4181bf8d24c0c4c84632ba4000d532a9e8683b55e8688a430370f","observation_id":"612c1e31-617f-40b2-8acf-a82378020f05","resolution":{"observed_at":"2026-08-06T20:31:47.936863Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.06366","last_updated":"2022-07-13T17:18:02Z","snapshot_observed_at":"2026-08-13T15:04:45.380602Z","submitted_at":"2022-07-13T17:18:02Z","title":"N-Grammer: Augmenting Transformers with latent n-grams","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.06366","snapshot_observed_at":"2026-08-06T20:31:47.940113Z","title":"N-grammer: Augmenting transformers with latent n-grams","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.940113Z"},"links":{"cited_paper":"/paper/2207.06366","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:56512554e44a310fbfe73d2e4a334dce90df8b0dc330a571a27fbd88d9e24235","observation_id":"3b78d1ba-6456-44db-820f-2801cdf63c95","resolution":{"observed_at":"2026-08-06T20:31:47.940113Z","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":"2026-08-06T20:31:48.632030Z","title":"Representational strengths and limitations of transformers","venue":null,"work_id":"cf3d6947-0e34-428a-bd5a-3a625c1b48a9","year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.943571Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:880e725ab186a6d4158d5619efc69416679694bac1f90ab3233adc2f8d98c08b","observation_id":"dd73ca29-adb4-4334-bf34-4ebf9ef17a3c","resolution":{"observed_at":"2026-08-06T20:31:48.635934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.17416","last_updated":"2025-02-24T18:49:05Z","snapshot_observed_at":"2026-08-12T17:52:51.001662Z","submitted_at":"2025-02-24T18:49:05Z","title":"Reasoning with Latent Thoughts: On the Power of Looped Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.17416","snapshot_observed_at":"2026-08-06T20:31:47.946894Z","title":"Reasoning with latent thoughts: On the power of looped transformers","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.946894Z"},"links":{"cited_paper":"/paper/2502.17416","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:0badc39658ef004e36840f90063feb70ac8148ed388201ab537a461fe898cec7","observation_id":"7cb73c37-19bc-4b79-865f-0299409f9023","resolution":{"observed_at":"2026-08-06T20:31:47.946894Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-08-13T11:35:07.866136Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-06T20:31:47.950381Z","title":"Outrageously large neural networks: The sparsely-gated mixture-of-experts layer","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.950381Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:b22c0a8543687158c74505fb62b968bfc7d92473c96a1c2812c736255f966f1a","observation_id":"46102a7f-c4b2-430e-a1bb-0552fd654313","resolution":{"observed_at":"2026-08-06T20:31:47.950381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16690","last_updated":"2024-06-24T14:51:31Z","snapshot_observed_at":"2026-08-12T23:36:03.305357Z","submitted_at":"2024-06-24T14:51:31Z","title":"Scaling Laws for Linear Complexity Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.16690","snapshot_observed_at":"2026-08-06T20:31:47.953763Z","title":"Scaling laws for linear complexity language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.953763Z"},"links":{"cited_paper":"/paper/2406.16690","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:5334b7d28968f28e7033ea0a69500ced96203e3ab42bf5e4a5e2981c41705f73","observation_id":"df7e133b-f805-4a35-81f7-064cee55d01d","resolution":{"observed_at":"2026-08-06T20:31:47.953763Z","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":"2026-08-06T20:31:48.620628Z","title":"Searching for efficient transformers for language modeling","venue":null,"work_id":"bfe24dab-05a1-46a7-8f0b-1f279ba997fe","year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.957258Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:04e52d90cd7ce2bb8deb17bc52a3d2306d57f9543179d211a56614e9f43ac405","observation_id":"bdf97131-425f-473d-9128-8e70286c6a36","resolution":{"observed_at":"2026-08-06T20:31:48.624188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.961505Z","title":"Beyond neural scaling laws: beating power law scaling via data pruning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.961505Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:47e910479b9bcdc14ddacb613fa99b3df11c272c33ffbefdcb4548107e05e77b","observation_id":"6801fb92-50a7-4266-800d-26187a2e3a49","resolution":{"observed_at":"2026-08-06T20:31:47.961505Z","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":"2026-08-06T20:31:48.601027Z","title":"Introduction to linear algebra","venue":null,"work_id":"0c771479-9463-4c30-9498-94e50a49aeba","year":2022},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.965176Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:310bfdad782039553cc57ab40902e9bb22b2fc05ae66576af84f72848f62215b","observation_id":"b0fad808-806b-42f6-b332-7e33fd351338","resolution":{"observed_at":"2026-08-06T20:31:48.604410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.968446Z","title":"Roformer: Enhanced transformer with rotary position embedding","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.968446Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:63cafa6f1ed9ab43243fa92e32b529b47b56084a042947e0c93b0eee5c3b781e","observation_id":"13fe905a-2e17-408a-a2f3-3951992d2336","resolution":{"observed_at":"2026-08-06T20:31:47.968446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-06T20:31:47.972385Z","title":"Gemini: a family of highly capable multimodal models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.972385Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:ae292c75f30c4f301d377939458c80822fed3604297056db06b34afd13398246","observation_id":"b5793db7-c1be-46d9-b7f8-113e2647b778","resolution":{"observed_at":"2026-08-06T20:31:47.972385Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-06T20:31:47.975851Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.975851Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:191e98483af7783eadf6bef2527a96b1323d8a6f8ef59872530a3fb32dff7731","observation_id":"cf94e19e-fde5-4398-a263-95f5696d1932","resolution":{"observed_at":"2026-08-06T20:31:47.975851Z","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":"2026-08-06T20:31:48.581427Z","title":"On the uniform convergence of relative frequencies of events to their probabilities","venue":null,"work_id":"67f1e827-25f1-429b-bdb0-db3bd716056e","year":1968},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.979234Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:38ed1d3d15f861bc4efcb04e62f25d0a998a8b356f13955f3f9a4f05b750d257","observation_id":"9bd4d8bf-6a49-442d-af78-ccc248a73793","resolution":{"observed_at":"2026-08-06T20:31:48.585422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.982421Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.982421Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:49a6c404d0c8d348e1250e7eaac1abc95a9c8d3f59bc0333162ce384fac5a3cf","observation_id":"194abe7a-bc53-4dae-a01f-f76f132f7c73","resolution":{"observed_at":"2026-08-06T20:31:47.982421Z","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":"2026-08-06T20:31:48.561249Z","title":"Dcn v2: Improved deep & cross network and practical lessons for web-scale learning to rank systems","venue":null,"work_id":"d00989e0-c0a5-437e-876e-ea020cf99c2d","year":2021},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.985661Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:c3767ac713b6fe83761b3c458ea90b73784896a4c8788b610781b62db0632145","observation_id":"0e702b2e-fec5-4033-b4d5-6438bb9c529d","resolution":{"observed_at":"2026-08-06T20:31:48.565542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T20:31:47.989049Z","title":"Mmlu-pro: A more robust and challenging multi-task language understanding benchmark","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.989049Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:03ea203a61466d783c9b6770876e824ccf07f626f431eb69d1cbff3e18b17b37","observation_id":"7c70767d-2472-41d1-b22e-34022cde12bc","resolution":{"observed_at":"2026-08-06T20:31:47.989049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12424","last_updated":"2024-03-16T21:10:38Z","snapshot_observed_at":"2026-08-13T05:20:37.970631Z","submitted_at":"2023-11-21T08:32:38Z","title":"Looped Transformers are Better at Learning Learning Algorithms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12424","snapshot_observed_at":"2026-08-06T20:31:47.992493Z","title":"Looped transformers are better at learning learning algorithms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.992493Z"},"links":{"cited_paper":"/paper/2311.12424","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:886d52dda6891749064013f88e3455c6960a604029f56542e86dc48eb34e7b94","observation_id":"7baf9805-b726-47c2-987a-4119f5be4ac3","resolution":{"observed_at":"2026-08-06T20:31:47.992493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11089","last_updated":"2025-02-27T09:01:21Z","snapshot_observed_at":"2026-08-07T14:17:15.942844Z","submitted_at":"2025-02-16T11:53:44Z","title":"Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11089","snapshot_observed_at":"2026-08-06T20:31:47.995786Z","title":"Native sparse attention: Hardware-aligned and natively trainable sparse attention","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.995786Z"},"links":{"cited_paper":"/paper/2502.11089","citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:e5c724144ce0b54bb64cc62e7da18635fa6a6af30f5789b32ef1b2b91bbcf485","observation_id":"c5627278-022b-4e60-a142-af34a25a09b2","resolution":{"observed_at":"2026-08-06T20:31:47.995786Z","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":"2026-08-06T20:31:47.999795Z","title":"Big bird: Transformers for longer sequences","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:47.999795Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:fa24a6a9bbcc07860f70e927408828caea1d25b2320259728a62f0dce9ce6907","observation_id":"156c8414-88fe-4294-8961-e7f04c55fb01","resolution":{"observed_at":"2026-08-06T20:31:47.999795Z","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":"2026-08-06T20:31:48.003056Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T20:31:48.003056Z"},"links":{"citing_paper":"/paper/2507.02754"},"observation_digest":"sha256:f0ef1b12ff0d543245fb503007a37280ceb6d380210564e958499ae542292969","observation_id":"d01a39a2-e8f4-4d62-ae49-70fe1aa6f144","resolution":{"observed_at":"2026-08-06T20:31:48.003056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.02754","last_updated":"2025-07-03T16:16:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-11T01:37:01.996040Z","submitted_at":"2025-07-03T16:16:34Z","title":"Fast and Simplex: 2-Simplicial Attention in Triton"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":35,"verified_exact":1,"verified_fuzzy":10},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 4 inbound Pith citation observations for arXiv:2507.02754."}