{"as_of":"2026-08-11T13:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:741a672a5489ba95142a39187c3e4a191f1484db81b96a899e1d8682c30ef468","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:53:58.574061Z","state":"measured"},{"denominator":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2501.00530/citation-record","integrity":"/paper/2501.00530/integrity","json":"/paper/2501.00530/citation-record.json","paper":"/paper/2501.00530"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-10T22:53:58.486206Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.486206Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:7e3aa76461d041de4a8fc54130f55eb3ce1ed0f1c849951728c2833195dbf770","observation_id":"a59730ed-cbb6-45ec-bf9e-6f1ad074e6f1","resolution":{"observed_at":"2026-08-10T22:53:58.486206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-10T22:53:58.491852Z","title":"GPT-4 Technical Report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.491852Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:6e0d3e4f5f01de2ee7048704203806b73a169cdbf807cd57f9f56d6098dbc926","observation_id":"8ab48715-7ce4-420a-8e2e-ff68e93490c6","resolution":{"observed_at":"2026-08-10T22:53:58.491852Z","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":"2026-08-10T22:53:59.117316Z","title":"McCloskey and N","venue":null,"work_id":"7056037d-23ca-413c-9f6d-4f9511107c45","year":1989},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.496542Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:64d3c226be45597d2fd20cc6a5caeb501eddcdc606c653bbd8e639e1eb15331f","observation_id":"6f30da60-f181-4329-8299-7abd8871c122","resolution":{"observed_at":"2026-08-10T22:53:59.122302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.09707","last_updated":"2023-04-19T14:55:31Z","snapshot_observed_at":"2026-07-06T15:17:33.651803Z","submitted_at":"2023-04-19T14:55:31Z","title":"Disentangling Neuron Representations with Concept Vectors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.09707","snapshot_observed_at":"2026-08-10T22:53:58.501085Z","title":"Disentan- gling Neuron Representations with Concept Vec- tors.arXiv preprint arXiv:2304.09707, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.501085Z"},"links":{"cited_paper":"/paper/2304.09707","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:204f773181cbca79caa8b3632c7044d5d0bfbfa0c44d9b061b7dc18b0bbb4c6c","observation_id":"8d6bb2e5-be7d-4541-9a54-d0aceb65f815","resolution":{"observed_at":"2026-08-10T22:53:58.501085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1606.04671","last_updated":"2022-10-22T14:34:44Z","snapshot_observed_at":"2026-08-09T14:14:13.613085Z","submitted_at":"2016-06-15T08:20:51Z","title":"Progressive Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.04671","snapshot_observed_at":"2026-08-10T22:53:58.506144Z","title":"Rusu, Neil C","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.506144Z"},"links":{"cited_paper":"/paper/1606.04671","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:03d3bc339c593d022091c2a5e5452c3c459de1b39ee6d7a74e7e606b616ff394","observation_id":"1fd2c4d1-739a-4519-833c-69e5242b974d","resolution":{"observed_at":"2026-08-10T22:53:58.506144Z","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":"2026-08-10T22:53:59.104120Z","title":"Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran and Raia Hadsell","venue":null,"work_id":"812bd878-7595-4d63-a9a8-47c1cb1243cc","year":2017},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.511035Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:377b672fc51f6e046fa1f5285e25385abfcf333f8b4d2ad9c93df99498dd5d35","observation_id":"bafe454e-94e4-4458-b8e7-f664af9a432d","resolution":{"observed_at":"2026-08-10T22:53:59.108819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:59.090270Z","title":"Jacobs, Michael I","venue":null,"work_id":"666f0080-f24c-4df4-b9a7-506e52ff56c1","year":1991},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.515577Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:b90a5366c0995abfe9c8f49ab6de680978a50eb971efc79644161e1eb567b15f","observation_id":"e3ed9d42-8e19-46a0-98e6-01481e4e3754","resolution":{"observed_at":"2026-08-10T22:53:59.094350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:59.076975Z","title":"Outrageously large neural net- works: The sparsely-gated mixture-of-experts layer","venue":null,"work_id":"d84222ac-d93f-41f4-9088-343cafdfaa3e","year":2017},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.519335Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:7e186203d01106f669abd8ae3a47a522a4318733d155aa625fd39a79965bbc67","observation_id":"36391d15-130a-43f5-9d06-778fb95bc065","resolution":{"observed_at":"2026-08-10T22:53:59.081255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02852","last_updated":"2024-04-03T16:33:42Z","snapshot_observed_at":"2026-08-07T12:28:27.474474Z","submitted_at":"2024-04-03T16:33:42Z","title":"Toward Inference-optimal Mixture-of-Expert Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02852","snapshot_observed_at":"2026-08-10T22:53:58.523522Z","title":"Toward Inference-optimal Mixture-of-Expert Large Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.523522Z"},"links":{"cited_paper":"/paper/2404.02852","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:91a98c6a9220552bb095f04e7b305f48b8ca863f4ff32346e137bd37e8abe590","observation_id":"e290c4bd-76cd-4b00-990c-532da986a089","resolution":{"observed_at":"2026-08-10T22:53:58.523522Z","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":"2026-08-10T22:53:59.059251Z","title":"Parameter-efficient transfer learn- ing for NLP","venue":null,"work_id":"0505b4c8-350f-45e1-b6ab-6fa8d1143ae4","year":2019},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.527564Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:a4b3bb0c0d3aa01db2aa69107d507963c6c3297159684348354bff25e5b11ede","observation_id":"7eed3209-e674-4431-aa14-6f051f3da1df","resolution":{"observed_at":"2026-08-10T22:53:59.065120Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:59.044737Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, and Weizhu Chen","venue":null,"work_id":"9217c7df-7252-46ca-afa2-35c9df3080dd","year":2021},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.531404Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:3d363e2c4632a3c1c5a30cf9c4d1394deea3b0a879c5ffd30e7b16255fc59509","observation_id":"7921e84d-92b2-4322-9b46-592c351d5ea8","resolution":{"observed_at":"2026-08-10T22:53:59.049324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.12410","last_updated":"2022-11-02T02:47:17Z","snapshot_observed_at":"2026-08-10T12:45:09.426994Z","submitted_at":"2022-05-24T23:41:22Z","title":"AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.12410","snapshot_observed_at":"2026-08-10T22:53:58.535137Z","title":"AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.535137Z"},"links":{"cited_paper":"/paper/2205.12410","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:a434389a9615ec539e1bcf22640b8f0a0b4741d5438146697c4f872368418416","observation_id":"c3757fa6-6ca7-48ff-8027-35d393a3a73c","resolution":{"observed_at":"2026-08-10T22:53:58.535137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05444","last_updated":"2023-09-11T13:31:00Z","snapshot_observed_at":"2026-08-09T18:55:06.895022Z","submitted_at":"2023-09-11T13:31:00Z","title":"Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05444","snapshot_observed_at":"2026-08-10T22:53:58.539289Z","title":"Pushing mixture of experts to the limit: Ex- tremely parameter efficient moe for instruction tuning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.539289Z"},"links":{"cited_paper":"/paper/2309.05444","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:da8f8f48d08df67ab1ca54251b7bc97a8399181f76c2def8364ba811061d4beb","observation_id":"c8853ec3-6d50-424d-bdb1-dad0cb6c816a","resolution":{"observed_at":"2026-08-10T22:53:58.539289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00968","last_updated":"2024-04-02T19:57:32Z","snapshot_observed_at":"2026-08-06T07:40:00.188748Z","submitted_at":"2023-12-01T23:04:27Z","title":"Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00968","snapshot_observed_at":"2026-08-10T22:53:58.543636Z","title":"Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mix- ture of Low-rank Experts","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.543636Z"},"links":{"cited_paper":"/paper/2312.00968","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:7eedf33545b6d7305f218b42fd53ed2adc76e392541cf18118823b7746b23337","observation_id":"887ed76a-1e23-4718-a58f-6ce467f04336","resolution":{"observed_at":"2026-08-10T22:53:58.543636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10652","last_updated":"2022-09-21T20:49:26Z","snapshot_observed_at":"2026-07-06T13:54:56.779166Z","submitted_at":"2022-09-21T20:49:26Z","title":"Toy Models of Superposition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.10652","snapshot_observed_at":"2026-08-10T22:53:58.547524Z","title":"Toy Models of Superposition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.547524Z"},"links":{"cited_paper":"/paper/2209.10652","citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:e161ea634af5a847f6b709da83ba8ff19654aba045953e4b183630b2f1d29341","observation_id":"eb196863-f856-4015-8475-2d1b67528767","resolution":{"observed_at":"2026-08-10T22:53:58.547524Z","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":"2026-08-10T22:53:59.029183Z","title":"Zoom In: An Introduction to Circuits","venue":null,"work_id":"101fb150-8888-49de-af0f-d5d879f63ee6","year":2020},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.551921Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:02ca071995cf4673a80cf22509e78c766d4a88c95aa4bc33e16c2da924afe11e","observation_id":"fbf148f9-2614-41ef-a3db-95c46e18cc98","resolution":{"observed_at":"2026-08-10T22:53:59.033911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:59.014793Z","title":"Sparse autoencoders find highly interpretable features in language models","venue":null,"work_id":"e90e4a0e-1756-458f-81b2-3d0c73e71676","year":2024},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.555810Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:440ab716fd1f8648b09a76b36dd1b2e8527ba4e61a9738c15af5c72da3b1658d","observation_id":"143f49b2-5b92-4fab-8f03-948729ca5547","resolution":{"observed_at":"2026-08-10T22:53:59.019277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:58.996987Z","title":"Towards Monosemanticity: Decomposing Language Mod- els With Dictionary Learning","venue":null,"work_id":"655b5abe-d15f-4ea0-9334-f640ea408901","year":2023},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.561047Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:81663a58924a12fcde8804a13ad86296c0c7f7a6935995bcfca9c951d0202198","observation_id":"278a7bb2-49a6-4501-88a7-cd392e5b9ac8","resolution":{"observed_at":"2026-08-10T22:53:59.002746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:58.982496Z","title":"Train big, then compress: Rethinking model size for efficient training and inference of transformers","venue":null,"work_id":"9347b2f0-e163-4066-8c59-fb7cb4da8c11","year":2020},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.565771Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:b09f27279a98f1a462a36ca1d0a5319b70ed2433420b99c1813d599cf7526c12","observation_id":"088cf15a-d8eb-4462-aef0-1627dd903fd3","resolution":{"observed_at":"2026-08-10T22:53:58.986974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:58.968108Z","title":"Merging mod- els with fisher-weighted averaging","venue":null,"work_id":"a0a1b2c5-1697-475d-926e-da88ac29bb35","year":2022},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.570106Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:5324618e5f050f25302629ee5879718fa3c5d13e5c28826580084ad6d6d3036c","observation_id":"24d2056b-fb7b-4c88-84e4-875ac88358fe","resolution":{"observed_at":"2026-08-10T22:53:58.973020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T22:53:58.951786Z","title":"Language Models are Unsupervised Multitask Learners","venue":null,"work_id":"77e65bad-3049-4688-b7a7-1f618d8bee93","year":2019},"citing_paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T22:53:58.574061Z"},"links":{"citing_paper":"/paper/2501.00530"},"observation_digest":"sha256:b5b103b7b618308ef6109aafdc9898522bf7453bb369304dfe8743c90ca9ebfd","observation_id":"b7f0c151-ebff-4740-a708-cb77aa804619","resolution":{"observed_at":"2026-08-10T22:53:58.958715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.00530","last_updated":"2025-01-06T23:02:42Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T09:40:40.805578Z","submitted_at":"2024-12-31T16:28:23Z","title":"Superposition in Transformers: A Novel Way of Building Mixture of Experts"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":21},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2501.00530."}