{"as_of":"2026-08-10T14:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:776d1bfc0e30a6e3fddad14b9a6bea0afda011c5cc471fdb3388e90aa20c6372","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:41:06.663514Z","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":"2026-07-02T23:07:26.908775Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","version":3},"cited_work":{"arxiv_id":"2110.01786","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.01786","snapshot_observed_at":"2026-07-02T23:07:26.908775Z","title":"Moefication: Transformer feed-forward layers are mixtures of experts","venue":null,"work_id":"8bbd46fd-dadc-4762-a85f-501e5406b4de","year":2021},"citing_paper":{"arxiv_id":"2502.04416","last_updated":"2026-04-23T00:51:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-06T14:05:30Z","title":"Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-23T04:08:29.089438Z"},"links":{"cited_paper":"/paper/2110.01786","citing_paper":"/paper/2502.04416"},"observation_digest":"sha256:4f0c4a21708672e8462e1eae627dd0f9c101493bc0c6714965f9b077859450b5","observation_id":"7517892b-b5a4-41a8-821c-fd4d8368920b","resolution":{"observed_at":"2026-05-23T04:12:31.089016Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.01786","snapshot_observed_at":"2026-08-07T05:41:06.663514Z","title":"Moefication: Transformer feed-forward layers are mixtures of experts","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.08054","last_updated":"2025-06-11T02:33:59Z","snapshot_observed_at":"2026-08-10T13:40:37.660137Z","submitted_at":"2025-06-09T04:05:00Z","title":"STAMImputer: Spatio-Temporal Attention MoE for Traffic Data Imputation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:41:06.663514Z"},"links":{"cited_paper":"/paper/2110.01786","citing_paper":"/paper/2506.08054"},"observation_digest":"sha256:2b0c342191e0a324ef5c661f84aba653eb77339bf7576dd9d503c281a686f304","observation_id":"c61f3149-415b-4b46-8d4d-40729afc244e","resolution":{"observed_at":"2026-08-07T05:41:06.663514Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","version":3},"cited_work":{"arxiv_id":"2110.01786","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.01786","snapshot_observed_at":"2026-07-02T23:07:26.908775Z","title":"Moefication: Transformer feed-forward layers are mixtures of experts","venue":null,"work_id":"8bbd46fd-dadc-4762-a85f-501e5406b4de","year":2021},"citing_paper":{"arxiv_id":"2506.12119","last_updated":"2026-05-17T08:18:55Z","snapshot_observed_at":"2026-08-02T23:22:23.397250Z","submitted_at":"2025-06-13T17:59:05Z","title":"Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-22T00:05:08.916339Z"},"links":{"cited_paper":"/paper/2110.01786","citing_paper":"/paper/2506.12119"},"observation_digest":"sha256:c9e73cb365b278150a3ee7661466a5bc2f16999b955dec4e0cd22d67b3ccaeac","observation_id":"280b87f7-95ae-40a7-a53d-0a4de84dd515","resolution":{"observed_at":"2026-05-22T00:05:47.722120Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.01786","snapshot_observed_at":"2026-08-06T17:47:40.269657Z","title":"MoEfica- tion: Transformer feed-forward layers are mixtures of experts,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.09955","last_updated":"2025-07-14T06:10:30Z","snapshot_observed_at":"2026-08-07T11:12:53.489576Z","submitted_at":"2025-07-14T06:10:30Z","title":"DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models","version":1},"reference_index":104,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:40.269657Z"},"links":{"cited_paper":"/paper/2110.01786","citing_paper":"/paper/2507.09955"},"observation_digest":"sha256:df6566d3dbf05adb959811dba6162c904f9994ab74a6c6072bd7b333169482ad","observation_id":"f4e1e821-e3a6-47a1-8fe6-7141d0f161eb","resolution":{"observed_at":"2026-08-06T17:47:40.269657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","version":3},"cited_work":{"arxiv_id":"2110.01786","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.01786","snapshot_observed_at":"2026-07-02T23:07:26.908775Z","title":"Moefication: Transformer feed-forward layers are mixtures of experts","venue":null,"work_id":"8bbd46fd-dadc-4762-a85f-501e5406b4de","year":2021},"citing_paper":{"arxiv_id":"2606.08814","last_updated":"2026-06-07T20:07:24Z","snapshot_observed_at":"2026-08-02T23:58:50.946844Z","submitted_at":"2026-06-07T20:07:24Z","title":"STAR: Rethinking MoE Routing as Structure-Aware Subspace Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T18:28:35.162934Z"},"links":{"cited_paper":"/paper/2110.01786","citing_paper":"/paper/2606.08814"},"observation_digest":"sha256:e93b71bd351430827d26cf5e9814a68098fc1ec272718ad91dde9275cbca6010","observation_id":"1ce9c816-0aed-46dc-a369-56755392d1ee","resolution":{"observed_at":"2026-07-02T23:07:26.910568Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2110.01786/citation-record","integrity":"/paper/2110.01786/integrity","json":"/paper/2110.01786/citation-record.json","paper":"/paper/2110.01786"},"outbound":[],"paper":{"arxiv_id":"2110.01786","last_updated":"2022-04-05T07:35:52Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-05T02:22:16.301608Z","submitted_at":"2021-10-05T02:14:38Z","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2110.01786."}