{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:AWAZZCU2OP44ZHBNYVNPGOKUMH","short_pith_number":"pith:AWAZZCU2","canonical_record":{"source":{"id":"2209.01667","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-04T18:00:29Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"a31a80bc2365248ba1a0a196f16373999260e1d1fbcc2d084fc2f45a12c04c02","abstract_canon_sha256":"de53585c0d9c575f80c9755e7a536a800a01598ce0789fd92365f70730e56234"},"schema_version":"1.0"},"canonical_sha256":"05819c8a9a73f9cc9c2dc55af3395461f102622132a80b6963fc411a4d12629d","source":{"kind":"arxiv","id":"2209.01667","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.01667","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"arxiv_version","alias_value":"2209.01667v1","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.01667","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_12","alias_value":"AWAZZCU2OP44","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_16","alias_value":"AWAZZCU2OP44ZHBN","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_8","alias_value":"AWAZZCU2","created_at":"2026-07-05T04:54:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:AWAZZCU2OP44ZHBNYVNPGOKUMH","target":"record","payload":{"canonical_record":{"source":{"id":"2209.01667","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-04T18:00:29Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"a31a80bc2365248ba1a0a196f16373999260e1d1fbcc2d084fc2f45a12c04c02","abstract_canon_sha256":"de53585c0d9c575f80c9755e7a536a800a01598ce0789fd92365f70730e56234"},"schema_version":"1.0"},"canonical_sha256":"05819c8a9a73f9cc9c2dc55af3395461f102622132a80b6963fc411a4d12629d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:54:31.988604Z","signature_b64":"rNMKOtRdTmDJY364ARFjgvSiWo2m5Uocz0Ne/DRlQI8thM8EFTpgVkkmk3wH15uxD5SVyaXlu2y3TbEkIsXhCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05819c8a9a73f9cc9c2dc55af3395461f102622132a80b6963fc411a4d12629d","last_reissued_at":"2026-07-05T04:54:31.988254Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:54:31.988254Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.01667","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:54:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VG86dYYzqQe9kX7YUUwRKc+nLkqLDMuSPz+xONjhY6d2kP9cBiHLLDK/E68LNYA783J2hfi8fFAzK/A+wtFaCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:45:07.717570Z"},"content_sha256":"55fbb52e2f500df28c1abdb4b78a8c3a8636db2ee18b8e69fc02aa4d4d5c3ede","schema_version":"1.0","event_id":"sha256:55fbb52e2f500df28c1abdb4b78a8c3a8636db2ee18b8e69fc02aa4d4d5c3ede"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:AWAZZCU2OP44ZHBNYVNPGOKUMH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Review of Sparse Expert Models in Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Barret Zoph, Jeff Dean, William Fedus","submitted_at":"2022-09-04T18:00:29Z","abstract_excerpt":"Sparse expert models are a thirty-year old concept re-emerging as a popular architecture in deep learning. This class of architecture encompasses Mixture-of-Experts, Switch Transformers, Routing Networks, BASE layers, and others, all with the unifying idea that each example is acted on by a subset of the parameters. By doing so, the degree of sparsity decouples the parameter count from the compute per example allowing for extremely large, but efficient models. The resulting models have demonstrated significant improvements across diverse domains such as natural language processing, computer vi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.01667","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2209.01667/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:54:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hPAvbdPjoI/+TwgZCaZnLYc81vBilJQHalE25mMmPWyj3NyQP89Fp8D8lSFhUB0C2mhZfeNV+ZTH5WKl1cbmCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:45:07.718095Z"},"content_sha256":"d5a77a248d92363eca38020fca7ab419901567cf3d2ac39631aee21fcf93196d","schema_version":"1.0","event_id":"sha256:d5a77a248d92363eca38020fca7ab419901567cf3d2ac39631aee21fcf93196d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/bundle.json","state_url":"https://pith.science/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T15:45:07Z","links":{"resolver":"https://pith.science/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH","bundle":"https://pith.science/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/bundle.json","state":"https://pith.science/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AWAZZCU2OP44ZHBNYVNPGOKUMH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:AWAZZCU2OP44ZHBNYVNPGOKUMH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"de53585c0d9c575f80c9755e7a536a800a01598ce0789fd92365f70730e56234","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-04T18:00:29Z","title_canon_sha256":"a31a80bc2365248ba1a0a196f16373999260e1d1fbcc2d084fc2f45a12c04c02"},"schema_version":"1.0","source":{"id":"2209.01667","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.01667","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"arxiv_version","alias_value":"2209.01667v1","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.01667","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_12","alias_value":"AWAZZCU2OP44","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_16","alias_value":"AWAZZCU2OP44ZHBN","created_at":"2026-07-05T04:54:31Z"},{"alias_kind":"pith_short_8","alias_value":"AWAZZCU2","created_at":"2026-07-05T04:54:31Z"}],"graph_snapshots":[{"event_id":"sha256:d5a77a248d92363eca38020fca7ab419901567cf3d2ac39631aee21fcf93196d","target":"graph","created_at":"2026-07-05T04:54:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2209.01667/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sparse expert models are a thirty-year old concept re-emerging as a popular architecture in deep learning. This class of architecture encompasses Mixture-of-Experts, Switch Transformers, Routing Networks, BASE layers, and others, all with the unifying idea that each example is acted on by a subset of the parameters. By doing so, the degree of sparsity decouples the parameter count from the compute per example allowing for extremely large, but efficient models. The resulting models have demonstrated significant improvements across diverse domains such as natural language processing, computer vi","authors_text":"Barret Zoph, Jeff Dean, William Fedus","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-04T18:00:29Z","title":"A Review of Sparse Expert Models in Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.01667","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:55fbb52e2f500df28c1abdb4b78a8c3a8636db2ee18b8e69fc02aa4d4d5c3ede","target":"record","created_at":"2026-07-05T04:54:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"de53585c0d9c575f80c9755e7a536a800a01598ce0789fd92365f70730e56234","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-04T18:00:29Z","title_canon_sha256":"a31a80bc2365248ba1a0a196f16373999260e1d1fbcc2d084fc2f45a12c04c02"},"schema_version":"1.0","source":{"id":"2209.01667","kind":"arxiv","version":1}},"canonical_sha256":"05819c8a9a73f9cc9c2dc55af3395461f102622132a80b6963fc411a4d12629d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05819c8a9a73f9cc9c2dc55af3395461f102622132a80b6963fc411a4d12629d","first_computed_at":"2026-07-05T04:54:31.988254Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:54:31.988254Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rNMKOtRdTmDJY364ARFjgvSiWo2m5Uocz0Ne/DRlQI8thM8EFTpgVkkmk3wH15uxD5SVyaXlu2y3TbEkIsXhCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:54:31.988604Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.01667","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55fbb52e2f500df28c1abdb4b78a8c3a8636db2ee18b8e69fc02aa4d4d5c3ede","sha256:d5a77a248d92363eca38020fca7ab419901567cf3d2ac39631aee21fcf93196d"],"state_sha256":"45376772b3aa2681defa29285298284b59cec9b648d3a826a19240dcc06b5e3b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aF3ckIYGNwdGrqbH1r/SgzFaFe989Ajn7iBhWfUocoKj7+gPhVAv/fhL0pcXGlNRjUndsbP3S6JCqQtaTGkaCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:45:07.722500Z","bundle_sha256":"da54f54bf9d15ae005d555ec8fa8e8909e111b3e32cb804210d68f9884f776a1"}}