{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:2DHVDUPRHJGS62GLY7YZFINL7N","short_pith_number":"pith:2DHVDUPR","canonical_record":{"source":{"id":"2205.07856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T00:16:09Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2ff5e9fb8622f39c8d2f9f82274c19f759eba17f5a81f15794b85c85ad5e6f5e","abstract_canon_sha256":"91860c52fb29175ed11a60aed9d06107c08aaa76200511fb88785cb31851d8c1"},"schema_version":"1.0"},"canonical_sha256":"d0cf51d1f13a4d2f68cbc7f192a1abfb6e149e88c929bc620a31b64db10cb325","source":{"kind":"arxiv","id":"2205.07856","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.07856","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"arxiv_version","alias_value":"2205.07856v1","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.07856","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_12","alias_value":"2DHVDUPRHJGS","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_16","alias_value":"2DHVDUPRHJGS62GL","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_8","alias_value":"2DHVDUPR","created_at":"2026-07-05T04:23:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:2DHVDUPRHJGS62GLY7YZFINL7N","target":"record","payload":{"canonical_record":{"source":{"id":"2205.07856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T00:16:09Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2ff5e9fb8622f39c8d2f9f82274c19f759eba17f5a81f15794b85c85ad5e6f5e","abstract_canon_sha256":"91860c52fb29175ed11a60aed9d06107c08aaa76200511fb88785cb31851d8c1"},"schema_version":"1.0"},"canonical_sha256":"d0cf51d1f13a4d2f68cbc7f192a1abfb6e149e88c929bc620a31b64db10cb325","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:23:56.542114Z","signature_b64":"HSit6rpaNnYsCgdUSFBm7eFxw3f3Ebu/vNNgsnychDYxUg98K8xxXG2IjpzcGupNJfXFHGSqdScTZjdQuej3AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0cf51d1f13a4d2f68cbc7f192a1abfb6e149e88c929bc620a31b64db10cb325","last_reissued_at":"2026-07-05T04:23:56.541693Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:23:56.541693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.07856","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":"2026-07-05T04:23:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vWbuv2d1tzM5cWyx61+JDkNIp5Za92QUrG+TrmK8Ue+zjjAG2imZzKW3ptUgITlfvia0hp/ZP+xey6GB6wZjDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T14:41:56.365577Z"},"content_sha256":"2b169fcdd7ed91b9320d659ff1c42b823abffd75ba650e149c7bd19e6f5b353f","schema_version":"1.0","event_id":"sha256:2b169fcdd7ed91b9320d659ff1c42b823abffd75ba650e149c7bd19e6f5b353f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:2DHVDUPRHJGS62GLY7YZFINL7N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Impact of Learning Rate on Noise Resistant Property of Deep Learning Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Lijun Qian, Omobayode Fagbohungbe","submitted_at":"2022-05-08T00:16:09Z","abstract_excerpt":"The interest in analog computation has grown tremendously in recent years due to its fast computation speed and excellent energy efficiency, which is very important for edge and IoT devices in the sub-watt power envelope for deep learning inferencing. However, significant performance degradation suffered by deep learning models due to the inherent noise present in the analog computation can limit their use in mission-critical applications. Hence, there is a need to understand the impact of critical model hyperparameters choice on the resulting model noise-resistant property. This need is criti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.07856","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/2205.07856/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":"2026-07-05T04:23:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fk+VYBr1obeFENtl2+de9v5zgbJp7r6tXLfnJ5m5mCCOhpwzYf0U+wyVin3lSiAnKcPC+MVsRiwzWSpMiOkRBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T14:41:56.366083Z"},"content_sha256":"4bd7b4b42a6cf353725596aef2b1e2014ebd9fa44f2b4104123539b4afebecc2","schema_version":"1.0","event_id":"sha256:4bd7b4b42a6cf353725596aef2b1e2014ebd9fa44f2b4104123539b4afebecc2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2DHVDUPRHJGS62GLY7YZFINL7N/bundle.json","state_url":"https://pith.science/pith/2DHVDUPRHJGS62GLY7YZFINL7N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2DHVDUPRHJGS62GLY7YZFINL7N/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":"2026-08-20T14:41:56Z","links":{"resolver":"https://pith.science/pith/2DHVDUPRHJGS62GLY7YZFINL7N","bundle":"https://pith.science/pith/2DHVDUPRHJGS62GLY7YZFINL7N/bundle.json","state":"https://pith.science/pith/2DHVDUPRHJGS62GLY7YZFINL7N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2DHVDUPRHJGS62GLY7YZFINL7N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:2DHVDUPRHJGS62GLY7YZFINL7N","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":"91860c52fb29175ed11a60aed9d06107c08aaa76200511fb88785cb31851d8c1","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T00:16:09Z","title_canon_sha256":"2ff5e9fb8622f39c8d2f9f82274c19f759eba17f5a81f15794b85c85ad5e6f5e"},"schema_version":"1.0","source":{"id":"2205.07856","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.07856","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"arxiv_version","alias_value":"2205.07856v1","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.07856","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_12","alias_value":"2DHVDUPRHJGS","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_16","alias_value":"2DHVDUPRHJGS62GL","created_at":"2026-07-05T04:23:56Z"},{"alias_kind":"pith_short_8","alias_value":"2DHVDUPR","created_at":"2026-07-05T04:23:56Z"}],"graph_snapshots":[{"event_id":"sha256:4bd7b4b42a6cf353725596aef2b1e2014ebd9fa44f2b4104123539b4afebecc2","target":"graph","created_at":"2026-07-05T04:23:56Z","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/2205.07856/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The interest in analog computation has grown tremendously in recent years due to its fast computation speed and excellent energy efficiency, which is very important for edge and IoT devices in the sub-watt power envelope for deep learning inferencing. However, significant performance degradation suffered by deep learning models due to the inherent noise present in the analog computation can limit their use in mission-critical applications. Hence, there is a need to understand the impact of critical model hyperparameters choice on the resulting model noise-resistant property. This need is criti","authors_text":"Lijun Qian, Omobayode Fagbohungbe","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T00:16:09Z","title":"Impact of Learning Rate on Noise Resistant Property of Deep Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.07856","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":"sha256:2b169fcdd7ed91b9320d659ff1c42b823abffd75ba650e149c7bd19e6f5b353f","target":"record","created_at":"2026-07-05T04:23:56Z","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":"91860c52fb29175ed11a60aed9d06107c08aaa76200511fb88785cb31851d8c1","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-08T00:16:09Z","title_canon_sha256":"2ff5e9fb8622f39c8d2f9f82274c19f759eba17f5a81f15794b85c85ad5e6f5e"},"schema_version":"1.0","source":{"id":"2205.07856","kind":"arxiv","version":1}},"canonical_sha256":"d0cf51d1f13a4d2f68cbc7f192a1abfb6e149e88c929bc620a31b64db10cb325","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d0cf51d1f13a4d2f68cbc7f192a1abfb6e149e88c929bc620a31b64db10cb325","first_computed_at":"2026-07-05T04:23:56.541693Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:23:56.541693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HSit6rpaNnYsCgdUSFBm7eFxw3f3Ebu/vNNgsnychDYxUg98K8xxXG2IjpzcGupNJfXFHGSqdScTZjdQuej3AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:23:56.542114Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.07856","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2b169fcdd7ed91b9320d659ff1c42b823abffd75ba650e149c7bd19e6f5b353f","sha256:4bd7b4b42a6cf353725596aef2b1e2014ebd9fa44f2b4104123539b4afebecc2"],"state_sha256":"c5a98afc6172e940e8b81a98d5d5692c601e9ca48b75ef97720f1ebefa3ca7bd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"68OHX6083urHv8w4EH9DA/vaaoHYuMWS/sAfsGRpoi5fa43RZuBR0+VaF00LE86TsuT76mkOLi1apipN6rDxCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T14:41:56.371278Z","bundle_sha256":"3df265d76cb2273d6fb85873118541b4898ef25b747ae74c1a1d029aeff92f21"}}