{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:WX3SZVQ2KJ3EISMPDTNJMYHLUP","short_pith_number":"pith:WX3SZVQ2","canonical_record":{"source":{"id":"2211.08410","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-10-27T08:13:20Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cad6a4e32fbda4776e4452d2b4d785259a9097cc391efd3a3a8ba1c26ecf9e65","abstract_canon_sha256":"bb697ee9ecf4b034e2f5b57c45515229e0dfd12b72cc0bb5a7b4c9048a9791a9"},"schema_version":"1.0"},"canonical_sha256":"b5f72cd61a527644498f1cda9660eba3dac977530bf13b09bd12b63b1c2c492c","source":{"kind":"arxiv","id":"2211.08410","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.08410","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"arxiv_version","alias_value":"2211.08410v1","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.08410","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_12","alias_value":"WX3SZVQ2KJ3E","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_16","alias_value":"WX3SZVQ2KJ3EISMP","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_8","alias_value":"WX3SZVQ2","created_at":"2026-07-05T05:16:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:WX3SZVQ2KJ3EISMPDTNJMYHLUP","target":"record","payload":{"canonical_record":{"source":{"id":"2211.08410","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-10-27T08:13:20Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cad6a4e32fbda4776e4452d2b4d785259a9097cc391efd3a3a8ba1c26ecf9e65","abstract_canon_sha256":"bb697ee9ecf4b034e2f5b57c45515229e0dfd12b72cc0bb5a7b4c9048a9791a9"},"schema_version":"1.0"},"canonical_sha256":"b5f72cd61a527644498f1cda9660eba3dac977530bf13b09bd12b63b1c2c492c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:16:29.094341Z","signature_b64":"c2X8Pcx1RU4QMd8fVNQQBbDjuvwMt571J6k8SiZC9opS1RRnO1Z+Va+RsUNZGLWecVWX6Lyw3EadWcd7lBdmBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b5f72cd61a527644498f1cda9660eba3dac977530bf13b09bd12b63b1c2c492c","last_reissued_at":"2026-07-05T05:16:29.093898Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:16:29.093898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.08410","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":"2026-07-05T05:16:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xUJIfbp/ApGFFpjXfHybkFK3wMo1zG1Bv3mXGRWhtn79/XJzp6zg+VbxPNFMfTLdfiDzSJfGks7ze3kESuEoCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:19:25.220741Z"},"content_sha256":"e71c026c328bd3b004dbffb54e40f03cecdfdb668bce21fe81f57791d830cbd6","schema_version":"1.0","event_id":"sha256:e71c026c328bd3b004dbffb54e40f03cecdfdb668bce21fe81f57791d830cbd6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:WX3SZVQ2KJ3EISMPDTNJMYHLUP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Jun Zhou, Weng-Fai Wong, Zhanglu Yan","submitted_at":"2022-10-27T08:13:20Z","abstract_excerpt":"Spiking neural networks (SNNs) are well suited for resource-constrained applications as they do not need expensive multipliers. In a typical rate-encoded SNN, a series of binary spikes within a globally fixed time window is used to fire the neurons. The maximum number of spikes in this time window is also the latency of the network in performing a single inference, as well as determines the overall energy efficiency of the model. The aim of this paper is to reduce this while maintaining accuracy when converting ANNs to their equivalent SNNs. The state-of-the-art conversion schemes yield SNNs w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.08410","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/2211.08410/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":"2026-07-05T05:16:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/Z6fJpUwfw/WPUda5AWKZWaOE2I/5kUnyJetzgiycAJC12M8li8hDFtkrHsfTE0rqdRtse3dTJTUZkSMRRzmCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:19:25.221300Z"},"content_sha256":"f1cdac74030a1afea4ddf2633d99e060fac189719bee90c29fc154f88aac53fd","schema_version":"1.0","event_id":"sha256:f1cdac74030a1afea4ddf2633d99e060fac189719bee90c29fc154f88aac53fd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/bundle.json","state_url":"https://pith.science/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/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":"2026-08-08T19:19:25Z","links":{"resolver":"https://pith.science/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP","bundle":"https://pith.science/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/bundle.json","state":"https://pith.science/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WX3SZVQ2KJ3EISMPDTNJMYHLUP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WX3SZVQ2KJ3EISMPDTNJMYHLUP","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":"bb697ee9ecf4b034e2f5b57c45515229e0dfd12b72cc0bb5a7b4c9048a9791a9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-10-27T08:13:20Z","title_canon_sha256":"cad6a4e32fbda4776e4452d2b4d785259a9097cc391efd3a3a8ba1c26ecf9e65"},"schema_version":"1.0","source":{"id":"2211.08410","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.08410","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"arxiv_version","alias_value":"2211.08410v1","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.08410","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_12","alias_value":"WX3SZVQ2KJ3E","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_16","alias_value":"WX3SZVQ2KJ3EISMP","created_at":"2026-07-05T05:16:29Z"},{"alias_kind":"pith_short_8","alias_value":"WX3SZVQ2","created_at":"2026-07-05T05:16:29Z"}],"graph_snapshots":[{"event_id":"sha256:f1cdac74030a1afea4ddf2633d99e060fac189719bee90c29fc154f88aac53fd","target":"graph","created_at":"2026-07-05T05:16:29Z","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/2211.08410/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spiking neural networks (SNNs) are well suited for resource-constrained applications as they do not need expensive multipliers. In a typical rate-encoded SNN, a series of binary spikes within a globally fixed time window is used to fire the neurons. The maximum number of spikes in this time window is also the latency of the network in performing a single inference, as well as determines the overall energy efficiency of the model. The aim of this paper is to reduce this while maintaining accuracy when converting ANNs to their equivalent SNNs. The state-of-the-art conversion schemes yield SNNs w","authors_text":"Jun Zhou, Weng-Fai Wong, Zhanglu Yan","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-10-27T08:13:20Z","title":"Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.08410","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:e71c026c328bd3b004dbffb54e40f03cecdfdb668bce21fe81f57791d830cbd6","target":"record","created_at":"2026-07-05T05:16:29Z","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":"bb697ee9ecf4b034e2f5b57c45515229e0dfd12b72cc0bb5a7b4c9048a9791a9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-10-27T08:13:20Z","title_canon_sha256":"cad6a4e32fbda4776e4452d2b4d785259a9097cc391efd3a3a8ba1c26ecf9e65"},"schema_version":"1.0","source":{"id":"2211.08410","kind":"arxiv","version":1}},"canonical_sha256":"b5f72cd61a527644498f1cda9660eba3dac977530bf13b09bd12b63b1c2c492c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b5f72cd61a527644498f1cda9660eba3dac977530bf13b09bd12b63b1c2c492c","first_computed_at":"2026-07-05T05:16:29.093898Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:16:29.093898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c2X8Pcx1RU4QMd8fVNQQBbDjuvwMt571J6k8SiZC9opS1RRnO1Z+Va+RsUNZGLWecVWX6Lyw3EadWcd7lBdmBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:16:29.094341Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.08410","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e71c026c328bd3b004dbffb54e40f03cecdfdb668bce21fe81f57791d830cbd6","sha256:f1cdac74030a1afea4ddf2633d99e060fac189719bee90c29fc154f88aac53fd"],"state_sha256":"2f0da934332f29f4f379f80fc3db5bc15b942da7debfafcf47d48b3977bb7425"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hcbY6xuA2WRUNbNDklhsL2rExaXF6j8YfcEVBwN8fqYMPuDC5ILVYdw1U9okPg7RIaZKHk5iIwibMMLf3qXVBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T19:19:25.226207Z","bundle_sha256":"963b1b5bdda9868ed1ca3183cdaf77c40a6facea7ea1287b32c589e16fd9c77c"}}