{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ZRWWXR3JJJ3GRHVS5V3EJH6ONM","short_pith_number":"pith:ZRWWXR3J","canonical_record":{"source":{"id":"2201.10777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-01-26T06:53:46Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cb94f2eafb5862566d6773439acd8434c35c93135e358f172d17ee9d67ab0c2e","abstract_canon_sha256":"88d170f2f95be39a708671dc5bd7b5a5f2f22b998c2aa6c17afbcff18840e779"},"schema_version":"1.0"},"canonical_sha256":"cc6d6bc7694a76689eb2ed76449fce6b0a22a862d3b190d1d64b9843cd086f56","source":{"kind":"arxiv","id":"2201.10777","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.10777","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2201.10777v1","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.10777","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"ZRWWXR3JJJ3G","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"ZRWWXR3JJJ3GRHVS","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"ZRWWXR3J","created_at":"2026-07-05T03:51:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ZRWWXR3JJJ3GRHVS5V3EJH6ONM","target":"record","payload":{"canonical_record":{"source":{"id":"2201.10777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-01-26T06:53:46Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"cb94f2eafb5862566d6773439acd8434c35c93135e358f172d17ee9d67ab0c2e","abstract_canon_sha256":"88d170f2f95be39a708671dc5bd7b5a5f2f22b998c2aa6c17afbcff18840e779"},"schema_version":"1.0"},"canonical_sha256":"cc6d6bc7694a76689eb2ed76449fce6b0a22a862d3b190d1d64b9843cd086f56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:51:49.502670Z","signature_b64":"4eGVEBpDmbY+eREejBITR8Xkat8SrOMTXhNC5WqPJ+u2sictDXjWH2WFahIf5ph7KgfMTvWcnNwyg9h2E37sBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc6d6bc7694a76689eb2ed76449fce6b0a22a862d3b190d1d64b9843cd086f56","last_reissued_at":"2026-07-05T03:51:49.502286Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:51:49.502286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2201.10777","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":"2026-07-05T03:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ve0+J1zahRFvDXbxZFGCxul4S++sXdJ3okHqS0mrnv8tlnNPKW2VePNv9n5HNYzu9cYzvcftkqWpC2vuGGDiAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:41:46.853712Z"},"content_sha256":"e217b4e710ca2a216218630bfc25a5ec33acea28d1db840f8c22a12224dc5be7","schema_version":"1.0","event_id":"sha256:e217b4e710ca2a216218630bfc25a5ec33acea28d1db840f8c22a12224dc5be7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ZRWWXR3JJJ3GRHVS5V3EJH6ONM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Meta-learning Spiking Neural Networks with Surrogate Gradient Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Emre Neftci, Kenneth Stewart","submitted_at":"2022-01-26T06:53:46Z","abstract_excerpt":"Adaptive \"life-long\" learning at the edge and during online task performance is an aspirational goal of AI research. Neuromorphic hardware implementing Spiking Neural Networks (SNNs) are particularly attractive in this regard, as their real-time, event-based, local computing paradigm makes them suitable for edge implementations and fast learning. However, the long and iterative learning that characterizes state-of-the-art SNN training is incompatible with the physical nature and real-time operation of neuromorphic hardware. Bi-level learning, such as meta-learning is increasingly used in deep "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.10777","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/2201.10777/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":"2026-07-05T03:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mC4NcxXYtsPKDkDD2xU9k9rMoet5iAk5g60Dv6JHp7c7twxo9Ti0/cZ+22Y9sjXCWkjXedI8kFIwjIAxxqH2Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:41:46.854697Z"},"content_sha256":"73de63060d11bce6183255829ef38403cac72121b4dd1187acc57d6e1f9b1332","schema_version":"1.0","event_id":"sha256:73de63060d11bce6183255829ef38403cac72121b4dd1187acc57d6e1f9b1332"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/bundle.json","state_url":"https://pith.science/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/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":"2026-08-19T17:41:46Z","links":{"resolver":"https://pith.science/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM","bundle":"https://pith.science/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/bundle.json","state":"https://pith.science/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZRWWXR3JJJ3GRHVS5V3EJH6ONM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ZRWWXR3JJJ3GRHVS5V3EJH6ONM","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":"88d170f2f95be39a708671dc5bd7b5a5f2f22b998c2aa6c17afbcff18840e779","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-01-26T06:53:46Z","title_canon_sha256":"cb94f2eafb5862566d6773439acd8434c35c93135e358f172d17ee9d67ab0c2e"},"schema_version":"1.0","source":{"id":"2201.10777","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.10777","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2201.10777v1","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.10777","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"ZRWWXR3JJJ3G","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"ZRWWXR3JJJ3GRHVS","created_at":"2026-07-05T03:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"ZRWWXR3J","created_at":"2026-07-05T03:51:49Z"}],"graph_snapshots":[{"event_id":"sha256:73de63060d11bce6183255829ef38403cac72121b4dd1187acc57d6e1f9b1332","target":"graph","created_at":"2026-07-05T03:51:49Z","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/2201.10777/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Adaptive \"life-long\" learning at the edge and during online task performance is an aspirational goal of AI research. Neuromorphic hardware implementing Spiking Neural Networks (SNNs) are particularly attractive in this regard, as their real-time, event-based, local computing paradigm makes them suitable for edge implementations and fast learning. However, the long and iterative learning that characterizes state-of-the-art SNN training is incompatible with the physical nature and real-time operation of neuromorphic hardware. Bi-level learning, such as meta-learning is increasingly used in deep ","authors_text":"Emre Neftci, Kenneth Stewart","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-01-26T06:53:46Z","title":"Meta-learning Spiking Neural Networks with Surrogate Gradient Descent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.10777","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:e217b4e710ca2a216218630bfc25a5ec33acea28d1db840f8c22a12224dc5be7","target":"record","created_at":"2026-07-05T03:51:49Z","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":"88d170f2f95be39a708671dc5bd7b5a5f2f22b998c2aa6c17afbcff18840e779","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2022-01-26T06:53:46Z","title_canon_sha256":"cb94f2eafb5862566d6773439acd8434c35c93135e358f172d17ee9d67ab0c2e"},"schema_version":"1.0","source":{"id":"2201.10777","kind":"arxiv","version":1}},"canonical_sha256":"cc6d6bc7694a76689eb2ed76449fce6b0a22a862d3b190d1d64b9843cd086f56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc6d6bc7694a76689eb2ed76449fce6b0a22a862d3b190d1d64b9843cd086f56","first_computed_at":"2026-07-05T03:51:49.502286Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:51:49.502286Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4eGVEBpDmbY+eREejBITR8Xkat8SrOMTXhNC5WqPJ+u2sictDXjWH2WFahIf5ph7KgfMTvWcnNwyg9h2E37sBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:51:49.502670Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.10777","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e217b4e710ca2a216218630bfc25a5ec33acea28d1db840f8c22a12224dc5be7","sha256:73de63060d11bce6183255829ef38403cac72121b4dd1187acc57d6e1f9b1332"],"state_sha256":"f806b1fdcabaa3db602a7641702ef936161e2d3438d7bf82c2a74a0184497fd0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0zJAuZO8BA6VihGX9j7NGXE4N6MiPPP+ALjCWuW1qtnd5Qj6XYy+GHTJ9Wl9zZ+sXtP8aRjjDCKjFqC3Gc9QBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T17:41:46.860654Z","bundle_sha256":"845baf76349be9a0bb2ab0db8df1762dca227e02c8683de700821117751a8240"}}