{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AS2A526U4MXZP4MVEWOVUD4UVX","short_pith_number":"pith:AS2A526U","canonical_record":{"source":{"id":"2402.00411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-02-01T08:10:39Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ccf02b311bf4d37d32f4122310964d68018e8af6071e2e074e1c63d02d336d54","abstract_canon_sha256":"16880d20f3c756b659fcc0792acb6688dd97afd92c2f950351111fc76e2aa1e7"},"schema_version":"1.0"},"canonical_sha256":"04b40eebd4e32f97f195259d5a0f94adcd189cde74c08fa3af4078c8120d76c8","source":{"kind":"arxiv","id":"2402.00411","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00411","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00411v2","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00411","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_12","alias_value":"AS2A526U4MXZ","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_16","alias_value":"AS2A526U4MXZP4MV","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_8","alias_value":"AS2A526U","created_at":"2026-07-05T09:17:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AS2A526U4MXZP4MVEWOVUD4UVX","target":"record","payload":{"canonical_record":{"source":{"id":"2402.00411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-02-01T08:10:39Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ccf02b311bf4d37d32f4122310964d68018e8af6071e2e074e1c63d02d336d54","abstract_canon_sha256":"16880d20f3c756b659fcc0792acb6688dd97afd92c2f950351111fc76e2aa1e7"},"schema_version":"1.0"},"canonical_sha256":"04b40eebd4e32f97f195259d5a0f94adcd189cde74c08fa3af4078c8120d76c8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:17:36.936380Z","signature_b64":"OgzMir+Qjoh/VLL4UfwnJ0ckcl23PzMZ4GIJjNRQIcKeOTcRTeMC2U6eWqlsK1PXtfEUrrWmHmuK6OUYdEvmDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04b40eebd4e32f97f195259d5a0f94adcd189cde74c08fa3af4078c8120d76c8","last_reissued_at":"2026-07-05T09:17:36.935810Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:17:36.935810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.00411","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:17:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vCcDGqJjnB80j8cUZ0MdL2BCA6YVReIVez0/UIpSF8g8fqCsmJGChC/MWfd4ckPQrzwhCdL1+fVjXA1zRDbICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:18:12.137444Z"},"content_sha256":"c7e163416be987664632cee5adaff8ccd986df790488a644d15562bdaed9086e","schema_version":"1.0","event_id":"sha256:c7e163416be987664632cee5adaff8ccd986df790488a644d15562bdaed9086e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AS2A526U4MXZP4MVEWOVUD4UVX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.NE","authors_text":"Tiejun Huang, Xinyu Shi, Yujia Liu, Zecheng Hao, Zhaofei Yu","submitted_at":"2024-02-01T08:10:39Z","abstract_excerpt":"Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has garnered widespread academic interest for its intrinsic ability to transmit information in a more energy-efficient manner. However, despite previous efforts to optimize the learning algorithm of SNNs through various methods, SNNs still lag behind ANNs in terms of performance. The recently proposed multi-threshold model provides more possibilities for further enhancing the learning capability of SNNs. In this paper, we rigorously analyze the relationship among the multi-threshold model, vanilla spiking mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00411","kind":"arxiv","version":2},"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/2402.00411/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":"2026-07-05T09:17:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0xXpBM8YlM3PnO84g3lBt0fW1QdbkSQfQEZmqTdXlpmpdIBlFlAOhazYtBr0K4Mv1OdQmnDJhGVEt1xqotydBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:18:12.137986Z"},"content_sha256":"7ba64582825d2efc69c4fd5b4db4b83d7d666c68669340f362808aa759313ac0","schema_version":"1.0","event_id":"sha256:7ba64582825d2efc69c4fd5b4db4b83d7d666c68669340f362808aa759313ac0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AS2A526U4MXZP4MVEWOVUD4UVX/bundle.json","state_url":"https://pith.science/pith/AS2A526U4MXZP4MVEWOVUD4UVX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AS2A526U4MXZP4MVEWOVUD4UVX/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":"2026-08-09T13:18:12Z","links":{"resolver":"https://pith.science/pith/AS2A526U4MXZP4MVEWOVUD4UVX","bundle":"https://pith.science/pith/AS2A526U4MXZP4MVEWOVUD4UVX/bundle.json","state":"https://pith.science/pith/AS2A526U4MXZP4MVEWOVUD4UVX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AS2A526U4MXZP4MVEWOVUD4UVX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AS2A526U4MXZP4MVEWOVUD4UVX","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":"16880d20f3c756b659fcc0792acb6688dd97afd92c2f950351111fc76e2aa1e7","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-02-01T08:10:39Z","title_canon_sha256":"ccf02b311bf4d37d32f4122310964d68018e8af6071e2e074e1c63d02d336d54"},"schema_version":"1.0","source":{"id":"2402.00411","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00411","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00411v2","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00411","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_12","alias_value":"AS2A526U4MXZ","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_16","alias_value":"AS2A526U4MXZP4MV","created_at":"2026-07-05T09:17:36Z"},{"alias_kind":"pith_short_8","alias_value":"AS2A526U","created_at":"2026-07-05T09:17:36Z"}],"graph_snapshots":[{"event_id":"sha256:7ba64582825d2efc69c4fd5b4db4b83d7d666c68669340f362808aa759313ac0","target":"graph","created_at":"2026-07-05T09:17:36Z","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/2402.00411/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has garnered widespread academic interest for its intrinsic ability to transmit information in a more energy-efficient manner. However, despite previous efforts to optimize the learning algorithm of SNNs through various methods, SNNs still lag behind ANNs in terms of performance. The recently proposed multi-threshold model provides more possibilities for further enhancing the learning capability of SNNs. In this paper, we rigorously analyze the relationship among the multi-threshold model, vanilla spiking mod","authors_text":"Tiejun Huang, Xinyu Shi, Yujia Liu, Zecheng Hao, Zhaofei Yu","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-02-01T08:10:39Z","title":"LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00411","kind":"arxiv","version":2},"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:c7e163416be987664632cee5adaff8ccd986df790488a644d15562bdaed9086e","target":"record","created_at":"2026-07-05T09:17:36Z","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":"16880d20f3c756b659fcc0792acb6688dd97afd92c2f950351111fc76e2aa1e7","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-02-01T08:10:39Z","title_canon_sha256":"ccf02b311bf4d37d32f4122310964d68018e8af6071e2e074e1c63d02d336d54"},"schema_version":"1.0","source":{"id":"2402.00411","kind":"arxiv","version":2}},"canonical_sha256":"04b40eebd4e32f97f195259d5a0f94adcd189cde74c08fa3af4078c8120d76c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04b40eebd4e32f97f195259d5a0f94adcd189cde74c08fa3af4078c8120d76c8","first_computed_at":"2026-07-05T09:17:36.935810Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:17:36.935810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OgzMir+Qjoh/VLL4UfwnJ0ckcl23PzMZ4GIJjNRQIcKeOTcRTeMC2U6eWqlsK1PXtfEUrrWmHmuK6OUYdEvmDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:17:36.936380Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00411","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c7e163416be987664632cee5adaff8ccd986df790488a644d15562bdaed9086e","sha256:7ba64582825d2efc69c4fd5b4db4b83d7d666c68669340f362808aa759313ac0"],"state_sha256":"1a6b2e452a2a5b70331ba29ac7483348213cbf43ec5a2962025f8da417748eb1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/L6IYYaibe3LtrXr7nVk1FLeJonDllMRiBWEiVC7i03XNpF6zYItXiCN+IJ5BUWr9j68Fg7OIPxZ0hxkQG7PDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:18:12.143802Z","bundle_sha256":"32625a2ff687d8460c91bc4dae1618732d13eb20aa5c887d34b5b5fe6ba794a3"}}