{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:CGIG2IPAXK5CD3FGOKHURISSQV","short_pith_number":"pith:CGIG2IPA","schema_version":"1.0","canonical_sha256":"11906d21e0baba21eca6728f48a252857117956021979eecf088d751816b8091","source":{"kind":"arxiv","id":"2506.09194","version":1},"attestation_state":"computed","paper":{"title":"Integration of Contrastive Predictive Coding and Spiking Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"eess.SP","authors_text":"Aykut G\\\"orkem Gelen, Emirhan Bilgi\\c{c}, Nam{\\i}k Berk Yalab{\\i}k, Neslihan Serap \\c{S}eng\\\"or, Rahmi Elibol, Yavuz Selim \\.I\\c{s}ler","submitted_at":"2025-06-10T19:23:08Z","abstract_excerpt":"This study examines the integration of Contrastive Predictive Coding (CPC) with Spiking Neural Networks (SNN). While CPC learns the predictive structure of data to generate meaningful representations, SNN mimics the computational processes of biological neural systems over time. In this study, the goal is to develop a predictive coding model with greater biological plausibility by processing inputs and outputs in a spike-based system. The proposed model was tested on the MNIST dataset and achieved a high classification rate in distinguishing positive sequential samples from non-sequential nega"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.09194","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-10T19:23:08Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"315f7bfd8de5853460a44351960a582c5a594faa37732c6f8f23c39e3208c098","abstract_canon_sha256":"f7520ef1561f92d0326e203e3be8adf27dac5039e4f72567454e3be772bc4ef1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:19:33.026246Z","signature_b64":"hNC4HQPbp1+nOcuL+o+EcnlOJfU3fWE1Mr+D6diEb9Imvl1RY1AJrqu4gEYRQDvjfiqdSGPPOYpkyY2qn4CcBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"11906d21e0baba21eca6728f48a252857117956021979eecf088d751816b8091","last_reissued_at":"2026-07-05T11:19:33.025815Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:19:33.025815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Integration of Contrastive Predictive Coding and Spiking Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"eess.SP","authors_text":"Aykut G\\\"orkem Gelen, Emirhan Bilgi\\c{c}, Nam{\\i}k Berk Yalab{\\i}k, Neslihan Serap \\c{S}eng\\\"or, Rahmi Elibol, Yavuz Selim \\.I\\c{s}ler","submitted_at":"2025-06-10T19:23:08Z","abstract_excerpt":"This study examines the integration of Contrastive Predictive Coding (CPC) with Spiking Neural Networks (SNN). While CPC learns the predictive structure of data to generate meaningful representations, SNN mimics the computational processes of biological neural systems over time. In this study, the goal is to develop a predictive coding model with greater biological plausibility by processing inputs and outputs in a spike-based system. The proposed model was tested on the MNIST dataset and achieved a high classification rate in distinguishing positive sequential samples from non-sequential nega"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.09194","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/2506.09194/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.09194","created_at":"2026-07-05T11:19:33.025870+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.09194v1","created_at":"2026-07-05T11:19:33.025870+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.09194","created_at":"2026-07-05T11:19:33.025870+00:00"},{"alias_kind":"pith_short_12","alias_value":"CGIG2IPAXK5C","created_at":"2026-07-05T11:19:33.025870+00:00"},{"alias_kind":"pith_short_16","alias_value":"CGIG2IPAXK5CD3FG","created_at":"2026-07-05T11:19:33.025870+00:00"},{"alias_kind":"pith_short_8","alias_value":"CGIG2IPA","created_at":"2026-07-05T11:19:33.025870+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV","json":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV.json","graph_json":"https://pith.science/api/pith-number/CGIG2IPAXK5CD3FGOKHURISSQV/graph.json","events_json":"https://pith.science/api/pith-number/CGIG2IPAXK5CD3FGOKHURISSQV/events.json","paper":"https://pith.science/paper/CGIG2IPA"},"agent_actions":{"view_html":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV","download_json":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV.json","view_paper":"https://pith.science/paper/CGIG2IPA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.09194&json=true","fetch_graph":"https://pith.science/api/pith-number/CGIG2IPAXK5CD3FGOKHURISSQV/graph.json","fetch_events":"https://pith.science/api/pith-number/CGIG2IPAXK5CD3FGOKHURISSQV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV/action/storage_attestation","attest_author":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV/action/author_attestation","sign_citation":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV/action/citation_signature","submit_replication":"https://pith.science/pith/CGIG2IPAXK5CD3FGOKHURISSQV/action/replication_record"}},"created_at":"2026-07-05T11:19:33.025870+00:00","updated_at":"2026-07-05T11:19:33.025870+00:00"}