{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:2767BDERRZPFDJEX74YCNBAA67","short_pith_number":"pith:2767BDER","schema_version":"1.0","canonical_sha256":"d7fdf08c918e5e51a497ff30268400f7c05ff3ff90e440c1e2f2a4fc10b604b6","source":{"kind":"arxiv","id":"2305.02885","version":1},"attestation_state":"computed","paper":{"title":"Input Layer Binarization with Bit-Plane Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Davide Maltoni, Lorenzo Vorabbi, Stefano Santi","submitted_at":"2023-05-04T14:49:07Z","abstract_excerpt":"Binary Neural Networks (BNNs) use 1-bit weights and activations to efficiently execute deep convolutional neural networks on edge devices. Nevertheless, the binarization of the first layer is conventionally excluded, as it leads to a large accuracy loss. The few works addressing the first layer binarization, typically increase the number of input channels to enhance data representation; such data expansion raises the amount of operations needed and it is feasible only on systems with enough computational resources. In this work, we present a new method to binarize the first layer using directl"},"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":"2305.02885","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-04T14:49:07Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"15f99e716258238757ef5ec309a8a72b234698a259806c31e9bcb53dfda74297","abstract_canon_sha256":"94452a329793e7dff748a19dfbe690f7404437e892be9e6f4a44aae8115d9610"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:07:06.044509Z","signature_b64":"cn5DfEjk7VRKl9Z56b6gKuqPgg81sXt8qf62BiwKljI0AZ10zkDmAAJ6rIeXYu7YYxWkTnxApWZNwtNpu7kvAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7fdf08c918e5e51a497ff30268400f7c05ff3ff90e440c1e2f2a4fc10b604b6","last_reissued_at":"2026-07-05T06:07:06.044102Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:07:06.044102Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Input Layer Binarization with Bit-Plane Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Davide Maltoni, Lorenzo Vorabbi, Stefano Santi","submitted_at":"2023-05-04T14:49:07Z","abstract_excerpt":"Binary Neural Networks (BNNs) use 1-bit weights and activations to efficiently execute deep convolutional neural networks on edge devices. Nevertheless, the binarization of the first layer is conventionally excluded, as it leads to a large accuracy loss. The few works addressing the first layer binarization, typically increase the number of input channels to enhance data representation; such data expansion raises the amount of operations needed and it is feasible only on systems with enough computational resources. In this work, we present a new method to binarize the first layer using directl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.02885","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/2305.02885/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":"2305.02885","created_at":"2026-07-05T06:07:06.044159+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.02885v1","created_at":"2026-07-05T06:07:06.044159+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.02885","created_at":"2026-07-05T06:07:06.044159+00:00"},{"alias_kind":"pith_short_12","alias_value":"2767BDERRZPF","created_at":"2026-07-05T06:07:06.044159+00:00"},{"alias_kind":"pith_short_16","alias_value":"2767BDERRZPFDJEX","created_at":"2026-07-05T06:07:06.044159+00:00"},{"alias_kind":"pith_short_8","alias_value":"2767BDER","created_at":"2026-07-05T06:07:06.044159+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/2767BDERRZPFDJEX74YCNBAA67","json":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67.json","graph_json":"https://pith.science/api/pith-number/2767BDERRZPFDJEX74YCNBAA67/graph.json","events_json":"https://pith.science/api/pith-number/2767BDERRZPFDJEX74YCNBAA67/events.json","paper":"https://pith.science/paper/2767BDER"},"agent_actions":{"view_html":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67","download_json":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67.json","view_paper":"https://pith.science/paper/2767BDER","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.02885&json=true","fetch_graph":"https://pith.science/api/pith-number/2767BDERRZPFDJEX74YCNBAA67/graph.json","fetch_events":"https://pith.science/api/pith-number/2767BDERRZPFDJEX74YCNBAA67/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67/action/storage_attestation","attest_author":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67/action/author_attestation","sign_citation":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67/action/citation_signature","submit_replication":"https://pith.science/pith/2767BDERRZPFDJEX74YCNBAA67/action/replication_record"}},"created_at":"2026-07-05T06:07:06.044159+00:00","updated_at":"2026-07-05T06:07:06.044159+00:00"}