{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:YJHAIRCJXC5WTBYCUTD63LZ5D6","short_pith_number":"pith:YJHAIRCJ","schema_version":"1.0","canonical_sha256":"c24e044449b8bb698702a4c7edaf3d1fb128447bdbf53689d8ee3b7becbf7ac7","source":{"kind":"arxiv","id":"2002.12900","version":1},"attestation_state":"computed","paper":{"title":"MajorityNets: BNNs Utilising Approximate Popcount for Improved Efficiency","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"David Boland, Hao Zhou, Lingli Wang, Philip H.W. Leong, Sean Fox, Seyedramin Rasoulinezhad","submitted_at":"2020-02-27T04:02:43Z","abstract_excerpt":"Binarized neural networks (BNNs) have shown exciting potential for utilising neural networks in embedded implementations where area, energy and latency constraints are paramount. With BNNs, multiply-accumulate (MAC) operations can be simplified to XnorPopcount operations, leading to massive reductions in both memory and computation resources. Furthermore, multiple efficient implementations of BNNs have been reported on field-programmable gate array (FPGA) implementations. This paper proposes a smaller, faster, more energy-efficient approximate replacement for the XnorPopcountoperation, called "},"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":"2002.12900","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-02-27T04:02:43Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"534fa1d561364e82a69e3815ffb6301e064d11ff8b493d4c5777e08c9c3978df","abstract_canon_sha256":"00c450cb5814b9020f4a82bc4d86eb1abd5f4717618c07f627d9a72b46bb9230"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:34.976237Z","signature_b64":"If4BtTM/EOFZhw6PjopoXuz6f6HIjlf2AGJdTRRPA3UZtntyETuj+kHzGQeeIL15I+O14v17uDycYZarscROAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c24e044449b8bb698702a4c7edaf3d1fb128447bdbf53689d8ee3b7becbf7ac7","last_reissued_at":"2026-07-05T00:44:34.975882Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:34.975882Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MajorityNets: BNNs Utilising Approximate Popcount for Improved Efficiency","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"David Boland, Hao Zhou, Lingli Wang, Philip H.W. Leong, Sean Fox, Seyedramin Rasoulinezhad","submitted_at":"2020-02-27T04:02:43Z","abstract_excerpt":"Binarized neural networks (BNNs) have shown exciting potential for utilising neural networks in embedded implementations where area, energy and latency constraints are paramount. With BNNs, multiply-accumulate (MAC) operations can be simplified to XnorPopcount operations, leading to massive reductions in both memory and computation resources. Furthermore, multiple efficient implementations of BNNs have been reported on field-programmable gate array (FPGA) implementations. This paper proposes a smaller, faster, more energy-efficient approximate replacement for the XnorPopcountoperation, called "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.12900","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/2002.12900/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":"2002.12900","created_at":"2026-07-05T00:44:34.975943+00:00"},{"alias_kind":"arxiv_version","alias_value":"2002.12900v1","created_at":"2026-07-05T00:44:34.975943+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.12900","created_at":"2026-07-05T00:44:34.975943+00:00"},{"alias_kind":"pith_short_12","alias_value":"YJHAIRCJXC5W","created_at":"2026-07-05T00:44:34.975943+00:00"},{"alias_kind":"pith_short_16","alias_value":"YJHAIRCJXC5WTBYC","created_at":"2026-07-05T00:44:34.975943+00:00"},{"alias_kind":"pith_short_8","alias_value":"YJHAIRCJ","created_at":"2026-07-05T00:44:34.975943+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/YJHAIRCJXC5WTBYCUTD63LZ5D6","json":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6.json","graph_json":"https://pith.science/api/pith-number/YJHAIRCJXC5WTBYCUTD63LZ5D6/graph.json","events_json":"https://pith.science/api/pith-number/YJHAIRCJXC5WTBYCUTD63LZ5D6/events.json","paper":"https://pith.science/paper/YJHAIRCJ"},"agent_actions":{"view_html":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6","download_json":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6.json","view_paper":"https://pith.science/paper/YJHAIRCJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2002.12900&json=true","fetch_graph":"https://pith.science/api/pith-number/YJHAIRCJXC5WTBYCUTD63LZ5D6/graph.json","fetch_events":"https://pith.science/api/pith-number/YJHAIRCJXC5WTBYCUTD63LZ5D6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6/action/storage_attestation","attest_author":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6/action/author_attestation","sign_citation":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6/action/citation_signature","submit_replication":"https://pith.science/pith/YJHAIRCJXC5WTBYCUTD63LZ5D6/action/replication_record"}},"created_at":"2026-07-05T00:44:34.975943+00:00","updated_at":"2026-07-05T00:44:34.975943+00:00"}