{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:5SC62VD3ESULJIXH4ZUOQZZOAA","short_pith_number":"pith:5SC62VD3","schema_version":"1.0","canonical_sha256":"ec85ed547b24a8b4a2e7e668e8672e0023b382d857a956bdf162390fbffc11f9","source":{"kind":"arxiv","id":"1708.08687","version":1},"attestation_state":"computed","paper":{"title":"Performance Guaranteed Network Acceleration via High-Order Residual Quantization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingbing Ni, Wen Gao, Wenjun Zhang, Xiaokang Yang, Zefan Li","submitted_at":"2017-08-29T10:42:29Z","abstract_excerpt":"Input binarization has shown to be an effective way for network acceleration. However, previous binarization scheme could be regarded as simple pixel-wise thresholding operations (i.e., order-one approximation) and suffers a big accuracy loss. In this paper, we propose a highorder binarization scheme, which achieves more accurate approximation while still possesses the advantage of binary operation. In particular, the proposed scheme recursively performs residual quantization and yields a series of binary input images with decreasing magnitude scales. Accordingly, we propose high-order binary "},"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":"1708.08687","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-29T10:42:29Z","cross_cats_sorted":[],"title_canon_sha256":"9b1db1af047abb049a984bebb5332e0dec15280fec1d2d54bdac46c7b4110315","abstract_canon_sha256":"d45aaeb07664ffaa85c207f8272a3b011d9f793746199cf5e802e965502812ff"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:26.014301Z","signature_b64":"s6qMHTO/jUKl5VUhW5eZIVMG+Vq5JnBf5+TUA6tWrO0PzA1cO5x0FWEj/xdQr6bhJUcZHmoxop1uCX8DnQMNCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec85ed547b24a8b4a2e7e668e8672e0023b382d857a956bdf162390fbffc11f9","last_reissued_at":"2026-05-18T00:36:26.013688Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:26.013688Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Performance Guaranteed Network Acceleration via High-Order Residual Quantization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingbing Ni, Wen Gao, Wenjun Zhang, Xiaokang Yang, Zefan Li","submitted_at":"2017-08-29T10:42:29Z","abstract_excerpt":"Input binarization has shown to be an effective way for network acceleration. However, previous binarization scheme could be regarded as simple pixel-wise thresholding operations (i.e., order-one approximation) and suffers a big accuracy loss. In this paper, we propose a highorder binarization scheme, which achieves more accurate approximation while still possesses the advantage of binary operation. In particular, the proposed scheme recursively performs residual quantization and yields a series of binary input images with decreasing magnitude scales. Accordingly, we propose high-order binary "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.08687","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":""},"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":"1708.08687","created_at":"2026-05-18T00:36:26.013788+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.08687v1","created_at":"2026-05-18T00:36:26.013788+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.08687","created_at":"2026-05-18T00:36:26.013788+00:00"},{"alias_kind":"pith_short_12","alias_value":"5SC62VD3ESUL","created_at":"2026-05-18T12:31:00.734936+00:00"},{"alias_kind":"pith_short_16","alias_value":"5SC62VD3ESULJIXH","created_at":"2026-05-18T12:31:00.734936+00:00"},{"alias_kind":"pith_short_8","alias_value":"5SC62VD3","created_at":"2026-05-18T12:31:00.734936+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/5SC62VD3ESULJIXH4ZUOQZZOAA","json":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA.json","graph_json":"https://pith.science/api/pith-number/5SC62VD3ESULJIXH4ZUOQZZOAA/graph.json","events_json":"https://pith.science/api/pith-number/5SC62VD3ESULJIXH4ZUOQZZOAA/events.json","paper":"https://pith.science/paper/5SC62VD3"},"agent_actions":{"view_html":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA","download_json":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA.json","view_paper":"https://pith.science/paper/5SC62VD3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.08687&json=true","fetch_graph":"https://pith.science/api/pith-number/5SC62VD3ESULJIXH4ZUOQZZOAA/graph.json","fetch_events":"https://pith.science/api/pith-number/5SC62VD3ESULJIXH4ZUOQZZOAA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA/action/storage_attestation","attest_author":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA/action/author_attestation","sign_citation":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA/action/citation_signature","submit_replication":"https://pith.science/pith/5SC62VD3ESULJIXH4ZUOQZZOAA/action/replication_record"}},"created_at":"2026-05-18T00:36:26.013788+00:00","updated_at":"2026-05-18T00:36:26.013788+00:00"}