{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:W655O2HTG3L6V6LSCSOP72CZZ7","short_pith_number":"pith:W655O2HT","canonical_record":{"source":{"id":"1903.05285","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-13T01:44:39Z","cross_cats_sorted":[],"title_canon_sha256":"ded3d1a6db1f8d9db367c89bf1da527353015c0b0160c4d25be506ed802a79eb","abstract_canon_sha256":"51598a8b3fca961ba5257fcfd27bd099585cea288b5c43ab142fbff2c4819d53"},"schema_version":"1.0"},"canonical_sha256":"b7bbd768f336d7eaf972149cffe859cfd2eb802b71021de3d7a34d3a38e07f9b","source":{"kind":"arxiv","id":"1903.05285","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05285","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05285v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05285","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"W655O2HTG3L6","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W655O2HTG3L6V6LS","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W655O2HT","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:W655O2HTG3L6V6LSCSOP72CZZ7","target":"record","payload":{"canonical_record":{"source":{"id":"1903.05285","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-13T01:44:39Z","cross_cats_sorted":[],"title_canon_sha256":"ded3d1a6db1f8d9db367c89bf1da527353015c0b0160c4d25be506ed802a79eb","abstract_canon_sha256":"51598a8b3fca961ba5257fcfd27bd099585cea288b5c43ab142fbff2c4819d53"},"schema_version":"1.0"},"canonical_sha256":"b7bbd768f336d7eaf972149cffe859cfd2eb802b71021de3d7a34d3a38e07f9b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:24.781593Z","signature_b64":"0M9dGkFQ8H14VyNjbHEBJQf+ZmXb3ILXqQvXM0FdLup4R3i9RqCZuMdaqWGYK72bqnJsNyQ391p1zu1+qpWxCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7bbd768f336d7eaf972149cffe859cfd2eb802b71021de3d7a34d3a38e07f9b","last_reissued_at":"2026-05-17T23:51:24.780925Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:24.780925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.05285","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L5Qx9KhP8Elb6Bbt6asAaoxKQsiryPkBFJPbiJtDGR2Kb/PMHHecNRx4SkLHv2p8uihLTBzyyWiu4Vg4RggjCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:27:49.071311Z"},"content_sha256":"e48b548ccb2f47b3554ab95e4fe4ef9098468193fed925d89fa013ada547d1f3","schema_version":"1.0","event_id":"sha256:e48b548ccb2f47b3554ab95e4fe4ef9098468193fed925d89fa013ada547d1f3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:W655O2HTG3L6V6LSCSOP72CZZ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Di Xie, Shiliang Pu, Weijie Chen, Yuan Zhang","submitted_at":"2019-03-13T01:44:39Z","abstract_excerpt":"Shift operation is an efficient alternative over depthwise separable convolution. However, it is still bottlenecked by its implementation manner, namely memory movement. To put this direction forward, a new and novel basic component named Sparse Shift Layer (SSL) is introduced in this paper to construct efficient convolutional neural networks. In this family of architectures, the basic block is only composed by 1x1 convolutional layers with only a few shift operations applied to the intermediate feature maps. To make this idea feasible, we introduce shift operation penalty during optimization "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05285","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MFYX9+no1hL3BrbWCdFivcacOWA6ASDRHDtD9At9csaM/bo6qaj75adHK5AASEgyIoskhGScZaDj8EocPvphCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:27:49.072058Z"},"content_sha256":"2768759f0943c651f338b2cc95a3ab3324b5698bed395769eae4ed6bebe8e31d","schema_version":"1.0","event_id":"sha256:2768759f0943c651f338b2cc95a3ab3324b5698bed395769eae4ed6bebe8e31d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W655O2HTG3L6V6LSCSOP72CZZ7/bundle.json","state_url":"https://pith.science/pith/W655O2HTG3L6V6LSCSOP72CZZ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W655O2HTG3L6V6LSCSOP72CZZ7/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":"2026-05-26T21:27:49Z","links":{"resolver":"https://pith.science/pith/W655O2HTG3L6V6LSCSOP72CZZ7","bundle":"https://pith.science/pith/W655O2HTG3L6V6LSCSOP72CZZ7/bundle.json","state":"https://pith.science/pith/W655O2HTG3L6V6LSCSOP72CZZ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W655O2HTG3L6V6LSCSOP72CZZ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:W655O2HTG3L6V6LSCSOP72CZZ7","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":"51598a8b3fca961ba5257fcfd27bd099585cea288b5c43ab142fbff2c4819d53","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-13T01:44:39Z","title_canon_sha256":"ded3d1a6db1f8d9db367c89bf1da527353015c0b0160c4d25be506ed802a79eb"},"schema_version":"1.0","source":{"id":"1903.05285","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05285","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05285v1","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05285","created_at":"2026-05-17T23:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"W655O2HTG3L6","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"W655O2HTG3L6V6LS","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"W655O2HT","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:2768759f0943c651f338b2cc95a3ab3324b5698bed395769eae4ed6bebe8e31d","target":"graph","created_at":"2026-05-17T23:51:24Z","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"},"paper":{"abstract_excerpt":"Shift operation is an efficient alternative over depthwise separable convolution. However, it is still bottlenecked by its implementation manner, namely memory movement. To put this direction forward, a new and novel basic component named Sparse Shift Layer (SSL) is introduced in this paper to construct efficient convolutional neural networks. In this family of architectures, the basic block is only composed by 1x1 convolutional layers with only a few shift operations applied to the intermediate feature maps. To make this idea feasible, we introduce shift operation penalty during optimization ","authors_text":"Di Xie, Shiliang Pu, Weijie Chen, Yuan Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-13T01:44:39Z","title":"All You Need is a Few Shifts: Designing Efficient Convolutional Neural Networks for Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05285","kind":"arxiv","version":1},"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:e48b548ccb2f47b3554ab95e4fe4ef9098468193fed925d89fa013ada547d1f3","target":"record","created_at":"2026-05-17T23:51:24Z","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":"51598a8b3fca961ba5257fcfd27bd099585cea288b5c43ab142fbff2c4819d53","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-13T01:44:39Z","title_canon_sha256":"ded3d1a6db1f8d9db367c89bf1da527353015c0b0160c4d25be506ed802a79eb"},"schema_version":"1.0","source":{"id":"1903.05285","kind":"arxiv","version":1}},"canonical_sha256":"b7bbd768f336d7eaf972149cffe859cfd2eb802b71021de3d7a34d3a38e07f9b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7bbd768f336d7eaf972149cffe859cfd2eb802b71021de3d7a34d3a38e07f9b","first_computed_at":"2026-05-17T23:51:24.780925Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:24.780925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0M9dGkFQ8H14VyNjbHEBJQf+ZmXb3ILXqQvXM0FdLup4R3i9RqCZuMdaqWGYK72bqnJsNyQ391p1zu1+qpWxCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:24.781593Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.05285","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e48b548ccb2f47b3554ab95e4fe4ef9098468193fed925d89fa013ada547d1f3","sha256:2768759f0943c651f338b2cc95a3ab3324b5698bed395769eae4ed6bebe8e31d"],"state_sha256":"ee735a789c0e6cbb180e8101daff59a8c7f345affbfb2c02f344761a4d7853c1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nLTCFN+BTuzpTT3WS8TwvRd8iv/dW5qYPyV+rcVSFMBCMl0EpwdZJlAMSn02QsN5af0hAmjL3Cj+i8gigp4lCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T21:27:49.076640Z","bundle_sha256":"0759107fe1b67562bec1400fb4cf54feacb258051ac02b2793e2ff6094a12bb5"}}