{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:LNLRSLFXMGLHQMI6TNG46FXCRD","short_pith_number":"pith:LNLRSLFX","canonical_record":{"source":{"id":"1707.07103","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T04:33:02Z","cross_cats_sorted":[],"title_canon_sha256":"dad79ce2cc4a887c1343dc39982a3319e80ac9763c4d9b387add2c53264c8614","abstract_canon_sha256":"028f7a20ccce803918af99db94088cf529e55e4a627bd2a99d127a0682f3daca"},"schema_version":"1.0"},"canonical_sha256":"5b57192cb7619678311e9b4dcf16e288dc8ae68c8f226fa7987310003585a5c5","source":{"kind":"arxiv","id":"1707.07103","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.07103","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"arxiv_version","alias_value":"1707.07103v1","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.07103","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"pith_short_12","alias_value":"LNLRSLFXMGLH","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LNLRSLFXMGLHQMI6","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LNLRSLFX","created_at":"2026-05-18T12:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:LNLRSLFXMGLHQMI6TNG46FXCRD","target":"record","payload":{"canonical_record":{"source":{"id":"1707.07103","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T04:33:02Z","cross_cats_sorted":[],"title_canon_sha256":"dad79ce2cc4a887c1343dc39982a3319e80ac9763c4d9b387add2c53264c8614","abstract_canon_sha256":"028f7a20ccce803918af99db94088cf529e55e4a627bd2a99d127a0682f3daca"},"schema_version":"1.0"},"canonical_sha256":"5b57192cb7619678311e9b4dcf16e288dc8ae68c8f226fa7987310003585a5c5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:45.341891Z","signature_b64":"gy9Zn6X/k9ZBRRrzUm9Yap+qoPeEiszyfJOlgr41h+U4ThGwZRTvBEnHI7fQvVx2/QwmC4bvjCkeZ0zIiZByBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b57192cb7619678311e9b4dcf16e288dc8ae68c8f226fa7987310003585a5c5","last_reissued_at":"2026-05-18T00:39:45.341155Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:45.341155Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.07103","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":"2026-05-18T00:39:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XZysrP1fH+taw3RudtTSsxizjId+QpU5Imff/VkQ0pNZ6xm5X3GRN94TWJEess7NNx9RNlVT3xIDEqfddVevAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T07:06:47.516075Z"},"content_sha256":"82de1ba7b73b0a5c47b9c20de5ae4ff9080521ce42430ffe8d44fbf9ac04ead0","schema_version":"1.0","event_id":"sha256:82de1ba7b73b0a5c47b9c20de5ae4ff9080521ce42430ffe8d44fbf9ac04ead0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:LNLRSLFXMGLHQMI6TNG46FXCRD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PatchShuffle Regularization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guoliang Kang, Liang Zheng, Xuanyi Dong, Yi Yang","submitted_at":"2017-07-22T04:33:02Z","abstract_excerpt":"This paper focuses on regularizing the training of the convolutional neural network (CNN). We propose a new regularization approach named ``PatchShuffle`` that can be adopted in any classification-oriented CNN models. It is easy to implement: in each mini-batch, images or feature maps are randomly chosen to undergo a transformation such that pixels within each local patch are shuffled. Through generating images and feature maps with interior orderless patches, PatchShuffle creates rich local variations, reduces the risk of network overfitting, and can be viewed as a beneficial supplement to va"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.07103","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":"2026-05-18T00:39:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+jzQ2raZ5IaCHeE+xlr6/+29XGixRNWOh7hCPt3EgVu+QvJ5ZDk5IEb516UDNUOdNTZmpuLcQfgRoMteuNM9Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T07:06:47.516438Z"},"content_sha256":"a399411b8bd0dce8dca311d49daafaf93ffa8d14a7922306ef4d6d6a5d932c0e","schema_version":"1.0","event_id":"sha256:a399411b8bd0dce8dca311d49daafaf93ffa8d14a7922306ef4d6d6a5d932c0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/bundle.json","state_url":"https://pith.science/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/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":"2026-05-23T07:06:47Z","links":{"resolver":"https://pith.science/pith/LNLRSLFXMGLHQMI6TNG46FXCRD","bundle":"https://pith.science/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/bundle.json","state":"https://pith.science/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LNLRSLFXMGLHQMI6TNG46FXCRD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LNLRSLFXMGLHQMI6TNG46FXCRD","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":"028f7a20ccce803918af99db94088cf529e55e4a627bd2a99d127a0682f3daca","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T04:33:02Z","title_canon_sha256":"dad79ce2cc4a887c1343dc39982a3319e80ac9763c4d9b387add2c53264c8614"},"schema_version":"1.0","source":{"id":"1707.07103","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.07103","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"arxiv_version","alias_value":"1707.07103v1","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.07103","created_at":"2026-05-18T00:39:45Z"},{"alias_kind":"pith_short_12","alias_value":"LNLRSLFXMGLH","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LNLRSLFXMGLHQMI6","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LNLRSLFX","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:a399411b8bd0dce8dca311d49daafaf93ffa8d14a7922306ef4d6d6a5d932c0e","target":"graph","created_at":"2026-05-18T00:39:45Z","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":"This paper focuses on regularizing the training of the convolutional neural network (CNN). We propose a new regularization approach named ``PatchShuffle`` that can be adopted in any classification-oriented CNN models. It is easy to implement: in each mini-batch, images or feature maps are randomly chosen to undergo a transformation such that pixels within each local patch are shuffled. Through generating images and feature maps with interior orderless patches, PatchShuffle creates rich local variations, reduces the risk of network overfitting, and can be viewed as a beneficial supplement to va","authors_text":"Guoliang Kang, Liang Zheng, Xuanyi Dong, Yi Yang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T04:33:02Z","title":"PatchShuffle Regularization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.07103","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":"sha256:82de1ba7b73b0a5c47b9c20de5ae4ff9080521ce42430ffe8d44fbf9ac04ead0","target":"record","created_at":"2026-05-18T00:39:45Z","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":"028f7a20ccce803918af99db94088cf529e55e4a627bd2a99d127a0682f3daca","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-22T04:33:02Z","title_canon_sha256":"dad79ce2cc4a887c1343dc39982a3319e80ac9763c4d9b387add2c53264c8614"},"schema_version":"1.0","source":{"id":"1707.07103","kind":"arxiv","version":1}},"canonical_sha256":"5b57192cb7619678311e9b4dcf16e288dc8ae68c8f226fa7987310003585a5c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b57192cb7619678311e9b4dcf16e288dc8ae68c8f226fa7987310003585a5c5","first_computed_at":"2026-05-18T00:39:45.341155Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:45.341155Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gy9Zn6X/k9ZBRRrzUm9Yap+qoPeEiszyfJOlgr41h+U4ThGwZRTvBEnHI7fQvVx2/QwmC4bvjCkeZ0zIiZByBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:45.341891Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.07103","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82de1ba7b73b0a5c47b9c20de5ae4ff9080521ce42430ffe8d44fbf9ac04ead0","sha256:a399411b8bd0dce8dca311d49daafaf93ffa8d14a7922306ef4d6d6a5d932c0e"],"state_sha256":"7eb0f45377383001c7174127e1d28651f54bfa8bc369d8442f1892aff77c376f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gTamlEVrJAsAYQJqQTL+ROTMcAQqhOZXBo1Ylfao8MFS03HVgvwUft0dkqIKs6jsg54Oc5pHdP2GX+TfV4loBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T07:06:47.519229Z","bundle_sha256":"2230cebc1d7dcda1eb880da1454c94c68f156c652e8046bd4593e8b2a2aefa6f"}}