{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:WBDKUYXU3QSANTZZPITGKXFRZK","short_pith_number":"pith:WBDKUYXU","canonical_record":{"source":{"id":"1512.05830","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-18T00:13:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"98aac8ad43bc7bcc85b8c4668cdfd00addf0b513808d49e11dfa630cde56adbf","abstract_canon_sha256":"fc0ba28ff74f1cf48ac9d8f26fd18463592779c00180d37377592705b70561e6"},"schema_version":"1.0"},"canonical_sha256":"b046aa62f4dc2406cf397a26655cb1cab01218365e2be83b986f6b518e0b38b7","source":{"kind":"arxiv","id":"1512.05830","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.05830","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"arxiv_version","alias_value":"1512.05830v2","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.05830","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"pith_short_12","alias_value":"WBDKUYXU3QSA","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"WBDKUYXU3QSANTZZ","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"WBDKUYXU","created_at":"2026-05-18T12:29:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:WBDKUYXU3QSANTZZPITGKXFRZK","target":"record","payload":{"canonical_record":{"source":{"id":"1512.05830","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-18T00:13:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"98aac8ad43bc7bcc85b8c4668cdfd00addf0b513808d49e11dfa630cde56adbf","abstract_canon_sha256":"fc0ba28ff74f1cf48ac9d8f26fd18463592779c00180d37377592705b70561e6"},"schema_version":"1.0"},"canonical_sha256":"b046aa62f4dc2406cf397a26655cb1cab01218365e2be83b986f6b518e0b38b7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:50.422489Z","signature_b64":"r65sVbXnnj8FP26IFIxu6DWlWCAL4pvru8eJr4ANX75xBOdbzI+VLokToqJMpqHwx65ryzkuXbIFN0uy2/HaAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b046aa62f4dc2406cf397a26655cb1cab01218365e2be83b986f6b518e0b38b7","last_reissued_at":"2026-05-18T01:17:50.421722Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:50.421722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.05830","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:17:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mikhfb8KeLM/eAAPkbje2ZmhfLXjLI9kEaqpkAkRYF4bOll0Xv57LPOxydLkISbyuN/bqb+5eWQeyQd+86X9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T10:40:18.048162Z"},"content_sha256":"9e6c43b6ce61ef1ca3159ea5a0df8c30ec494d85154852281e003aaf50034045","schema_version":"1.0","event_id":"sha256:9e6c43b6ce61ef1ca3159ea5a0df8c30ec494d85154852281e003aaf50034045"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:WBDKUYXU3QSANTZZPITGKXFRZK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Li Shen, Qingming Huang, Zhouchen Lin","submitted_at":"2015-12-18T00:13:10Z","abstract_excerpt":"Learning deeper convolutional neural networks becomes a tendency in recent years. However, many empirical evidences suggest that performance improvement cannot be gained by simply stacking more layers. In this paper, we consider the issue from an information theoretical perspective, and propose a novel method Relay Backpropagation, that encourages the propagation of effective information through the network in training stage. By virtue of the method, we achieved the first place in ILSVRC 2015 Scene Classification Challenge. Extensive experiments on two challenging large scale datasets demonstr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.05830","kind":"arxiv","version":2},"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":"2026-05-18T01:17:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3HAB2dVlJ3a4Jk9TcfLMKYiV8AhHulmjn00yrbVIOKuiS9NSMy+iOBx6dDh8gkcD+N58tunDf3bhIDUe5mLYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T10:40:18.048524Z"},"content_sha256":"18cfc88244830d83ed22a00f546e073606c628b0d0e993f178fa846c3164a0d1","schema_version":"1.0","event_id":"sha256:18cfc88244830d83ed22a00f546e073606c628b0d0e993f178fa846c3164a0d1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WBDKUYXU3QSANTZZPITGKXFRZK/bundle.json","state_url":"https://pith.science/pith/WBDKUYXU3QSANTZZPITGKXFRZK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WBDKUYXU3QSANTZZPITGKXFRZK/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":"2026-06-04T10:40:18Z","links":{"resolver":"https://pith.science/pith/WBDKUYXU3QSANTZZPITGKXFRZK","bundle":"https://pith.science/pith/WBDKUYXU3QSANTZZPITGKXFRZK/bundle.json","state":"https://pith.science/pith/WBDKUYXU3QSANTZZPITGKXFRZK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WBDKUYXU3QSANTZZPITGKXFRZK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:WBDKUYXU3QSANTZZPITGKXFRZK","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":"fc0ba28ff74f1cf48ac9d8f26fd18463592779c00180d37377592705b70561e6","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-18T00:13:10Z","title_canon_sha256":"98aac8ad43bc7bcc85b8c4668cdfd00addf0b513808d49e11dfa630cde56adbf"},"schema_version":"1.0","source":{"id":"1512.05830","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.05830","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"arxiv_version","alias_value":"1512.05830v2","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.05830","created_at":"2026-05-18T01:17:50Z"},{"alias_kind":"pith_short_12","alias_value":"WBDKUYXU3QSA","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"WBDKUYXU3QSANTZZ","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"WBDKUYXU","created_at":"2026-05-18T12:29:47Z"}],"graph_snapshots":[{"event_id":"sha256:18cfc88244830d83ed22a00f546e073606c628b0d0e993f178fa846c3164a0d1","target":"graph","created_at":"2026-05-18T01:17:50Z","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":"Learning deeper convolutional neural networks becomes a tendency in recent years. However, many empirical evidences suggest that performance improvement cannot be gained by simply stacking more layers. In this paper, we consider the issue from an information theoretical perspective, and propose a novel method Relay Backpropagation, that encourages the propagation of effective information through the network in training stage. By virtue of the method, we achieved the first place in ILSVRC 2015 Scene Classification Challenge. Extensive experiments on two challenging large scale datasets demonstr","authors_text":"Li Shen, Qingming Huang, Zhouchen Lin","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-18T00:13:10Z","title":"Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.05830","kind":"arxiv","version":2},"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":"sha256:9e6c43b6ce61ef1ca3159ea5a0df8c30ec494d85154852281e003aaf50034045","target":"record","created_at":"2026-05-18T01:17:50Z","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":"fc0ba28ff74f1cf48ac9d8f26fd18463592779c00180d37377592705b70561e6","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-18T00:13:10Z","title_canon_sha256":"98aac8ad43bc7bcc85b8c4668cdfd00addf0b513808d49e11dfa630cde56adbf"},"schema_version":"1.0","source":{"id":"1512.05830","kind":"arxiv","version":2}},"canonical_sha256":"b046aa62f4dc2406cf397a26655cb1cab01218365e2be83b986f6b518e0b38b7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b046aa62f4dc2406cf397a26655cb1cab01218365e2be83b986f6b518e0b38b7","first_computed_at":"2026-05-18T01:17:50.421722Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:17:50.421722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r65sVbXnnj8FP26IFIxu6DWlWCAL4pvru8eJr4ANX75xBOdbzI+VLokToqJMpqHwx65ryzkuXbIFN0uy2/HaAg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:17:50.422489Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.05830","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9e6c43b6ce61ef1ca3159ea5a0df8c30ec494d85154852281e003aaf50034045","sha256:18cfc88244830d83ed22a00f546e073606c628b0d0e993f178fa846c3164a0d1"],"state_sha256":"1abad680d137e155abb840e7e7576fd9748772b03c81e2ccd887bd07d79d6c7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O/dPU+p3yFQVlOIpVr0bpQhDzn4snDTAcLGHe/S1XTnORG+vtSD7UpeOQEGuz5R5tJoF/gLGFGZmOqNYUR08Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T10:40:18.050492Z","bundle_sha256":"812f22a16460d2ff8ea89fb596d165a9e06dc093c9c17788167d0e16e830852b"}}