{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:XQRAKQYU4DHJ45EMI62NQPPZW6","short_pith_number":"pith:XQRAKQYU","canonical_record":{"source":{"id":"1804.08233","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-04-23T03:03:13Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6c2590e61ce6f2abeb24a53cc18282d6c69c2acefecab349fb40660905e99235","abstract_canon_sha256":"57859a7352022cb88648b399bfb9ea58bfe7e30bc7293800e47706ee8e0b0fb7"},"schema_version":"1.0"},"canonical_sha256":"bc22054314e0ce9e748c47b4d83df9b7b967253056a2401fb4d30c50b3140031","source":{"kind":"arxiv","id":"1804.08233","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.08233","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"arxiv_version","alias_value":"1804.08233v3","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08233","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"pith_short_12","alias_value":"XQRAKQYU4DHJ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"XQRAKQYU4DHJ45EM","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"XQRAKQYU","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:XQRAKQYU4DHJ45EMI62NQPPZW6","target":"record","payload":{"canonical_record":{"source":{"id":"1804.08233","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-04-23T03:03:13Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6c2590e61ce6f2abeb24a53cc18282d6c69c2acefecab349fb40660905e99235","abstract_canon_sha256":"57859a7352022cb88648b399bfb9ea58bfe7e30bc7293800e47706ee8e0b0fb7"},"schema_version":"1.0"},"canonical_sha256":"bc22054314e0ce9e748c47b4d83df9b7b967253056a2401fb4d30c50b3140031","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:53.451828Z","signature_b64":"p2k4G85T3zLlEvoY7mKA7LgZRFMANZTB2YEn/tIYIS+gRRcjy66LJKZHoiOughAuz/lZCPYZP0FO+GGw2qRHBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc22054314e0ce9e748c47b4d83df9b7b967253056a2401fb4d30c50b3140031","last_reissued_at":"2026-05-17T23:56:53.451264Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:53.451264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1804.08233","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:56:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qFv98rh1pyq6sC6ahG+pt9yy7pyo9mPrBY9+zUk7pcWjm0K8oL4Hg2D9Ima47ZcFABFPjuWSvqu8i1/EbHyxCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T16:59:16.766972Z"},"content_sha256":"a0283b2e8086623dd1bb4bea0b04cc7615573187585c050bf8dbec1608f70c7a","schema_version":"1.0","event_id":"sha256:a0283b2e8086623dd1bb4bea0b04cc7615573187585c050bf8dbec1608f70c7a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:XQRAKQYU4DHJ45EMI62NQPPZW6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"N-fold Superposition: Improving Neural Networks by Reducing the Noise in Feature Maps","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Chao Gao, Qiang Qu, Yang Liu","submitted_at":"2018-04-23T03:03:13Z","abstract_excerpt":"Considering the use of Fully Connected (FC) layer limits the performance of Convolutional Neural Networks (CNNs), this paper develops a method to improve the coupling between the convolution layer and the FC layer by reducing the noise in Feature Maps (FMs). Our approach is divided into three steps. Firstly, we separate all the FMs into n blocks equally. Then, the weighted summation of FMs at the same position in all blocks constitutes a new block of FMs. Finally, we replicate this new block into n copies and concatenate them as the input to the FC layer. This sharing of FMs could reduce the n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08233","kind":"arxiv","version":3},"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":"2026-05-17T23:56:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zuudZO5NtGF/hwMKaUM9VaKB6eM0otonOddG7Kulxvzv/0kpjQw/ySreOeTjOXCXnhfE3MOt8HFy5aWlcmcEBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T16:59:16.767326Z"},"content_sha256":"6ffc1ace43d297547798dafb5d37a5a91ff49c5895c152ab6fbf4c2d620fcde6","schema_version":"1.0","event_id":"sha256:6ffc1ace43d297547798dafb5d37a5a91ff49c5895c152ab6fbf4c2d620fcde6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/bundle.json","state_url":"https://pith.science/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/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":"2026-06-03T16:59:16Z","links":{"resolver":"https://pith.science/pith/XQRAKQYU4DHJ45EMI62NQPPZW6","bundle":"https://pith.science/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/bundle.json","state":"https://pith.science/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XQRAKQYU4DHJ45EMI62NQPPZW6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:XQRAKQYU4DHJ45EMI62NQPPZW6","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":"57859a7352022cb88648b399bfb9ea58bfe7e30bc7293800e47706ee8e0b0fb7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-04-23T03:03:13Z","title_canon_sha256":"6c2590e61ce6f2abeb24a53cc18282d6c69c2acefecab349fb40660905e99235"},"schema_version":"1.0","source":{"id":"1804.08233","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.08233","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"arxiv_version","alias_value":"1804.08233v3","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08233","created_at":"2026-05-17T23:56:53Z"},{"alias_kind":"pith_short_12","alias_value":"XQRAKQYU4DHJ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"XQRAKQYU4DHJ45EM","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"XQRAKQYU","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:6ffc1ace43d297547798dafb5d37a5a91ff49c5895c152ab6fbf4c2d620fcde6","target":"graph","created_at":"2026-05-17T23:56:53Z","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":"Considering the use of Fully Connected (FC) layer limits the performance of Convolutional Neural Networks (CNNs), this paper develops a method to improve the coupling between the convolution layer and the FC layer by reducing the noise in Feature Maps (FMs). Our approach is divided into three steps. Firstly, we separate all the FMs into n blocks equally. Then, the weighted summation of FMs at the same position in all blocks constitutes a new block of FMs. Finally, we replicate this new block into n copies and concatenate them as the input to the FC layer. This sharing of FMs could reduce the n","authors_text":"Chao Gao, Qiang Qu, Yang Liu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-04-23T03:03:13Z","title":"N-fold Superposition: Improving Neural Networks by Reducing the Noise in Feature Maps"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08233","kind":"arxiv","version":3},"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:a0283b2e8086623dd1bb4bea0b04cc7615573187585c050bf8dbec1608f70c7a","target":"record","created_at":"2026-05-17T23:56:53Z","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":"57859a7352022cb88648b399bfb9ea58bfe7e30bc7293800e47706ee8e0b0fb7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-04-23T03:03:13Z","title_canon_sha256":"6c2590e61ce6f2abeb24a53cc18282d6c69c2acefecab349fb40660905e99235"},"schema_version":"1.0","source":{"id":"1804.08233","kind":"arxiv","version":3}},"canonical_sha256":"bc22054314e0ce9e748c47b4d83df9b7b967253056a2401fb4d30c50b3140031","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc22054314e0ce9e748c47b4d83df9b7b967253056a2401fb4d30c50b3140031","first_computed_at":"2026-05-17T23:56:53.451264Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:53.451264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"p2k4G85T3zLlEvoY7mKA7LgZRFMANZTB2YEn/tIYIS+gRRcjy66LJKZHoiOughAuz/lZCPYZP0FO+GGw2qRHBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:53.451828Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.08233","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0283b2e8086623dd1bb4bea0b04cc7615573187585c050bf8dbec1608f70c7a","sha256:6ffc1ace43d297547798dafb5d37a5a91ff49c5895c152ab6fbf4c2d620fcde6"],"state_sha256":"5693287f66af9df3d2f2758cce51bc1e5fab95d732b0dd0ab4e424d41b93a0db"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XhAKtrFsjG23E+rFAJes1oZ2aytPAE4KSJ0hnX/AACRTNBC+XCY9oAqYrH5ZVHN3wtcVoN1BpQ7twl14WxbyCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T16:59:16.769427Z","bundle_sha256":"94aecb3c306158221b6457560c20685dcd53fc629669f2c7cdf090d4cd187f0b"}}