{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:VNFURS3WYXZBK66NGPAT6VGWSE","short_pith_number":"pith:VNFURS3W","canonical_record":{"source":{"id":"1512.04150","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-14T01:32:33Z","cross_cats_sorted":[],"title_canon_sha256":"318d43875357b146f76df1f89ca29f2407af89cb3c0fbc3b654a0868d84d9c3f","abstract_canon_sha256":"950be91788197c205dfb6f2d6fd56681ce5cd644094485d306e3fcec163c5943"},"schema_version":"1.0"},"canonical_sha256":"ab4b48cb76c5f2157bcd33c13f54d6910228443b7ee810b76de2e3034c8d1d59","source":{"kind":"arxiv","id":"1512.04150","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04150","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04150v1","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04150","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"pith_short_12","alias_value":"VNFURS3WYXZB","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"VNFURS3WYXZBK66N","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"VNFURS3W","created_at":"2026-05-18T12:29:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:VNFURS3WYXZBK66NGPAT6VGWSE","target":"record","payload":{"canonical_record":{"source":{"id":"1512.04150","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-14T01:32:33Z","cross_cats_sorted":[],"title_canon_sha256":"318d43875357b146f76df1f89ca29f2407af89cb3c0fbc3b654a0868d84d9c3f","abstract_canon_sha256":"950be91788197c205dfb6f2d6fd56681ce5cd644094485d306e3fcec163c5943"},"schema_version":"1.0"},"canonical_sha256":"ab4b48cb76c5f2157bcd33c13f54d6910228443b7ee810b76de2e3034c8d1d59","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:24:22.983298Z","signature_b64":"387fmpE4sbT/NOHBltVL3zUka7Qj6uxFQfDOEHUvAftMVfVpBkqzF/iZwRbrxCpXyJf/VvFJLqDj9w/LfxEhAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab4b48cb76c5f2157bcd33c13f54d6910228443b7ee810b76de2e3034c8d1d59","last_reissued_at":"2026-05-18T01:24:22.982571Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:24:22.982571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.04150","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":"2026-05-18T01:24:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z0R3suKuLNPYlaLQzLEKlM0Op5hCUvrjlKucJwp09DkPY8tqcZdEKxovybclkKHMLvmfeTpySQMKzz+1QRRFAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T15:34:15.161301Z"},"content_sha256":"3c64c2e1c036a9ea1980881a18dcb69cde7df8f69fb7e5f0d871f90e502c112d","schema_version":"1.0","event_id":"sha256:3c64c2e1c036a9ea1980881a18dcb69cde7df8f69fb7e5f0d871f90e502c112d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:VNFURS3WYXZBK66NGPAT6VGWSE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Deep Features for Discriminative Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aditya Khosla, Agata Lapedriza, Antonio Torralba, Aude Oliva, Bolei Zhou","submitted_at":"2015-12-14T01:32:33Z","abstract_excerpt":"In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despite being trained on image-level labels. While this technique was previously proposed as a means for regularizing training, we find that it actually builds a generic localizable deep representation that can be applied to a variety of tasks. Despite the apparent simplicity of global average pooling, we are able to achieve 37.1% top-5 error for object localization on ILSVRC 2014, which is remarkably cl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04150","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":"2026-05-18T01:24:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+VxT3X5lJMBCVMJs39WdLInCWuV2K16GzsNBRcOLAGaV1W7rauLIDQI18+6GoSIH6dbvPLMqlW8t0K0QhmHQDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T15:34:15.162019Z"},"content_sha256":"5ae0e2e4ae1d31a20ed3bf5cecfedfee58563cbea5fea113b795ca44b2f974f6","schema_version":"1.0","event_id":"sha256:5ae0e2e4ae1d31a20ed3bf5cecfedfee58563cbea5fea113b795ca44b2f974f6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VNFURS3WYXZBK66NGPAT6VGWSE/bundle.json","state_url":"https://pith.science/pith/VNFURS3WYXZBK66NGPAT6VGWSE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VNFURS3WYXZBK66NGPAT6VGWSE/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":"2026-05-22T15:34:15Z","links":{"resolver":"https://pith.science/pith/VNFURS3WYXZBK66NGPAT6VGWSE","bundle":"https://pith.science/pith/VNFURS3WYXZBK66NGPAT6VGWSE/bundle.json","state":"https://pith.science/pith/VNFURS3WYXZBK66NGPAT6VGWSE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VNFURS3WYXZBK66NGPAT6VGWSE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:VNFURS3WYXZBK66NGPAT6VGWSE","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":"950be91788197c205dfb6f2d6fd56681ce5cd644094485d306e3fcec163c5943","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-14T01:32:33Z","title_canon_sha256":"318d43875357b146f76df1f89ca29f2407af89cb3c0fbc3b654a0868d84d9c3f"},"schema_version":"1.0","source":{"id":"1512.04150","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04150","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04150v1","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04150","created_at":"2026-05-18T01:24:22Z"},{"alias_kind":"pith_short_12","alias_value":"VNFURS3WYXZB","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"VNFURS3WYXZBK66N","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"VNFURS3W","created_at":"2026-05-18T12:29:47Z"}],"graph_snapshots":[{"event_id":"sha256:5ae0e2e4ae1d31a20ed3bf5cecfedfee58563cbea5fea113b795ca44b2f974f6","target":"graph","created_at":"2026-05-18T01:24:22Z","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":"In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network to have remarkable localization ability despite being trained on image-level labels. While this technique was previously proposed as a means for regularizing training, we find that it actually builds a generic localizable deep representation that can be applied to a variety of tasks. Despite the apparent simplicity of global average pooling, we are able to achieve 37.1% top-5 error for object localization on ILSVRC 2014, which is remarkably cl","authors_text":"Aditya Khosla, Agata Lapedriza, Antonio Torralba, Aude Oliva, Bolei Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-14T01:32:33Z","title":"Learning Deep Features for Discriminative Localization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04150","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":"sha256:3c64c2e1c036a9ea1980881a18dcb69cde7df8f69fb7e5f0d871f90e502c112d","target":"record","created_at":"2026-05-18T01:24:22Z","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":"950be91788197c205dfb6f2d6fd56681ce5cd644094485d306e3fcec163c5943","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-12-14T01:32:33Z","title_canon_sha256":"318d43875357b146f76df1f89ca29f2407af89cb3c0fbc3b654a0868d84d9c3f"},"schema_version":"1.0","source":{"id":"1512.04150","kind":"arxiv","version":1}},"canonical_sha256":"ab4b48cb76c5f2157bcd33c13f54d6910228443b7ee810b76de2e3034c8d1d59","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab4b48cb76c5f2157bcd33c13f54d6910228443b7ee810b76de2e3034c8d1d59","first_computed_at":"2026-05-18T01:24:22.982571Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:24:22.982571Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"387fmpE4sbT/NOHBltVL3zUka7Qj6uxFQfDOEHUvAftMVfVpBkqzF/iZwRbrxCpXyJf/VvFJLqDj9w/LfxEhAA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:24:22.983298Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.04150","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3c64c2e1c036a9ea1980881a18dcb69cde7df8f69fb7e5f0d871f90e502c112d","sha256:5ae0e2e4ae1d31a20ed3bf5cecfedfee58563cbea5fea113b795ca44b2f974f6"],"state_sha256":"9cf2a8c60a5193a1d98fc81df5ba17b411c9dd3857b218107126ecc965f0bf51"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kVh/UIe0ptu3287B8ernRd0GNzFceviGNRlsOWQV+x2cNZQD+8NhrC8tD+LRsB2VTqWGfi0enANJTV5y1kjpDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T15:34:15.165731Z","bundle_sha256":"0086eb73fc9fe5b06a433be84cde6754b05db604606564fda02dd76c7a155afa"}}