{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:E42HXJJ7CNDPJMPCZ2MKBBD4MC","short_pith_number":"pith:E42HXJJ7","canonical_record":{"source":{"id":"1611.07450","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-22T18:34:36Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"8b61aec900b51264781ec89e540c881145dd3289a0c68327f79c6f5b91215c6e","abstract_canon_sha256":"f68fac44245227f940177da98b5e2989fd3a04e50b0b651798563e5350d1990b"},"schema_version":"1.0"},"canonical_sha256":"27347ba53f1346f4b1e2ce98a0847c60919963d726dbf371f2cc1d9929708c74","source":{"kind":"arxiv","id":"1611.07450","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07450","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07450v2","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07450","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"pith_short_12","alias_value":"E42HXJJ7CNDP","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"E42HXJJ7CNDPJMPC","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"E42HXJJ7","created_at":"2026-05-18T12:30:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:E42HXJJ7CNDPJMPCZ2MKBBD4MC","target":"record","payload":{"canonical_record":{"source":{"id":"1611.07450","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-22T18:34:36Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"8b61aec900b51264781ec89e540c881145dd3289a0c68327f79c6f5b91215c6e","abstract_canon_sha256":"f68fac44245227f940177da98b5e2989fd3a04e50b0b651798563e5350d1990b"},"schema_version":"1.0"},"canonical_sha256":"27347ba53f1346f4b1e2ce98a0847c60919963d726dbf371f2cc1d9929708c74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:07.953654Z","signature_b64":"mNSxvdFxggvWmgAib9XKfqn1/pPoDrbOhSuGN8vMW0vhvRklnVB5222/Iq8hZ9Tp4EBtsxp/fjQGpC0p7g2gAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27347ba53f1346f4b1e2ce98a0847c60919963d726dbf371f2cc1d9929708c74","last_reissued_at":"2026-05-18T00:52:07.953091Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:07.953091Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.07450","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":"2026-05-18T00:52:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KHX9GH43qRt+wIzX9Z8ijNgB0U5aVsHXjvpOERBKI+e5GRps9qyqYnhfYQHhLTLH9KlGYKAVkOivANOOETXWAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:54:53.409858Z"},"content_sha256":"105b4644e779874af8a2f7e29b1db8063c4b26ca9b54bd14a4e3bb20c317cfe3","schema_version":"1.0","event_id":"sha256:105b4644e779874af8a2f7e29b1db8063c4b26ca9b54bd14a4e3bb20c317cfe3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:E42HXJJ7CNDPJMPCZ2MKBBD4MC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Grad-CAM: Why did you say that?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Abhishek Das, Devi Parikh, Dhruv Batra, Michael Cogswell, Ramakrishna Vedantam, Ramprasaath R Selvaraju","submitted_at":"2016-11-22T18:34:36Z","abstract_excerpt":"We propose a technique for making Convolutional Neural Network (CNN)-based models more transparent by visualizing input regions that are 'important' for predictions -- or visual explanations. Our approach, called Gradient-weighted Class Activation Mapping (Grad-CAM), uses class-specific gradient information to localize important regions. These localizations are combined with existing pixel-space visualizations to create a novel high-resolution and class-discriminative visualization called Guided Grad-CAM. These methods help better understand CNN-based models, including image captioning and vis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07450","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":"2026-05-18T00:52:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tVkQCMIfoOWsLC4dbTrdOrvKGRXWbvvym3Ax3jwWkEvmmcO2Or2t8CKiyDAGrFfMbz9NLMSDDGY/Pe9uFXMBCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:54:53.410532Z"},"content_sha256":"e3da8437fa2a6cface11b3e612a84d327d6653d66432089dfbdb3442280c6b43","schema_version":"1.0","event_id":"sha256:e3da8437fa2a6cface11b3e612a84d327d6653d66432089dfbdb3442280c6b43"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/bundle.json","state_url":"https://pith.science/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/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":"2026-06-06T19:54:53Z","links":{"resolver":"https://pith.science/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC","bundle":"https://pith.science/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/bundle.json","state":"https://pith.science/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E42HXJJ7CNDPJMPCZ2MKBBD4MC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:E42HXJJ7CNDPJMPCZ2MKBBD4MC","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":"f68fac44245227f940177da98b5e2989fd3a04e50b0b651798563e5350d1990b","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-22T18:34:36Z","title_canon_sha256":"8b61aec900b51264781ec89e540c881145dd3289a0c68327f79c6f5b91215c6e"},"schema_version":"1.0","source":{"id":"1611.07450","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.07450","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"arxiv_version","alias_value":"1611.07450v2","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.07450","created_at":"2026-05-18T00:52:07Z"},{"alias_kind":"pith_short_12","alias_value":"E42HXJJ7CNDP","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"E42HXJJ7CNDPJMPC","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"E42HXJJ7","created_at":"2026-05-18T12:30:12Z"}],"graph_snapshots":[{"event_id":"sha256:e3da8437fa2a6cface11b3e612a84d327d6653d66432089dfbdb3442280c6b43","target":"graph","created_at":"2026-05-18T00:52:07Z","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":"We propose a technique for making Convolutional Neural Network (CNN)-based models more transparent by visualizing input regions that are 'important' for predictions -- or visual explanations. Our approach, called Gradient-weighted Class Activation Mapping (Grad-CAM), uses class-specific gradient information to localize important regions. These localizations are combined with existing pixel-space visualizations to create a novel high-resolution and class-discriminative visualization called Guided Grad-CAM. These methods help better understand CNN-based models, including image captioning and vis","authors_text":"Abhishek Das, Devi Parikh, Dhruv Batra, Michael Cogswell, Ramakrishna Vedantam, Ramprasaath R Selvaraju","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-22T18:34:36Z","title":"Grad-CAM: Why did you say that?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.07450","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":"sha256:105b4644e779874af8a2f7e29b1db8063c4b26ca9b54bd14a4e3bb20c317cfe3","target":"record","created_at":"2026-05-18T00:52:07Z","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":"f68fac44245227f940177da98b5e2989fd3a04e50b0b651798563e5350d1990b","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-22T18:34:36Z","title_canon_sha256":"8b61aec900b51264781ec89e540c881145dd3289a0c68327f79c6f5b91215c6e"},"schema_version":"1.0","source":{"id":"1611.07450","kind":"arxiv","version":2}},"canonical_sha256":"27347ba53f1346f4b1e2ce98a0847c60919963d726dbf371f2cc1d9929708c74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27347ba53f1346f4b1e2ce98a0847c60919963d726dbf371f2cc1d9929708c74","first_computed_at":"2026-05-18T00:52:07.953091Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:07.953091Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mNSxvdFxggvWmgAib9XKfqn1/pPoDrbOhSuGN8vMW0vhvRklnVB5222/Iq8hZ9Tp4EBtsxp/fjQGpC0p7g2gAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:07.953654Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.07450","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:105b4644e779874af8a2f7e29b1db8063c4b26ca9b54bd14a4e3bb20c317cfe3","sha256:e3da8437fa2a6cface11b3e612a84d327d6653d66432089dfbdb3442280c6b43"],"state_sha256":"cca8af760f7f2ce23d25533e0ed8150122bf79d2b93668b9d1725d02472a0730"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Em12vaAar6fcS8+vUJ7VxhWYf06zKi4xDD1wYKjfrqb1UqemZ1Ghx0HDeZK//jKr6KOXPko7OUIUO3AvQQ0NCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T19:54:53.414198Z","bundle_sha256":"fb373870d4a06a0f9f1d086175b0382e7d3c551007d05d69e4182b8f53195de4"}}