{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:6RVHDFUFEHNFDTNM5IU76SKLDF","short_pith_number":"pith:6RVHDFUF","schema_version":"1.0","canonical_sha256":"f46a71968521da51cdacea29ff494b1951bd85832fa4859bf8a4e245278b0ae3","source":{"kind":"arxiv","id":"1908.06306","version":4},"attestation_state":"computed","paper":{"title":"U-CAM: Visual Explanation using Uncertainty based Class Activation Maps","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Badri N. Patro, Mayank Lunayach, Shivansh Patel, Vinay P. Namboodiri","submitted_at":"2019-08-17T14:39:36Z","abstract_excerpt":"Understanding and explaining deep learning models is an imperative task. Towards this, we propose a method that obtains gradient-based certainty estimates that also provide visual attention maps. Particularly, we solve for visual question answering task. We incorporate modern probabilistic deep learning methods that we further improve by using the gradients for these estimates. These have two-fold benefits: a) improvement in obtaining the certainty estimates that correlate better with misclassified samples and b) improved attention maps that provide state-of-the-art results in terms of correla"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1908.06306","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2019-08-17T14:39:36Z","cross_cats_sorted":["cs.CL","cs.LG","eess.IV"],"title_canon_sha256":"207c0849774e7eb3ae1f6f1f9981ca84c86506d83a4ec25133a3f1f4f83d6e78","abstract_canon_sha256":"2bc782d62085e5856f23f2a6948528efbe8e0b1a54d77f06deb422b7924a6d7e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:12:53.198656Z","signature_b64":"XUvWrDQ6zj4DOZ6FKoX7tL/h4SispumT8zW9hvQJEa0j02Bru4K2pN0dV6JWxEOIAeJJXbpLRjQNif7A8l2dCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f46a71968521da51cdacea29ff494b1951bd85832fa4859bf8a4e245278b0ae3","last_reissued_at":"2026-07-05T00:12:53.198161Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:12:53.198161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"U-CAM: Visual Explanation using Uncertainty based Class Activation Maps","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Badri N. Patro, Mayank Lunayach, Shivansh Patel, Vinay P. Namboodiri","submitted_at":"2019-08-17T14:39:36Z","abstract_excerpt":"Understanding and explaining deep learning models is an imperative task. Towards this, we propose a method that obtains gradient-based certainty estimates that also provide visual attention maps. Particularly, we solve for visual question answering task. We incorporate modern probabilistic deep learning methods that we further improve by using the gradients for these estimates. These have two-fold benefits: a) improvement in obtaining the certainty estimates that correlate better with misclassified samples and b) improved attention maps that provide state-of-the-art results in terms of correla"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06306","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.06306/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1908.06306","created_at":"2026-07-05T00:12:53.198219+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.06306v4","created_at":"2026-07-05T00:12:53.198219+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06306","created_at":"2026-07-05T00:12:53.198219+00:00"},{"alias_kind":"pith_short_12","alias_value":"6RVHDFUFEHNF","created_at":"2026-07-05T00:12:53.198219+00:00"},{"alias_kind":"pith_short_16","alias_value":"6RVHDFUFEHNFDTNM","created_at":"2026-07-05T00:12:53.198219+00:00"},{"alias_kind":"pith_short_8","alias_value":"6RVHDFUF","created_at":"2026-07-05T00:12:53.198219+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF","json":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF.json","graph_json":"https://pith.science/api/pith-number/6RVHDFUFEHNFDTNM5IU76SKLDF/graph.json","events_json":"https://pith.science/api/pith-number/6RVHDFUFEHNFDTNM5IU76SKLDF/events.json","paper":"https://pith.science/paper/6RVHDFUF"},"agent_actions":{"view_html":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF","download_json":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF.json","view_paper":"https://pith.science/paper/6RVHDFUF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.06306&json=true","fetch_graph":"https://pith.science/api/pith-number/6RVHDFUFEHNFDTNM5IU76SKLDF/graph.json","fetch_events":"https://pith.science/api/pith-number/6RVHDFUFEHNFDTNM5IU76SKLDF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF/action/storage_attestation","attest_author":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF/action/author_attestation","sign_citation":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF/action/citation_signature","submit_replication":"https://pith.science/pith/6RVHDFUFEHNFDTNM5IU76SKLDF/action/replication_record"}},"created_at":"2026-07-05T00:12:53.198219+00:00","updated_at":"2026-07-05T00:12:53.198219+00:00"}