{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:SQRDFOOPQ5QT2FJ6L4L3IIDPA4","short_pith_number":"pith:SQRDFOOP","canonical_record":{"source":{"id":"2310.20478","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-31T14:11:37Z","cross_cats_sorted":[],"title_canon_sha256":"67f32610af8deb519a29458ed925b30bbde8ca609316d61dd2faf1e2af9eb022","abstract_canon_sha256":"94ff2dd3fb2cadcf2bf35eb551a66a8fc02491586f23a550782cb689e43d7cde"},"schema_version":"1.0"},"canonical_sha256":"942232b9cf87613d153e5f17b4206f0714a4146d2b84593142c384db5a636568","source":{"kind":"arxiv","id":"2310.20478","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.20478","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"arxiv_version","alias_value":"2310.20478v1","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.20478","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_12","alias_value":"SQRDFOOPQ5QT","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_16","alias_value":"SQRDFOOPQ5QT2FJ6","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_8","alias_value":"SQRDFOOP","created_at":"2026-07-05T08:49:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:SQRDFOOPQ5QT2FJ6L4L3IIDPA4","target":"record","payload":{"canonical_record":{"source":{"id":"2310.20478","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-31T14:11:37Z","cross_cats_sorted":[],"title_canon_sha256":"67f32610af8deb519a29458ed925b30bbde8ca609316d61dd2faf1e2af9eb022","abstract_canon_sha256":"94ff2dd3fb2cadcf2bf35eb551a66a8fc02491586f23a550782cb689e43d7cde"},"schema_version":"1.0"},"canonical_sha256":"942232b9cf87613d153e5f17b4206f0714a4146d2b84593142c384db5a636568","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:49:26.471386Z","signature_b64":"9Uo1lcJ96UBfSr+MFfR6qlfbzOIKaKthdHSHeY2zZzAJoLAUvTKIaUjIhDMpAXAcqd0ibg9EcdNVX8qiyUWDDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"942232b9cf87613d153e5f17b4206f0714a4146d2b84593142c384db5a636568","last_reissued_at":"2026-07-05T08:49:26.470958Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:49:26.470958Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.20478","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":"2026-07-05T08:49:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0ZDgskja7juU6AUbA3VyPrT7tgYQN8yuO6SJxcyT43TWErcNr39xFWuTpHhK9DlQOalOuyxfqSmZED4cq6nvAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T22:47:50.660168Z"},"content_sha256":"d758ad9ac16913f7292e5fa9dbd9a2dbae124e0190e2471e1b678fc6bc4f2dbf","schema_version":"1.0","event_id":"sha256:d758ad9ac16913f7292e5fa9dbd9a2dbae124e0190e2471e1b678fc6bc4f2dbf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:SQRDFOOPQ5QT2FJ6L4L3IIDPA4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unveiling Black-boxes: Explainable Deep Learning Models for Patent Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Alexander Boden, Gunnar Stevens, Md. Rezaul Karim, Md Shajalal, Sebastian Denef","submitted_at":"2023-10-31T14:11:37Z","abstract_excerpt":"Recent technological advancements have led to a large number of patents in a diverse range of domains, making it challenging for human experts to analyze and manage. State-of-the-art methods for multi-label patent classification rely on deep neural networks (DNNs), which are complex and often considered black-boxes due to their opaque decision-making processes. In this paper, we propose a novel deep explainable patent classification framework by introducing layer-wise relevance propagation (LRP) to provide human-understandable explanations for predictions. We train several DNN models, includin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.20478","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2310.20478/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:49:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9YOw8p60pg6BLjbeSP7Eh55f6UJ8Xgk9xYLfwWHcsrclHRuyb6IrMtij0y6MGXIwwenVBz+zlPdfEaMFQWe+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T22:47:50.661076Z"},"content_sha256":"4022733929f98ed3285dcb8e8b17366bbe425642ac792ba5d5bd7953728b1a04","schema_version":"1.0","event_id":"sha256:4022733929f98ed3285dcb8e8b17366bbe425642ac792ba5d5bd7953728b1a04"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/bundle.json","state_url":"https://pith.science/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/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":"2026-08-19T22:47:50Z","links":{"resolver":"https://pith.science/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4","bundle":"https://pith.science/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/bundle.json","state":"https://pith.science/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SQRDFOOPQ5QT2FJ6L4L3IIDPA4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SQRDFOOPQ5QT2FJ6L4L3IIDPA4","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":"94ff2dd3fb2cadcf2bf35eb551a66a8fc02491586f23a550782cb689e43d7cde","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-31T14:11:37Z","title_canon_sha256":"67f32610af8deb519a29458ed925b30bbde8ca609316d61dd2faf1e2af9eb022"},"schema_version":"1.0","source":{"id":"2310.20478","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.20478","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"arxiv_version","alias_value":"2310.20478v1","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.20478","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_12","alias_value":"SQRDFOOPQ5QT","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_16","alias_value":"SQRDFOOPQ5QT2FJ6","created_at":"2026-07-05T08:49:26Z"},{"alias_kind":"pith_short_8","alias_value":"SQRDFOOP","created_at":"2026-07-05T08:49:26Z"}],"graph_snapshots":[{"event_id":"sha256:4022733929f98ed3285dcb8e8b17366bbe425642ac792ba5d5bd7953728b1a04","target":"graph","created_at":"2026-07-05T08:49:26Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2310.20478/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent technological advancements have led to a large number of patents in a diverse range of domains, making it challenging for human experts to analyze and manage. State-of-the-art methods for multi-label patent classification rely on deep neural networks (DNNs), which are complex and often considered black-boxes due to their opaque decision-making processes. In this paper, we propose a novel deep explainable patent classification framework by introducing layer-wise relevance propagation (LRP) to provide human-understandable explanations for predictions. We train several DNN models, includin","authors_text":"Alexander Boden, Gunnar Stevens, Md. Rezaul Karim, Md Shajalal, Sebastian Denef","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-31T14:11:37Z","title":"Unveiling Black-boxes: Explainable Deep Learning Models for Patent Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.20478","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:d758ad9ac16913f7292e5fa9dbd9a2dbae124e0190e2471e1b678fc6bc4f2dbf","target":"record","created_at":"2026-07-05T08:49:26Z","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":"94ff2dd3fb2cadcf2bf35eb551a66a8fc02491586f23a550782cb689e43d7cde","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-31T14:11:37Z","title_canon_sha256":"67f32610af8deb519a29458ed925b30bbde8ca609316d61dd2faf1e2af9eb022"},"schema_version":"1.0","source":{"id":"2310.20478","kind":"arxiv","version":1}},"canonical_sha256":"942232b9cf87613d153e5f17b4206f0714a4146d2b84593142c384db5a636568","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"942232b9cf87613d153e5f17b4206f0714a4146d2b84593142c384db5a636568","first_computed_at":"2026-07-05T08:49:26.470958Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:49:26.470958Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9Uo1lcJ96UBfSr+MFfR6qlfbzOIKaKthdHSHeY2zZzAJoLAUvTKIaUjIhDMpAXAcqd0ibg9EcdNVX8qiyUWDDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:49:26.471386Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.20478","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d758ad9ac16913f7292e5fa9dbd9a2dbae124e0190e2471e1b678fc6bc4f2dbf","sha256:4022733929f98ed3285dcb8e8b17366bbe425642ac792ba5d5bd7953728b1a04"],"state_sha256":"f70cb4677f5a2250e50119152155775515991bc643d48a6895e22b3cdd8cfbae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gR4smOnB9EO800UIMTpgPzvicLj4p8HfL2gbsEoQS6wgYezcV2MON6Wyc8DydPz1Aup/i+E2SpxAruH2pI0LDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T22:47:50.667499Z","bundle_sha256":"02eead1cd7273db33c7ef7c070fdcd7d40055c008c6cedcff2932a53fd83ea00"}}