{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ZHLM7TZOODF5JIC57VWFJL4LF6","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":"285c46c05272b4c63e2491ca38ec2ba2a8f5fab87f8a1e51347938545d887fd9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2020-12-15T12:58:44Z","title_canon_sha256":"b0d9ef3cd800b4f62715c02b5571433912d053c065d3d7a9a15dcff838af1551"},"schema_version":"1.0","source":{"id":"2012.09603","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.09603","created_at":"2026-07-05T02:00:19Z"},{"alias_kind":"arxiv_version","alias_value":"2012.09603v1","created_at":"2026-07-05T02:00:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.09603","created_at":"2026-07-05T02:00:19Z"},{"alias_kind":"pith_short_12","alias_value":"ZHLM7TZOODF5","created_at":"2026-07-05T02:00:19Z"},{"alias_kind":"pith_short_16","alias_value":"ZHLM7TZOODF5JIC5","created_at":"2026-07-05T02:00:19Z"},{"alias_kind":"pith_short_8","alias_value":"ZHLM7TZO","created_at":"2026-07-05T02:00:19Z"}],"graph_snapshots":[{"event_id":"sha256:80bebfe44b7d78ca15e03f892f06ff47f9833ea961cf718bc914d225e96eb664","target":"graph","created_at":"2026-07-05T02:00:19Z","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/2012.09603/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Explainable AI(XAI)is a domain focused on providing interpretability and explainability of a decision-making process. In the domain of law, in addition to system and data transparency, it also requires the (legal-) decision-model transparency and the ability to understand the models inner working when arriving at the decision. This paper provides the first approaches to using a popular image processing technique, Grad-CAM, to showcase the explainability concept for legal texts. With the help of adapted Grad-CAM metrics, we show the interplay between the choice of embeddings, its consideration ","authors_text":"Jedrzej M. Nowosielski, Lukasz Gorski, Shashishekar Ramakrishna","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2020-12-15T12:58:44Z","title":"Towards Grad-CAM Based Explainability in a Legal Text Processing Pipeline"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.09603","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:ba4af151a7debf317ab03e7ce36f88b504e366d66c0628e87fbd3ee73bda86d4","target":"record","created_at":"2026-07-05T02:00:19Z","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":"285c46c05272b4c63e2491ca38ec2ba2a8f5fab87f8a1e51347938545d887fd9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2020-12-15T12:58:44Z","title_canon_sha256":"b0d9ef3cd800b4f62715c02b5571433912d053c065d3d7a9a15dcff838af1551"},"schema_version":"1.0","source":{"id":"2012.09603","kind":"arxiv","version":1}},"canonical_sha256":"c9d6cfcf2e70cbd4a05dfd6c54af8b2fb3a8764278c3a670eef821f7f1e67ef4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9d6cfcf2e70cbd4a05dfd6c54af8b2fb3a8764278c3a670eef821f7f1e67ef4","first_computed_at":"2026-07-05T02:00:19.384619Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:00:19.384619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GY+xXdiTlMUyA/fdRL1BLPa85jaJBPkMJPC6uXiCoEL1dXgaZkXjO8vcU6/Yn6tXGad43Rf7RLuh6FdhyuZWCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:00:19.385071Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.09603","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba4af151a7debf317ab03e7ce36f88b504e366d66c0628e87fbd3ee73bda86d4","sha256:80bebfe44b7d78ca15e03f892f06ff47f9833ea961cf718bc914d225e96eb664"],"state_sha256":"0ca86f9261fb29176677a512d01a5740e8d91494fe0b04d443d154e87284ea4e"}