{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WFIQ3VFCIALGN46EKGJDDPUBDF","short_pith_number":"pith:WFIQ3VFC","canonical_record":{"source":{"id":"2508.10490","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-14T09:49:07Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"e6f7d6b000503af82d532e209871ec0baa5c7973bc76743f3d5f3b9a4820cae5","abstract_canon_sha256":"05ef0b6c12d36132842069bfa0c761517222eb220344a388c4cad06d112390b3"},"schema_version":"1.0"},"canonical_sha256":"b1510dd4a2401666f3c4519231be8119700711df56d6bbf1129c4ec9ad235d6a","source":{"kind":"arxiv","id":"2508.10490","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.10490","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"2508.10490v1","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.10490","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"WFIQ3VFCIALG","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_16","alias_value":"WFIQ3VFCIALGN46E","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_8","alias_value":"WFIQ3VFC","created_at":"2026-07-05T11:53:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WFIQ3VFCIALGN46EKGJDDPUBDF","target":"record","payload":{"canonical_record":{"source":{"id":"2508.10490","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-14T09:49:07Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"e6f7d6b000503af82d532e209871ec0baa5c7973bc76743f3d5f3b9a4820cae5","abstract_canon_sha256":"05ef0b6c12d36132842069bfa0c761517222eb220344a388c4cad06d112390b3"},"schema_version":"1.0"},"canonical_sha256":"b1510dd4a2401666f3c4519231be8119700711df56d6bbf1129c4ec9ad235d6a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:53:57.460499Z","signature_b64":"iso9WgsjERMEpejthNAcbSdRenwqJy0PA2YE9g3wnhZ/+vI4YSdCfve3FJ6i9PL9WC151jOeJfi+/bT+fG3lBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b1510dd4a2401666f3c4519231be8119700711df56d6bbf1129c4ec9ad235d6a","last_reissued_at":"2026-07-05T11:53:57.459927Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:53:57.459927Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.10490","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":"2026-07-05T11:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uTcZdtoRBXw9/0NuzrOiYd5jBYeqse/LgMvnXlN3yFr4f6ZSz7QgaBPtSosgsZDap2EK0qPbt+lFaodI7XMOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:24:12.777302Z"},"content_sha256":"e8461ab2b6218c585169041f1970068e27fe047ade6cfe6a2f64f9a8970eafbf","schema_version":"1.0","event_id":"sha256:e8461ab2b6218c585169041f1970068e27fe047ade6cfe6a2f64f9a8970eafbf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WFIQ3VFCIALGN46EKGJDDPUBDF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Amir Mehrpanah, Hossein Azizpour, Kevin Smith, Matteo Gamba","submitted_at":"2025-08-14T09:49:07Z","abstract_excerpt":"ReLU networks, while prevalent for visual data, have sharp transitions, sometimes relying on individual pixels for predictions, making vanilla gradient-based explanations noisy and difficult to interpret. Existing methods, such as GradCAM, smooth these explanations by producing surrogate models at the cost of faithfulness. We introduce a unifying spectral framework to systematically analyze and quantify smoothness, faithfulness, and their trade-off in explanations. Using this framework, we quantify and regularize the contribution of ReLU networks to high-frequency information, providing a prin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.10490","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/2508.10490/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":"2026-07-05T11:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cM41FWf7pihjNSZ7vLCsuIIvjSs4LpVSSpgrKalI643ax/vBcof6B33BXx4IGP7oYaczcUo0Shb/EpR6Q7k+BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T13:24:12.777962Z"},"content_sha256":"64a8c946c372e8b5de72b6759041018af0754b77e3e6c2206ef53a1803f5023f","schema_version":"1.0","event_id":"sha256:64a8c946c372e8b5de72b6759041018af0754b77e3e6c2206ef53a1803f5023f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/bundle.json","state_url":"https://pith.science/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/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":"2026-08-06T13:24:12Z","links":{"resolver":"https://pith.science/pith/WFIQ3VFCIALGN46EKGJDDPUBDF","bundle":"https://pith.science/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/bundle.json","state":"https://pith.science/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WFIQ3VFCIALGN46EKGJDDPUBDF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WFIQ3VFCIALGN46EKGJDDPUBDF","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":"05ef0b6c12d36132842069bfa0c761517222eb220344a388c4cad06d112390b3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-14T09:49:07Z","title_canon_sha256":"e6f7d6b000503af82d532e209871ec0baa5c7973bc76743f3d5f3b9a4820cae5"},"schema_version":"1.0","source":{"id":"2508.10490","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.10490","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"2508.10490v1","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.10490","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"WFIQ3VFCIALG","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_16","alias_value":"WFIQ3VFCIALGN46E","created_at":"2026-07-05T11:53:57Z"},{"alias_kind":"pith_short_8","alias_value":"WFIQ3VFC","created_at":"2026-07-05T11:53:57Z"}],"graph_snapshots":[{"event_id":"sha256:64a8c946c372e8b5de72b6759041018af0754b77e3e6c2206ef53a1803f5023f","target":"graph","created_at":"2026-07-05T11:53:57Z","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/2508.10490/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"ReLU networks, while prevalent for visual data, have sharp transitions, sometimes relying on individual pixels for predictions, making vanilla gradient-based explanations noisy and difficult to interpret. Existing methods, such as GradCAM, smooth these explanations by producing surrogate models at the cost of faithfulness. We introduce a unifying spectral framework to systematically analyze and quantify smoothness, faithfulness, and their trade-off in explanations. Using this framework, we quantify and regularize the contribution of ReLU networks to high-frequency information, providing a prin","authors_text":"Amir Mehrpanah, Hossein Azizpour, Kevin Smith, Matteo Gamba","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-14T09:49:07Z","title":"On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.10490","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:e8461ab2b6218c585169041f1970068e27fe047ade6cfe6a2f64f9a8970eafbf","target":"record","created_at":"2026-07-05T11:53:57Z","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":"05ef0b6c12d36132842069bfa0c761517222eb220344a388c4cad06d112390b3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-08-14T09:49:07Z","title_canon_sha256":"e6f7d6b000503af82d532e209871ec0baa5c7973bc76743f3d5f3b9a4820cae5"},"schema_version":"1.0","source":{"id":"2508.10490","kind":"arxiv","version":1}},"canonical_sha256":"b1510dd4a2401666f3c4519231be8119700711df56d6bbf1129c4ec9ad235d6a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1510dd4a2401666f3c4519231be8119700711df56d6bbf1129c4ec9ad235d6a","first_computed_at":"2026-07-05T11:53:57.459927Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:53:57.459927Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iso9WgsjERMEpejthNAcbSdRenwqJy0PA2YE9g3wnhZ/+vI4YSdCfve3FJ6i9PL9WC151jOeJfi+/bT+fG3lBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:53:57.460499Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.10490","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e8461ab2b6218c585169041f1970068e27fe047ade6cfe6a2f64f9a8970eafbf","sha256:64a8c946c372e8b5de72b6759041018af0754b77e3e6c2206ef53a1803f5023f"],"state_sha256":"fc9da0c1346ab9fae5cffe053011638e7dfff01730ea1100a5680ef3ea81068b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5FRGz498kB3vQ4qaSNvbi/5OSvy2hSzI7WCtzqxrUYllrBhCOhKYclh8jkpqMlbsxU5l6PmUfCtIrHvBBHSgCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T13:24:12.784321Z","bundle_sha256":"9aeca4056734b5cc796a831ba265f819d6aaf8d5df809749570ecad92eaa0c3b"}}