{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ZZF64T4OV2Y42NOQZZWVFVKNBR","short_pith_number":"pith:ZZF64T4O","canonical_record":{"source":{"id":"2009.07896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-09-16T18:57:57Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"482eb81c1b0cd391436ac240c3efa60f6bf7d43c177da1327412dee1be057eb0","abstract_canon_sha256":"a55069b3022e3c26d53104dc45d86066607d6904eee03a63d10ab70a65bfffb8"},"schema_version":"1.0"},"canonical_sha256":"ce4bee4f8eaeb1cd35d0ce6d52d54d0c4a8247cda58be35811608cf24ef9e338","source":{"kind":"arxiv","id":"2009.07896","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.07896","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"arxiv_version","alias_value":"2009.07896v1","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.07896","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZZF64T4OV2Y4","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZZF64T4OV2Y42NOQ","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZZF64T4O","created_at":"2026-07-05T01:35:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ZZF64T4OV2Y42NOQZZWVFVKNBR","target":"record","payload":{"canonical_record":{"source":{"id":"2009.07896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-09-16T18:57:57Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"482eb81c1b0cd391436ac240c3efa60f6bf7d43c177da1327412dee1be057eb0","abstract_canon_sha256":"a55069b3022e3c26d53104dc45d86066607d6904eee03a63d10ab70a65bfffb8"},"schema_version":"1.0"},"canonical_sha256":"ce4bee4f8eaeb1cd35d0ce6d52d54d0c4a8247cda58be35811608cf24ef9e338","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:35:59.343254Z","signature_b64":"5BFPsQVnMuWx1bscl77alGp3i4DNkwfkavYdQDTHKMxIpQjw1MslXO+J90Fje7z9zkF0ehIqXAdpc0uI6SOvDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce4bee4f8eaeb1cd35d0ce6d52d54d0c4a8247cda58be35811608cf24ef9e338","last_reissued_at":"2026-07-05T01:35:59.342803Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:35:59.342803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.07896","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":"2026-07-05T01:35:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wrEZ+qcN4RYU0DSEdB4HiEldISt/2Cs7srf60Ee97KKphYF+ZWLhDVj4Bn4INwCpBwJxrUwPEz4azHrYboLNDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:14:58.257805Z"},"content_sha256":"003a1e1210fd4c72677537fdff54965422b3edecb7bc53990e0f51c2b2896dfd","schema_version":"1.0","event_id":"sha256:003a1e1210fd4c72677537fdff54965422b3edecb7bc53990e0f51c2b2896dfd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ZZF64T4OV2Y42NOQZZWVFVKNBR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Captum: A unified and generic model interpretability library for PyTorch","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexander Melnikov, Bilal Alsallakh, Carlos Araya, Edward Wang, Jonathan Reynolds, Miguel Martin, Narine Kokhlikyan, Natalia Kliushkina, Orion Reblitz-Richardson, Siqi Yan, Vivek Miglani","submitted_at":"2020-09-16T18:57:57Z","abstract_excerpt":"In this paper we introduce a novel, unified, open-source model interpretability library for PyTorch [12]. The library contains generic implementations of a number of gradient and perturbation-based attribution algorithms, also known as feature, neuron and layer importance algorithms, as well as a set of evaluation metrics for these algorithms. It can be used for both classification and non-classification models including graph-structured models built on Neural Networks (NN). In this paper we give a high-level overview of supported attribution algorithms and show how to perform memory-efficient"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.07896","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/2009.07896/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":"2026-07-05T01:35:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t6yY3wvIbZbEakRVDWS665++i2B55ASCgtg3SFVE1TKwiS/RrfswoZ2MWClf0nZZlqXcJ/YcrFZk0i16unQhBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:14:58.260215Z"},"content_sha256":"60f370d70b7ddf824ec6d60229b7c22fd4f6f1733a7331890892296906e030e8","schema_version":"1.0","event_id":"sha256:60f370d70b7ddf824ec6d60229b7c22fd4f6f1733a7331890892296906e030e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/bundle.json","state_url":"https://pith.science/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/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":"2026-08-14T08:14:58Z","links":{"resolver":"https://pith.science/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR","bundle":"https://pith.science/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/bundle.json","state":"https://pith.science/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZZF64T4OV2Y42NOQZZWVFVKNBR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ZZF64T4OV2Y42NOQZZWVFVKNBR","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":"a55069b3022e3c26d53104dc45d86066607d6904eee03a63d10ab70a65bfffb8","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-09-16T18:57:57Z","title_canon_sha256":"482eb81c1b0cd391436ac240c3efa60f6bf7d43c177da1327412dee1be057eb0"},"schema_version":"1.0","source":{"id":"2009.07896","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.07896","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"arxiv_version","alias_value":"2009.07896v1","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.07896","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZZF64T4OV2Y4","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZZF64T4OV2Y42NOQ","created_at":"2026-07-05T01:35:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZZF64T4O","created_at":"2026-07-05T01:35:59Z"}],"graph_snapshots":[{"event_id":"sha256:60f370d70b7ddf824ec6d60229b7c22fd4f6f1733a7331890892296906e030e8","target":"graph","created_at":"2026-07-05T01:35:59Z","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/2009.07896/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we introduce a novel, unified, open-source model interpretability library for PyTorch [12]. The library contains generic implementations of a number of gradient and perturbation-based attribution algorithms, also known as feature, neuron and layer importance algorithms, as well as a set of evaluation metrics for these algorithms. It can be used for both classification and non-classification models including graph-structured models built on Neural Networks (NN). In this paper we give a high-level overview of supported attribution algorithms and show how to perform memory-efficient","authors_text":"Alexander Melnikov, Bilal Alsallakh, Carlos Araya, Edward Wang, Jonathan Reynolds, Miguel Martin, Narine Kokhlikyan, Natalia Kliushkina, Orion Reblitz-Richardson, Siqi Yan, Vivek Miglani","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.07896","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":"sha256:003a1e1210fd4c72677537fdff54965422b3edecb7bc53990e0f51c2b2896dfd","target":"record","created_at":"2026-07-05T01:35:59Z","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":"a55069b3022e3c26d53104dc45d86066607d6904eee03a63d10ab70a65bfffb8","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-09-16T18:57:57Z","title_canon_sha256":"482eb81c1b0cd391436ac240c3efa60f6bf7d43c177da1327412dee1be057eb0"},"schema_version":"1.0","source":{"id":"2009.07896","kind":"arxiv","version":1}},"canonical_sha256":"ce4bee4f8eaeb1cd35d0ce6d52d54d0c4a8247cda58be35811608cf24ef9e338","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ce4bee4f8eaeb1cd35d0ce6d52d54d0c4a8247cda58be35811608cf24ef9e338","first_computed_at":"2026-07-05T01:35:59.342803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:35:59.342803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5BFPsQVnMuWx1bscl77alGp3i4DNkwfkavYdQDTHKMxIpQjw1MslXO+J90Fje7z9zkF0ehIqXAdpc0uI6SOvDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:35:59.343254Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.07896","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:003a1e1210fd4c72677537fdff54965422b3edecb7bc53990e0f51c2b2896dfd","sha256:60f370d70b7ddf824ec6d60229b7c22fd4f6f1733a7331890892296906e030e8"],"state_sha256":"8296b981295d9f9577d1eb740fc4006857d53a7f43a996afea1d8f8c0620a782"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r+NtJr6cp66ls3pQE6LMyKavXuICwged7tpc0yHd/ntu3jCrbOMsl9N9n57bsH3MSmKOIHP1IBtu8VNOXnnBCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:14:58.273350Z","bundle_sha256":"208cb0abcff80a6b9692963e0f293fcac51d26894026b29c0a6923c95011d792"}}