{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:RF3MEPHHGNGCLCQ7FD25FPEHP2","short_pith_number":"pith:RF3MEPHH","canonical_record":{"source":{"id":"1911.00418","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-01T15:14:06Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"afd9682d905afcb8da4b6b1f0cb9d8b3d5b71cb71ccd5eaad9f31fe9638877ab","abstract_canon_sha256":"4a5b8a5dc043ac64d4b79da716a30ef5af97743fb1f0109c6eb83cbed594d367"},"schema_version":"1.0"},"canonical_sha256":"8976c23ce7334c258a1f28f5d2bc877e8fde18fc9181e1b1f736d3ef86ea37a1","source":{"kind":"arxiv","id":"1911.00418","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00418","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00418v2","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00418","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_12","alias_value":"RF3MEPHHGNGC","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_16","alias_value":"RF3MEPHHGNGCLCQ7","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_8","alias_value":"RF3MEPHH","created_at":"2026-07-05T01:16:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:RF3MEPHHGNGCLCQ7FD25FPEHP2","target":"record","payload":{"canonical_record":{"source":{"id":"1911.00418","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-01T15:14:06Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"afd9682d905afcb8da4b6b1f0cb9d8b3d5b71cb71ccd5eaad9f31fe9638877ab","abstract_canon_sha256":"4a5b8a5dc043ac64d4b79da716a30ef5af97743fb1f0109c6eb83cbed594d367"},"schema_version":"1.0"},"canonical_sha256":"8976c23ce7334c258a1f28f5d2bc877e8fde18fc9181e1b1f736d3ef86ea37a1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:16:41.594457Z","signature_b64":"O83dwSjbWrdQnrKkpDLrlVwScDlN3T7KtbIIK1kTW/BNKT5M2PIERTAwjNfYp0VfbMhOErPZmDgcHJNISjtIAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8976c23ce7334c258a1f28f5d2bc877e8fde18fc9181e1b1f736d3ef86ea37a1","last_reissued_at":"2026-07-05T01:16:41.594048Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:16:41.594048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.00418","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:16:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pj/lded8Fs4J9CcxP4HZq0YSbo1TSy1giFvao1yRFqp7g7ff+DkFrPadmSGrRRjxWSN3c99Bx+oUBdPCJ44gAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T13:04:05.865362Z"},"content_sha256":"47c21c4e20ac5642735bbc18b6524034efb98e69558ea7785a4979367b87b2bd","schema_version":"1.0","event_id":"sha256:47c21c4e20ac5642735bbc18b6524034efb98e69558ea7785a4979367b87b2bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:RF3MEPHHGNGCLCQ7FD25FPEHP2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Second-Order Group Influence Functions for Black-Box Predictions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Samyadeep Basu, Soheil Feizi, Xuchen You","submitted_at":"2019-11-01T15:14:06Z","abstract_excerpt":"With the rapid adoption of machine learning systems in sensitive applications, there is an increasing need to make black-box models explainable. Often we want to identify an influential group of training samples in a particular test prediction for a given machine learning model. Existing influence functions tackle this problem by using first-order approximations of the effect of removing a sample from the training set on model parameters. To compute the influence of a group of training samples (rather than an individual point) in model predictions, the change in optimal model parameters after "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00418","kind":"arxiv","version":2},"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/1911.00418/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":"2026-07-05T01:16:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bAGK+jovTLqoAVfTLHuXjwfhz0A6z2amIN26Eyq++54yv6mYBd4YMkYCX1KVAmnUZXDPcHyj5FrDLBftZvx4DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T13:04:05.865763Z"},"content_sha256":"a97e45b2a00c63b82f2ec2e16877ab7279a066d35225ac9084b45c3492bc87c9","schema_version":"1.0","event_id":"sha256:a97e45b2a00c63b82f2ec2e16877ab7279a066d35225ac9084b45c3492bc87c9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/bundle.json","state_url":"https://pith.science/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/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":"2026-07-27T13:04:05Z","links":{"resolver":"https://pith.science/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2","bundle":"https://pith.science/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/bundle.json","state":"https://pith.science/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RF3MEPHHGNGCLCQ7FD25FPEHP2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:RF3MEPHHGNGCLCQ7FD25FPEHP2","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":"4a5b8a5dc043ac64d4b79da716a30ef5af97743fb1f0109c6eb83cbed594d367","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-01T15:14:06Z","title_canon_sha256":"afd9682d905afcb8da4b6b1f0cb9d8b3d5b71cb71ccd5eaad9f31fe9638877ab"},"schema_version":"1.0","source":{"id":"1911.00418","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00418","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00418v2","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00418","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_12","alias_value":"RF3MEPHHGNGC","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_16","alias_value":"RF3MEPHHGNGCLCQ7","created_at":"2026-07-05T01:16:41Z"},{"alias_kind":"pith_short_8","alias_value":"RF3MEPHH","created_at":"2026-07-05T01:16:41Z"}],"graph_snapshots":[{"event_id":"sha256:a97e45b2a00c63b82f2ec2e16877ab7279a066d35225ac9084b45c3492bc87c9","target":"graph","created_at":"2026-07-05T01:16:41Z","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/1911.00418/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid adoption of machine learning systems in sensitive applications, there is an increasing need to make black-box models explainable. Often we want to identify an influential group of training samples in a particular test prediction for a given machine learning model. Existing influence functions tackle this problem by using first-order approximations of the effect of removing a sample from the training set on model parameters. To compute the influence of a group of training samples (rather than an individual point) in model predictions, the change in optimal model parameters after ","authors_text":"Samyadeep Basu, Soheil Feizi, Xuchen You","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-01T15:14:06Z","title":"On Second-Order Group Influence Functions for Black-Box Predictions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00418","kind":"arxiv","version":2},"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":"sha256:47c21c4e20ac5642735bbc18b6524034efb98e69558ea7785a4979367b87b2bd","target":"record","created_at":"2026-07-05T01:16:41Z","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":"4a5b8a5dc043ac64d4b79da716a30ef5af97743fb1f0109c6eb83cbed594d367","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-01T15:14:06Z","title_canon_sha256":"afd9682d905afcb8da4b6b1f0cb9d8b3d5b71cb71ccd5eaad9f31fe9638877ab"},"schema_version":"1.0","source":{"id":"1911.00418","kind":"arxiv","version":2}},"canonical_sha256":"8976c23ce7334c258a1f28f5d2bc877e8fde18fc9181e1b1f736d3ef86ea37a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8976c23ce7334c258a1f28f5d2bc877e8fde18fc9181e1b1f736d3ef86ea37a1","first_computed_at":"2026-07-05T01:16:41.594048Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:16:41.594048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O83dwSjbWrdQnrKkpDLrlVwScDlN3T7KtbIIK1kTW/BNKT5M2PIERTAwjNfYp0VfbMhOErPZmDgcHJNISjtIAw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:16:41.594457Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.00418","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47c21c4e20ac5642735bbc18b6524034efb98e69558ea7785a4979367b87b2bd","sha256:a97e45b2a00c63b82f2ec2e16877ab7279a066d35225ac9084b45c3492bc87c9"],"state_sha256":"8fa0b108f6f86147da03b7cfe91cab9db01b7832db766ec15ccc4aa9512caa43"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GvWTGPC/gAN4AskuhkqSV27xwV6TjrxB91YMHdPRu2uTIAYTK5CjrgxY/KEHP9lCnLuanzDLmyt2avRLsocCAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T13:04:05.868869Z","bundle_sha256":"1446e5cbfc14786a785352b1baa00be235e04aec5961a6a11218386324b7b4b7"}}