{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:J7ACJBQCTMZFW7YABY3AXZNG3V","short_pith_number":"pith:J7ACJBQC","canonical_record":{"source":{"id":"2106.12894","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-10T08:42:50Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"3d708c7bcfff4d5d92cf3314ed53ef273ea017f62229752a3ec3f177cbe2933d","abstract_canon_sha256":"580009074d6caefeb145f95b80d190e90580a7157556cb1f797ee67bd0a4ab0e"},"schema_version":"1.0"},"canonical_sha256":"4fc02486029b325b7f000e360be5a6dd74cf8be5ea6eb214827df9ca1ddeb1a1","source":{"kind":"arxiv","id":"2106.12894","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.12894","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"arxiv_version","alias_value":"2106.12894v2","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.12894","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_12","alias_value":"J7ACJBQCTMZF","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_16","alias_value":"J7ACJBQCTMZFW7YA","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_8","alias_value":"J7ACJBQC","created_at":"2026-07-05T03:32:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:J7ACJBQCTMZFW7YABY3AXZNG3V","target":"record","payload":{"canonical_record":{"source":{"id":"2106.12894","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-10T08:42:50Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"3d708c7bcfff4d5d92cf3314ed53ef273ea017f62229752a3ec3f177cbe2933d","abstract_canon_sha256":"580009074d6caefeb145f95b80d190e90580a7157556cb1f797ee67bd0a4ab0e"},"schema_version":"1.0"},"canonical_sha256":"4fc02486029b325b7f000e360be5a6dd74cf8be5ea6eb214827df9ca1ddeb1a1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:32:06.027973Z","signature_b64":"ZqXSOsvDGir1F7xshlAdMXEZkc01c+SM1dA2bWBFLFr64HfEulpprxyNNznj8at8eJ2WbyeRxoE91icr0/K2BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4fc02486029b325b7f000e360be5a6dd74cf8be5ea6eb214827df9ca1ddeb1a1","last_reissued_at":"2026-07-05T03:32:06.026513Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:32:06.026513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.12894","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":"2026-07-05T03:32:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M0kLoZn9jbsxp4D7SUe/1y66P4eqR4bTsWylykcdf52W0hQ/kLeu/iII8LYkW49aqqvgEnOBFIsjIcmCDo9CDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:01:08.128366Z"},"content_sha256":"796d8a36ccf9aed5dbcef263c78e4403ea6fb58d2d046612087600cc54a4d4db","schema_version":"1.0","event_id":"sha256:796d8a36ccf9aed5dbcef263c78e4403ea6fb58d2d046612087600cc54a4d4db"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:J7ACJBQCTMZFW7YABY3AXZNG3V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"InFlow: Robust outlier detection utilizing Normalizing Flows","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Michael Bussmann, Michael Hecht, Nico Hoffmann, Nishant Kumar, Pia Hanfeld, Stefan Gumhold","submitted_at":"2021-06-10T08:42:50Z","abstract_excerpt":"Normalizing flows are prominent deep generative models that provide tractable probability distributions and efficient density estimation. However, they are well known to fail while detecting Out-of-Distribution (OOD) inputs as they directly encode the local features of the input representations in their latent space. In this paper, we solve this overconfidence issue of normalizing flows by demonstrating that flows, if extended by an attention mechanism, can reliably detect outliers including adversarial attacks. Our approach does not require outlier data for training and we showcase the effici"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.12894","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/2106.12894/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":"2026-07-05T03:32:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c8R21zu107BFtI0QkHyA+S3iDRStcPXNKnr0hKv5kfut6ijA81M3KTPTjMs7orShTuAk6EPjf2TJjFzXJp3yBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:01:08.129263Z"},"content_sha256":"c1e7083fd154440a3a2776e5afe51a36455eb41e154aa76db47737fbd5add2fe","schema_version":"1.0","event_id":"sha256:c1e7083fd154440a3a2776e5afe51a36455eb41e154aa76db47737fbd5add2fe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/bundle.json","state_url":"https://pith.science/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/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":"2026-08-05T03:01:08Z","links":{"resolver":"https://pith.science/pith/J7ACJBQCTMZFW7YABY3AXZNG3V","bundle":"https://pith.science/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/bundle.json","state":"https://pith.science/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J7ACJBQCTMZFW7YABY3AXZNG3V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:J7ACJBQCTMZFW7YABY3AXZNG3V","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":"580009074d6caefeb145f95b80d190e90580a7157556cb1f797ee67bd0a4ab0e","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-10T08:42:50Z","title_canon_sha256":"3d708c7bcfff4d5d92cf3314ed53ef273ea017f62229752a3ec3f177cbe2933d"},"schema_version":"1.0","source":{"id":"2106.12894","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.12894","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"arxiv_version","alias_value":"2106.12894v2","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.12894","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_12","alias_value":"J7ACJBQCTMZF","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_16","alias_value":"J7ACJBQCTMZFW7YA","created_at":"2026-07-05T03:32:06Z"},{"alias_kind":"pith_short_8","alias_value":"J7ACJBQC","created_at":"2026-07-05T03:32:06Z"}],"graph_snapshots":[{"event_id":"sha256:c1e7083fd154440a3a2776e5afe51a36455eb41e154aa76db47737fbd5add2fe","target":"graph","created_at":"2026-07-05T03:32:06Z","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/2106.12894/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Normalizing flows are prominent deep generative models that provide tractable probability distributions and efficient density estimation. However, they are well known to fail while detecting Out-of-Distribution (OOD) inputs as they directly encode the local features of the input representations in their latent space. In this paper, we solve this overconfidence issue of normalizing flows by demonstrating that flows, if extended by an attention mechanism, can reliably detect outliers including adversarial attacks. Our approach does not require outlier data for training and we showcase the effici","authors_text":"Michael Bussmann, Michael Hecht, Nico Hoffmann, Nishant Kumar, Pia Hanfeld, Stefan Gumhold","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-10T08:42:50Z","title":"InFlow: Robust outlier detection utilizing Normalizing Flows"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.12894","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":"sha256:796d8a36ccf9aed5dbcef263c78e4403ea6fb58d2d046612087600cc54a4d4db","target":"record","created_at":"2026-07-05T03:32:06Z","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":"580009074d6caefeb145f95b80d190e90580a7157556cb1f797ee67bd0a4ab0e","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-10T08:42:50Z","title_canon_sha256":"3d708c7bcfff4d5d92cf3314ed53ef273ea017f62229752a3ec3f177cbe2933d"},"schema_version":"1.0","source":{"id":"2106.12894","kind":"arxiv","version":2}},"canonical_sha256":"4fc02486029b325b7f000e360be5a6dd74cf8be5ea6eb214827df9ca1ddeb1a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4fc02486029b325b7f000e360be5a6dd74cf8be5ea6eb214827df9ca1ddeb1a1","first_computed_at":"2026-07-05T03:32:06.026513Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:32:06.026513Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZqXSOsvDGir1F7xshlAdMXEZkc01c+SM1dA2bWBFLFr64HfEulpprxyNNznj8at8eJ2WbyeRxoE91icr0/K2BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:32:06.027973Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.12894","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:796d8a36ccf9aed5dbcef263c78e4403ea6fb58d2d046612087600cc54a4d4db","sha256:c1e7083fd154440a3a2776e5afe51a36455eb41e154aa76db47737fbd5add2fe"],"state_sha256":"9f73cf097a34ead0c28d63a04045f7a56ac06bf6633921f9dbd89c19447a90c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8gxQd0h5rSysvkvsqCF+RGBHQEu3s+J+0IPeemzj0MOK9gpxTgc64HYaPPPICLPc0oUnPwN0IGjg6rCR1zSMAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T03:01:08.135277Z","bundle_sha256":"e99be2f2fca1baaa79fe209cfaf4cb7d33b5569fda0a939b272d842e7e8764f3"}}