{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:X24ZBYOYI7DOS5UQTTOW3TA6AQ","short_pith_number":"pith:X24ZBYOY","canonical_record":{"source":{"id":"2203.07861","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-14T15:22:20Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"97e0928c57c60955a931ea15ccad148b46a76dc07e34ce8e13e591f31fb8498a","abstract_canon_sha256":"5fe467c6c0d88de5fdf792b5ce7437c8a58d8b742456fbe347ab92273cb45e3c"},"schema_version":"1.0"},"canonical_sha256":"beb990e1d847c6e976909cdd6dcc1e04070cee4e8dd8c9b84a394f3962e83bbc","source":{"kind":"arxiv","id":"2203.07861","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.07861","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"arxiv_version","alias_value":"2203.07861v3","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.07861","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_12","alias_value":"X24ZBYOYI7DO","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_16","alias_value":"X24ZBYOYI7DOS5UQ","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_8","alias_value":"X24ZBYOY","created_at":"2026-07-05T11:34:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:X24ZBYOYI7DOS5UQTTOW3TA6AQ","target":"record","payload":{"canonical_record":{"source":{"id":"2203.07861","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-14T15:22:20Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"97e0928c57c60955a931ea15ccad148b46a76dc07e34ce8e13e591f31fb8498a","abstract_canon_sha256":"5fe467c6c0d88de5fdf792b5ce7437c8a58d8b742456fbe347ab92273cb45e3c"},"schema_version":"1.0"},"canonical_sha256":"beb990e1d847c6e976909cdd6dcc1e04070cee4e8dd8c9b84a394f3962e83bbc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:34:39.206800Z","signature_b64":"PcN4fqLbikZtp88/1kI8etQvU+WcJ1bjiA7xipxYANO8YNxSInwtL5XbPwiwa2V4T0HLxL2ZVqvY0U6WaKLDDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"beb990e1d847c6e976909cdd6dcc1e04070cee4e8dd8c9b84a394f3962e83bbc","last_reissued_at":"2026-07-05T11:34:39.206194Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:34:39.206194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.07861","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:34:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bmMeJaBuljnMYSmRnEGI8kgI+LLHoLTlKZkeCGKTVy61PpdY7pN+fVMQQ+0lf13ZrWjll3TbifW4Ckc/nnnhAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:18:43.407754Z"},"content_sha256":"668c63e8aeab88cede20b34bce4fe1c77e9931c5fd8b456c30326bd565835d7e","schema_version":"1.0","event_id":"sha256:668c63e8aeab88cede20b34bce4fe1c77e9931c5fd8b456c30326bd565835d7e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:X24ZBYOYI7DOS5UQTTOW3TA6AQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bjoern Eskofier, Christoffer Loeffler, Christopher Mutschler, Dario Zanca, Lukas Schmidt, Wei-Cheng Lai","submitted_at":"2022-03-14T15:22:20Z","abstract_excerpt":"The correct interpretation of convolutional models is a hard problem for time series data. While saliency methods promise visual validation of predictions for image and language processing, they fall short when applied to time series. These tend to be less intuitive and represent highly diverse data, such as the tool-use time series dataset. Furthermore, saliency methods often generate varied, conflicting explanations, complicating the reliability of these methods. Consequently, a rigorous objective assessment is necessary to establish trust in them. This paper investigates saliency methods on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.07861","kind":"arxiv","version":3},"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/2203.07861/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":"2026-07-05T11:34:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Phzcpj0XLAbcFrEh7oiZVmfBW0/VtpcEpC/SzzDBGCq0od8Pqiao/nOSSu9006p961g3o48lTktmg67kfcPaAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:18:43.408325Z"},"content_sha256":"7df616651a9b21fe51b26b34093e20b553a82fc108506dc6c634a1a6c406c676","schema_version":"1.0","event_id":"sha256:7df616651a9b21fe51b26b34093e20b553a82fc108506dc6c634a1a6c406c676"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/bundle.json","state_url":"https://pith.science/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/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":"2026-08-08T19:18:43Z","links":{"resolver":"https://pith.science/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ","bundle":"https://pith.science/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/bundle.json","state":"https://pith.science/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X24ZBYOYI7DOS5UQTTOW3TA6AQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:X24ZBYOYI7DOS5UQTTOW3TA6AQ","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":"5fe467c6c0d88de5fdf792b5ce7437c8a58d8b742456fbe347ab92273cb45e3c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-14T15:22:20Z","title_canon_sha256":"97e0928c57c60955a931ea15ccad148b46a76dc07e34ce8e13e591f31fb8498a"},"schema_version":"1.0","source":{"id":"2203.07861","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.07861","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"arxiv_version","alias_value":"2203.07861v3","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.07861","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_12","alias_value":"X24ZBYOYI7DO","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_16","alias_value":"X24ZBYOYI7DOS5UQ","created_at":"2026-07-05T11:34:39Z"},{"alias_kind":"pith_short_8","alias_value":"X24ZBYOY","created_at":"2026-07-05T11:34:39Z"}],"graph_snapshots":[{"event_id":"sha256:7df616651a9b21fe51b26b34093e20b553a82fc108506dc6c634a1a6c406c676","target":"graph","created_at":"2026-07-05T11:34:39Z","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/2203.07861/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The correct interpretation of convolutional models is a hard problem for time series data. While saliency methods promise visual validation of predictions for image and language processing, they fall short when applied to time series. These tend to be less intuitive and represent highly diverse data, such as the tool-use time series dataset. Furthermore, saliency methods often generate varied, conflicting explanations, complicating the reliability of these methods. Consequently, a rigorous objective assessment is necessary to establish trust in them. This paper investigates saliency methods on","authors_text":"Bjoern Eskofier, Christoffer Loeffler, Christopher Mutschler, Dario Zanca, Lukas Schmidt, Wei-Cheng Lai","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-14T15:22:20Z","title":"Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.07861","kind":"arxiv","version":3},"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":"sha256:668c63e8aeab88cede20b34bce4fe1c77e9931c5fd8b456c30326bd565835d7e","target":"record","created_at":"2026-07-05T11:34:39Z","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":"5fe467c6c0d88de5fdf792b5ce7437c8a58d8b742456fbe347ab92273cb45e3c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-14T15:22:20Z","title_canon_sha256":"97e0928c57c60955a931ea15ccad148b46a76dc07e34ce8e13e591f31fb8498a"},"schema_version":"1.0","source":{"id":"2203.07861","kind":"arxiv","version":3}},"canonical_sha256":"beb990e1d847c6e976909cdd6dcc1e04070cee4e8dd8c9b84a394f3962e83bbc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"beb990e1d847c6e976909cdd6dcc1e04070cee4e8dd8c9b84a394f3962e83bbc","first_computed_at":"2026-07-05T11:34:39.206194Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:39.206194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PcN4fqLbikZtp88/1kI8etQvU+WcJ1bjiA7xipxYANO8YNxSInwtL5XbPwiwa2V4T0HLxL2ZVqvY0U6WaKLDDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:39.206800Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.07861","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:668c63e8aeab88cede20b34bce4fe1c77e9931c5fd8b456c30326bd565835d7e","sha256:7df616651a9b21fe51b26b34093e20b553a82fc108506dc6c634a1a6c406c676"],"state_sha256":"c30b3f87055cf9e6a3327466e7b6febf4c5d3ee481eba49a8d9e3e363d4b944e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"meRyGzgh2jmYmtwqAYxZSd+IIlcY9PVn7UZLvQVuFh1hdbyAOo8L1ZwuBDSb1PcAdFbl28DucPYC2UyCqHcQDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T19:18:43.413087Z","bundle_sha256":"6f66d8ef065dfd2d4de543f303069169ec48ae604ac77ac34ec761dd59818f5e"}}