{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:JRU4USWXIAT6FQOZISU7CADHSR","short_pith_number":"pith:JRU4USWX","canonical_record":{"source":{"id":"2210.03080","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T17:36:00Z","cross_cats_sorted":[],"title_canon_sha256":"7042cb3cb7516dfb1b9f1313ca373bd4b87a883c89102863e6a659273915ba23","abstract_canon_sha256":"c1abcc6fdb2316d9c9b2a70ad600f1c643210e433e63e12d0773f69f558b5bd5"},"schema_version":"1.0"},"canonical_sha256":"4c69ca4ad74027e2c1d944a9f10067947ea4e67becb12ce916d067127979de4e","source":{"kind":"arxiv","id":"2210.03080","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03080","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03080v1","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03080","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_12","alias_value":"JRU4USWXIAT6","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_16","alias_value":"JRU4USWXIAT6FQOZ","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_8","alias_value":"JRU4USWX","created_at":"2026-07-05T05:04:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:JRU4USWXIAT6FQOZISU7CADHSR","target":"record","payload":{"canonical_record":{"source":{"id":"2210.03080","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T17:36:00Z","cross_cats_sorted":[],"title_canon_sha256":"7042cb3cb7516dfb1b9f1313ca373bd4b87a883c89102863e6a659273915ba23","abstract_canon_sha256":"c1abcc6fdb2316d9c9b2a70ad600f1c643210e433e63e12d0773f69f558b5bd5"},"schema_version":"1.0"},"canonical_sha256":"4c69ca4ad74027e2c1d944a9f10067947ea4e67becb12ce916d067127979de4e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:04:07.600223Z","signature_b64":"op64hVwoAKbCoQinfuDKVpSAdaAPDjl0PWJ3PaBii0x0dbnk6dlYG9T9QwiK7mJZgdz3Xy40MvOctRxUmPVgBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c69ca4ad74027e2c1d944a9f10067947ea4e67becb12ce916d067127979de4e","last_reissued_at":"2026-07-05T05:04:07.599390Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:04:07.599390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.03080","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":"2026-07-05T05:04:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N6uSkV93Szwd4+VCuPs30v2EopwT0xxnCDf0NFVmh/m2opLvSi6zy+Hioi03GVnKMYjrweGewq+g2Pdd6ORsAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:03:37.785643Z"},"content_sha256":"6a7c1325131f55bcdbbf726dda3d920b2467708b342e7612e8d2febfc91db9ed","schema_version":"1.0","event_id":"sha256:6a7c1325131f55bcdbbf726dda3d920b2467708b342e7612e8d2febfc91db9ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:JRU4USWXIAT6FQOZISU7CADHSR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Verbal Deception Detection using Transformers","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bennett Kleinberg, Felix Soldner, Loukas Ilias","submitted_at":"2022-10-06T17:36:00Z","abstract_excerpt":"People are regularly confronted with potentially deceptive statements (e.g., fake news, misleading product reviews, or lies about activities). Only few works on automated text-based deception detection have exploited the potential of deep learning approaches. A critique of deep-learning methods is their lack of interpretability, preventing us from understanding the underlying (linguistic) mechanisms involved in deception. However, recent advancements have made it possible to explain some aspects of such models. This paper proposes and evaluates six deep-learning models, including combinations "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03080","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/2210.03080/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":"2026-07-05T05:04:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IcYzWdZ3BpqM+5X0+EBqLFKYHonTrDDp7yPLvGepCnAUM06zUAlHwzrYj/pSx2KswTNDBN/UkaOJaGWJh5vEAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T22:03:37.786220Z"},"content_sha256":"435fbe7a2e56c2c033539788e9bf2977dde4abdcbe50486d013b88ae41180339","schema_version":"1.0","event_id":"sha256:435fbe7a2e56c2c033539788e9bf2977dde4abdcbe50486d013b88ae41180339"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JRU4USWXIAT6FQOZISU7CADHSR/bundle.json","state_url":"https://pith.science/pith/JRU4USWXIAT6FQOZISU7CADHSR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JRU4USWXIAT6FQOZISU7CADHSR/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":"2026-08-08T22:03:37Z","links":{"resolver":"https://pith.science/pith/JRU4USWXIAT6FQOZISU7CADHSR","bundle":"https://pith.science/pith/JRU4USWXIAT6FQOZISU7CADHSR/bundle.json","state":"https://pith.science/pith/JRU4USWXIAT6FQOZISU7CADHSR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JRU4USWXIAT6FQOZISU7CADHSR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:JRU4USWXIAT6FQOZISU7CADHSR","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":"c1abcc6fdb2316d9c9b2a70ad600f1c643210e433e63e12d0773f69f558b5bd5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T17:36:00Z","title_canon_sha256":"7042cb3cb7516dfb1b9f1313ca373bd4b87a883c89102863e6a659273915ba23"},"schema_version":"1.0","source":{"id":"2210.03080","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03080","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03080v1","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03080","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_12","alias_value":"JRU4USWXIAT6","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_16","alias_value":"JRU4USWXIAT6FQOZ","created_at":"2026-07-05T05:04:07Z"},{"alias_kind":"pith_short_8","alias_value":"JRU4USWX","created_at":"2026-07-05T05:04:07Z"}],"graph_snapshots":[{"event_id":"sha256:435fbe7a2e56c2c033539788e9bf2977dde4abdcbe50486d013b88ae41180339","target":"graph","created_at":"2026-07-05T05:04:07Z","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/2210.03080/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"People are regularly confronted with potentially deceptive statements (e.g., fake news, misleading product reviews, or lies about activities). Only few works on automated text-based deception detection have exploited the potential of deep learning approaches. A critique of deep-learning methods is their lack of interpretability, preventing us from understanding the underlying (linguistic) mechanisms involved in deception. However, recent advancements have made it possible to explain some aspects of such models. This paper proposes and evaluates six deep-learning models, including combinations ","authors_text":"Bennett Kleinberg, Felix Soldner, Loukas Ilias","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T17:36:00Z","title":"Explainable Verbal Deception Detection using Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03080","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":"sha256:6a7c1325131f55bcdbbf726dda3d920b2467708b342e7612e8d2febfc91db9ed","target":"record","created_at":"2026-07-05T05:04:07Z","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":"c1abcc6fdb2316d9c9b2a70ad600f1c643210e433e63e12d0773f69f558b5bd5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T17:36:00Z","title_canon_sha256":"7042cb3cb7516dfb1b9f1313ca373bd4b87a883c89102863e6a659273915ba23"},"schema_version":"1.0","source":{"id":"2210.03080","kind":"arxiv","version":1}},"canonical_sha256":"4c69ca4ad74027e2c1d944a9f10067947ea4e67becb12ce916d067127979de4e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c69ca4ad74027e2c1d944a9f10067947ea4e67becb12ce916d067127979de4e","first_computed_at":"2026-07-05T05:04:07.599390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:04:07.599390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"op64hVwoAKbCoQinfuDKVpSAdaAPDjl0PWJ3PaBii0x0dbnk6dlYG9T9QwiK7mJZgdz3Xy40MvOctRxUmPVgBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:04:07.600223Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.03080","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a7c1325131f55bcdbbf726dda3d920b2467708b342e7612e8d2febfc91db9ed","sha256:435fbe7a2e56c2c033539788e9bf2977dde4abdcbe50486d013b88ae41180339"],"state_sha256":"4e3f37718585c5a2924de860b43c987502d40107f87e18f9f78b5f01f5d22b3b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2hXoAaKWJ5eiZ0LWBwdfm7y1eWfQh5EA/wInDONCQN01/qNY5mLDTmGYtbij0pM1UuglfAcEglrNZlPoCtsODw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T22:03:37.789937Z","bundle_sha256":"d88226462cfe18e7e082a0760a1096aaa30cbe4967f351636d52239391a6f582"}}