{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:R77CAC2QRSBJBAJT4B6Y3DWHQI","short_pith_number":"pith:R77CAC2Q","canonical_record":{"source":{"id":"1911.00650","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-02T04:52:00Z","cross_cats_sorted":[],"title_canon_sha256":"126e4a78ba8628ad69bb28ec3c66e2683ad260ad5279761faec4c57eed61e85b","abstract_canon_sha256":"18fa690a319e60676abdb46c288ecc5815505e6a214915d90f44f66e7d6cd295"},"schema_version":"1.0"},"canonical_sha256":"8ffe200b508c82908133e07d8d8ec78223ca34ec8faf1a67c6ee3599358597a9","source":{"kind":"arxiv","id":"1911.00650","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00650","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00650v2","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00650","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_12","alias_value":"R77CAC2QRSBJ","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_16","alias_value":"R77CAC2QRSBJBAJT","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_8","alias_value":"R77CAC2Q","created_at":"2026-07-05T01:01:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:R77CAC2QRSBJBAJT4B6Y3DWHQI","target":"record","payload":{"canonical_record":{"source":{"id":"1911.00650","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-02T04:52:00Z","cross_cats_sorted":[],"title_canon_sha256":"126e4a78ba8628ad69bb28ec3c66e2683ad260ad5279761faec4c57eed61e85b","abstract_canon_sha256":"18fa690a319e60676abdb46c288ecc5815505e6a214915d90f44f66e7d6cd295"},"schema_version":"1.0"},"canonical_sha256":"8ffe200b508c82908133e07d8d8ec78223ca34ec8faf1a67c6ee3599358597a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:01:21.343417Z","signature_b64":"mcwRyEnSLK8NejwshhxZWyDzY7PdylMCJkjKUiemDA9rlqKmRvYGmMflnyE8D2buiTAt2Ps4+zu0Ux34JFy7DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8ffe200b508c82908133e07d8d8ec78223ca34ec8faf1a67c6ee3599358597a9","last_reissued_at":"2026-07-05T01:01:21.342965Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:01:21.342965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.00650","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":"2026-07-05T01:01:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y/Ky94ihd0qh7oQFrXOIRKZHC7xAL7QRdZwyBFr69gFuj/mdYeO8DbOfrzZnYVBjH6czE8crrS1bUqCuSoUHAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:04:28.128088Z"},"content_sha256":"b35b204c59b9f1f56b9e34434698f17c58a2e71a760d0e6d4548c2cd6ec9bbdc","schema_version":"1.0","event_id":"sha256:b35b204c59b9f1f56b9e34434698f17c58a2e71a760d0e6d4548c2cd6ec9bbdc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:R77CAC2QRSBJBAJT4B6Y3DWHQI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Detection of Generated Text is Easiest when Humans are Fooled","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chris Callison-Burch, Daniel Duckworth, Daphne Ippolito, Douglas Eck","submitted_at":"2019-11-02T04:52:00Z","abstract_excerpt":"Recent advancements in neural language modelling make it possible to rapidly generate vast amounts of human-sounding text. The capabilities of humans and automatic discriminators to detect machine-generated text have been a large source of research interest, but humans and machines rely on different cues to make their decisions. Here, we perform careful benchmarking and analysis of three popular sampling-based decoding strategies---top-$k$, nucleus sampling, and untruncated random sampling---and show that improvements in decoding methods have primarily optimized for fooling humans. This comes "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00650","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/1911.00650/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":"2026-07-05T01:01:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UyM3kKyF/4uAD2A+/fb2xuguhFoXKmMabdpMuHD94aHiLPDLj02h7OMNCrrPYfdCCKZ2nCvqIMBJg5pLsUJ3Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:04:28.128578Z"},"content_sha256":"e167529ca5315cf1657d65eb0855c63b0ebe91e99f0e620f20de987a4328d278","schema_version":"1.0","event_id":"sha256:e167529ca5315cf1657d65eb0855c63b0ebe91e99f0e620f20de987a4328d278"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/bundle.json","state_url":"https://pith.science/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/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":"2026-08-04T14:04:28Z","links":{"resolver":"https://pith.science/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI","bundle":"https://pith.science/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/bundle.json","state":"https://pith.science/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R77CAC2QRSBJBAJT4B6Y3DWHQI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:R77CAC2QRSBJBAJT4B6Y3DWHQI","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":"18fa690a319e60676abdb46c288ecc5815505e6a214915d90f44f66e7d6cd295","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-02T04:52:00Z","title_canon_sha256":"126e4a78ba8628ad69bb28ec3c66e2683ad260ad5279761faec4c57eed61e85b"},"schema_version":"1.0","source":{"id":"1911.00650","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.00650","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"arxiv_version","alias_value":"1911.00650v2","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.00650","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_12","alias_value":"R77CAC2QRSBJ","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_16","alias_value":"R77CAC2QRSBJBAJT","created_at":"2026-07-05T01:01:21Z"},{"alias_kind":"pith_short_8","alias_value":"R77CAC2Q","created_at":"2026-07-05T01:01:21Z"}],"graph_snapshots":[{"event_id":"sha256:e167529ca5315cf1657d65eb0855c63b0ebe91e99f0e620f20de987a4328d278","target":"graph","created_at":"2026-07-05T01:01:21Z","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/1911.00650/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in neural language modelling make it possible to rapidly generate vast amounts of human-sounding text. The capabilities of humans and automatic discriminators to detect machine-generated text have been a large source of research interest, but humans and machines rely on different cues to make their decisions. Here, we perform careful benchmarking and analysis of three popular sampling-based decoding strategies---top-$k$, nucleus sampling, and untruncated random sampling---and show that improvements in decoding methods have primarily optimized for fooling humans. This comes ","authors_text":"Chris Callison-Burch, Daniel Duckworth, Daphne Ippolito, Douglas Eck","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-02T04:52:00Z","title":"Automatic Detection of Generated Text is Easiest when Humans are Fooled"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.00650","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:b35b204c59b9f1f56b9e34434698f17c58a2e71a760d0e6d4548c2cd6ec9bbdc","target":"record","created_at":"2026-07-05T01:01:21Z","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":"18fa690a319e60676abdb46c288ecc5815505e6a214915d90f44f66e7d6cd295","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-02T04:52:00Z","title_canon_sha256":"126e4a78ba8628ad69bb28ec3c66e2683ad260ad5279761faec4c57eed61e85b"},"schema_version":"1.0","source":{"id":"1911.00650","kind":"arxiv","version":2}},"canonical_sha256":"8ffe200b508c82908133e07d8d8ec78223ca34ec8faf1a67c6ee3599358597a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8ffe200b508c82908133e07d8d8ec78223ca34ec8faf1a67c6ee3599358597a9","first_computed_at":"2026-07-05T01:01:21.342965Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:01:21.342965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mcwRyEnSLK8NejwshhxZWyDzY7PdylMCJkjKUiemDA9rlqKmRvYGmMflnyE8D2buiTAt2Ps4+zu0Ux34JFy7DA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:01:21.343417Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.00650","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b35b204c59b9f1f56b9e34434698f17c58a2e71a760d0e6d4548c2cd6ec9bbdc","sha256:e167529ca5315cf1657d65eb0855c63b0ebe91e99f0e620f20de987a4328d278"],"state_sha256":"52f93532c8de6005bc77d41abaee5187b3d8332efae77e2c2a96a0d5a6a40930"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rgiV++tB8YUmjypgiYS/aeXZh512Qx+fjpZs5CBAfxWLAkO72Nq8Mb7Y7uFyfgQuRtmJfJ8B9tP5Oc4z7Z0qBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T14:04:28.132189Z","bundle_sha256":"6542ee43920e39f26ee86bac460d4ae6327fb93c21d56f08eb1dfbaf9b7bd0ce"}}