{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:4TTM72N3WFZK2TDKLZ57DFGFQF","short_pith_number":"pith:4TTM72N3","canonical_record":{"source":{"id":"2204.10176","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-16T05:13:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f12f2a1fef7e516a96995e93a75864733abc9add3c0b0d4b909250f9edb5d05d","abstract_canon_sha256":"34c161446671086f71803263d72f13480cd6ed0af3eca3818430caabbcf7d9b2"},"schema_version":"1.0"},"canonical_sha256":"e4e6cfe9bbb172ad4c6a5e7bf194c58165922238926baee7409d09313159d926","source":{"kind":"arxiv","id":"2204.10176","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.10176","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"arxiv_version","alias_value":"2204.10176v1","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.10176","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_12","alias_value":"4TTM72N3WFZK","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_16","alias_value":"4TTM72N3WFZK2TDK","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_8","alias_value":"4TTM72N3","created_at":"2026-07-05T04:16:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:4TTM72N3WFZK2TDKLZ57DFGFQF","target":"record","payload":{"canonical_record":{"source":{"id":"2204.10176","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-16T05:13:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f12f2a1fef7e516a96995e93a75864733abc9add3c0b0d4b909250f9edb5d05d","abstract_canon_sha256":"34c161446671086f71803263d72f13480cd6ed0af3eca3818430caabbcf7d9b2"},"schema_version":"1.0"},"canonical_sha256":"e4e6cfe9bbb172ad4c6a5e7bf194c58165922238926baee7409d09313159d926","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:16:47.529425Z","signature_b64":"Z9G+rVb4hs731kkp4iCQvcJk0WiEYuRocYkFk4PlGOJAynymEFHz2nfpj8ssIMwCzC9la1TLtDwsx//EWvt2BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e4e6cfe9bbb172ad4c6a5e7bf194c58165922238926baee7409d09313159d926","last_reissued_at":"2026-07-05T04:16:47.529007Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:16:47.529007Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2204.10176","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":"2026-07-05T04:16:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KOxBRuVgvDw0FCH/q4XtFPcm4OdhfvQN3q8uAByVzkCwGJLEg+xfeAMqrbg+XiQ5sjySyEe6gIjBj3XrBpHMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:53:48.024726Z"},"content_sha256":"0ffb45ebf31962582a880ed782c2a7bf05e99c4b83af058702cc767310a34de3","schema_version":"1.0","event_id":"sha256:0ffb45ebf31962582a880ed782c2a7bf05e99c4b83af058702cc767310a34de3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:4TTM72N3WFZK2TDKLZ57DFGFQF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Probing Script Knowledge from Pre-Trained Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Lifu Huang, Mo Yu, Xingyu Zhang, Zijian Jin","submitted_at":"2022-04-16T05:13:39Z","abstract_excerpt":"Script knowledge is critical for humans to understand the broad daily tasks and routine activities in the world. Recently researchers have explored the large-scale pre-trained language models (PLMs) to perform various script related tasks, such as story generation, temporal ordering of event, future event prediction and so on. However, it's still not well studied in terms of how well the PLMs capture the script knowledge. To answer this question, we design three probing tasks: inclusive sub-event selection, starting sub-event selection and temporal ordering to investigate the capabilities of P"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.10176","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/2204.10176/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":"2026-07-05T04:16:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vs0CXdqe1wpXvpdzqRm3OatFKD9AwE3wMbpeTZDFWsCv9GwtbPkzG9O2JKIA3iu8pUX6CVxQ8AMcND8uLZcaBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:53:48.025301Z"},"content_sha256":"0a5a8847312b9e58e99b459aef3f3e0d5dd7f9bb8f15616120fe01d89b1250fa","schema_version":"1.0","event_id":"sha256:0a5a8847312b9e58e99b459aef3f3e0d5dd7f9bb8f15616120fe01d89b1250fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/bundle.json","state_url":"https://pith.science/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/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":"2026-08-09T17:53:48Z","links":{"resolver":"https://pith.science/pith/4TTM72N3WFZK2TDKLZ57DFGFQF","bundle":"https://pith.science/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/bundle.json","state":"https://pith.science/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4TTM72N3WFZK2TDKLZ57DFGFQF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:4TTM72N3WFZK2TDKLZ57DFGFQF","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":"34c161446671086f71803263d72f13480cd6ed0af3eca3818430caabbcf7d9b2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-16T05:13:39Z","title_canon_sha256":"f12f2a1fef7e516a96995e93a75864733abc9add3c0b0d4b909250f9edb5d05d"},"schema_version":"1.0","source":{"id":"2204.10176","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.10176","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"arxiv_version","alias_value":"2204.10176v1","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.10176","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_12","alias_value":"4TTM72N3WFZK","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_16","alias_value":"4TTM72N3WFZK2TDK","created_at":"2026-07-05T04:16:47Z"},{"alias_kind":"pith_short_8","alias_value":"4TTM72N3","created_at":"2026-07-05T04:16:47Z"}],"graph_snapshots":[{"event_id":"sha256:0a5a8847312b9e58e99b459aef3f3e0d5dd7f9bb8f15616120fe01d89b1250fa","target":"graph","created_at":"2026-07-05T04:16:47Z","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/2204.10176/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Script knowledge is critical for humans to understand the broad daily tasks and routine activities in the world. Recently researchers have explored the large-scale pre-trained language models (PLMs) to perform various script related tasks, such as story generation, temporal ordering of event, future event prediction and so on. However, it's still not well studied in terms of how well the PLMs capture the script knowledge. To answer this question, we design three probing tasks: inclusive sub-event selection, starting sub-event selection and temporal ordering to investigate the capabilities of P","authors_text":"Lifu Huang, Mo Yu, Xingyu Zhang, Zijian Jin","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-16T05:13:39Z","title":"Probing Script Knowledge from Pre-Trained Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.10176","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":"sha256:0ffb45ebf31962582a880ed782c2a7bf05e99c4b83af058702cc767310a34de3","target":"record","created_at":"2026-07-05T04:16:47Z","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":"34c161446671086f71803263d72f13480cd6ed0af3eca3818430caabbcf7d9b2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-04-16T05:13:39Z","title_canon_sha256":"f12f2a1fef7e516a96995e93a75864733abc9add3c0b0d4b909250f9edb5d05d"},"schema_version":"1.0","source":{"id":"2204.10176","kind":"arxiv","version":1}},"canonical_sha256":"e4e6cfe9bbb172ad4c6a5e7bf194c58165922238926baee7409d09313159d926","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e4e6cfe9bbb172ad4c6a5e7bf194c58165922238926baee7409d09313159d926","first_computed_at":"2026-07-05T04:16:47.529007Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:16:47.529007Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z9G+rVb4hs731kkp4iCQvcJk0WiEYuRocYkFk4PlGOJAynymEFHz2nfpj8ssIMwCzC9la1TLtDwsx//EWvt2BA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:16:47.529425Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.10176","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ffb45ebf31962582a880ed782c2a7bf05e99c4b83af058702cc767310a34de3","sha256:0a5a8847312b9e58e99b459aef3f3e0d5dd7f9bb8f15616120fe01d89b1250fa"],"state_sha256":"0a3eba0297236f616debc28d38cc9911560634c5c043e7005ca1b949eb9c8e42"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mxJ70aBAk09Foscj1Z2CpSKS9ZdyAv2F78YKIrkiodfX2bgx2GAyLGs44VQMaVfBldabUnpE47a7a7UR3bsjDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T17:53:48.029724Z","bundle_sha256":"7fcce7abb44550ff8cdafdc7f997a25de020d93dd8f6e2f426e015dc30a4719a"}}