{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:Q2ZEBULYIP6YYXXISLU24WL7NN","short_pith_number":"pith:Q2ZEBULY","canonical_record":{"source":{"id":"2209.14500","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-29T01:35:57Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"45d2e08d08d7277cd6f660e9ae8d04ef132abfb3ac75158dbf1f53501b7c9fa1","abstract_canon_sha256":"d80b8dcfe5499abac9db43496c352cb1aaa73b6bc47f53fab3d3fff50644b8aa"},"schema_version":"1.0"},"canonical_sha256":"86b240d17843fd8c5ee892e9ae597f6b426328dbc89eea0f17bc098007b2120b","source":{"kind":"arxiv","id":"2209.14500","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.14500","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2209.14500v2","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.14500","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"Q2ZEBULYIP6Y","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"Q2ZEBULYIP6YYXXI","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"Q2ZEBULY","created_at":"2026-07-05T05:38:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:Q2ZEBULYIP6YYXXISLU24WL7NN","target":"record","payload":{"canonical_record":{"source":{"id":"2209.14500","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-29T01:35:57Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"45d2e08d08d7277cd6f660e9ae8d04ef132abfb3ac75158dbf1f53501b7c9fa1","abstract_canon_sha256":"d80b8dcfe5499abac9db43496c352cb1aaa73b6bc47f53fab3d3fff50644b8aa"},"schema_version":"1.0"},"canonical_sha256":"86b240d17843fd8c5ee892e9ae597f6b426328dbc89eea0f17bc098007b2120b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:38:44.337856Z","signature_b64":"3EzvhCCqJCh0RoNV+hQqssavyXRZdBXYvm4TscuIG96yaBG86uEooRS85MuhnVPinc5HPYQu1XNEDsZDmvylCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"86b240d17843fd8c5ee892e9ae597f6b426328dbc89eea0f17bc098007b2120b","last_reissued_at":"2026-07-05T05:38:44.337396Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:38:44.337396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.14500","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":"2026-07-05T05:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jf0Jhp9TWlDKXeX8H6VAeH+lnlaUT7viE+MqKwZrsyQwF8b2KOcdsPjbZZrOQ3raCPCVs02e0byXZXg52p/VAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:19:20.523364Z"},"content_sha256":"0d047070c88b0e1cf9f19265c23f745823bec27f1d983e0d4d82e81dbcacdf6d","schema_version":"1.0","event_id":"sha256:0d047070c88b0e1cf9f19265c23f745823bec27f1d983e0d4d82e81dbcacdf6d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:Q2ZEBULYIP6YYXXISLU24WL7NN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bidirectional Language Models Are Also Few-shot Learners","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Ajay Patel, Bryan Li, Chris Callison-Burch, Colin Raffel, Mohammad Sadegh Rasooli, Noah Constant","submitted_at":"2022-09-29T01:35:57Z","abstract_excerpt":"Large language models such as GPT-3 (Brown et al., 2020) can perform arbitrary tasks without undergoing fine-tuning after being prompted with only a few labeled examples. An arbitrary task can be reformulated as a natural language prompt, and a language model can be asked to generate the completion, indirectly performing the task in a paradigm known as prompt-based learning. To date, emergent prompt-based learning capabilities have mainly been demonstrated for unidirectional language models. However, bidirectional language models pre-trained on denoising objectives such as masked language mode"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.14500","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/2209.14500/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":"2026-07-05T05:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yIVn3ijr+fBux8oGyk16iI8Ftq7Nx9QC4cSNP13HB8pWv8laRR19wjyOJUFK6bkVfheCVTkPVrawLUWQyVLPBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:19:20.523987Z"},"content_sha256":"821b2559857922a970b0071c0c5b40609a3e60ec45366177b8195495a60eead7","schema_version":"1.0","event_id":"sha256:821b2559857922a970b0071c0c5b40609a3e60ec45366177b8195495a60eead7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/bundle.json","state_url":"https://pith.science/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/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":"2026-08-09T15:19:20Z","links":{"resolver":"https://pith.science/pith/Q2ZEBULYIP6YYXXISLU24WL7NN","bundle":"https://pith.science/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/bundle.json","state":"https://pith.science/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q2ZEBULYIP6YYXXISLU24WL7NN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:Q2ZEBULYIP6YYXXISLU24WL7NN","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":"d80b8dcfe5499abac9db43496c352cb1aaa73b6bc47f53fab3d3fff50644b8aa","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-29T01:35:57Z","title_canon_sha256":"45d2e08d08d7277cd6f660e9ae8d04ef132abfb3ac75158dbf1f53501b7c9fa1"},"schema_version":"1.0","source":{"id":"2209.14500","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.14500","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2209.14500v2","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.14500","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"Q2ZEBULYIP6Y","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"Q2ZEBULYIP6YYXXI","created_at":"2026-07-05T05:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"Q2ZEBULY","created_at":"2026-07-05T05:38:44Z"}],"graph_snapshots":[{"event_id":"sha256:821b2559857922a970b0071c0c5b40609a3e60ec45366177b8195495a60eead7","target":"graph","created_at":"2026-07-05T05:38:44Z","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/2209.14500/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models such as GPT-3 (Brown et al., 2020) can perform arbitrary tasks without undergoing fine-tuning after being prompted with only a few labeled examples. An arbitrary task can be reformulated as a natural language prompt, and a language model can be asked to generate the completion, indirectly performing the task in a paradigm known as prompt-based learning. To date, emergent prompt-based learning capabilities have mainly been demonstrated for unidirectional language models. However, bidirectional language models pre-trained on denoising objectives such as masked language mode","authors_text":"Ajay Patel, Bryan Li, Chris Callison-Burch, Colin Raffel, Mohammad Sadegh Rasooli, Noah Constant","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-29T01:35:57Z","title":"Bidirectional Language Models Are Also Few-shot Learners"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.14500","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":"sha256:0d047070c88b0e1cf9f19265c23f745823bec27f1d983e0d4d82e81dbcacdf6d","target":"record","created_at":"2026-07-05T05:38:44Z","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":"d80b8dcfe5499abac9db43496c352cb1aaa73b6bc47f53fab3d3fff50644b8aa","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-09-29T01:35:57Z","title_canon_sha256":"45d2e08d08d7277cd6f660e9ae8d04ef132abfb3ac75158dbf1f53501b7c9fa1"},"schema_version":"1.0","source":{"id":"2209.14500","kind":"arxiv","version":2}},"canonical_sha256":"86b240d17843fd8c5ee892e9ae597f6b426328dbc89eea0f17bc098007b2120b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"86b240d17843fd8c5ee892e9ae597f6b426328dbc89eea0f17bc098007b2120b","first_computed_at":"2026-07-05T05:38:44.337396Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:38:44.337396Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3EzvhCCqJCh0RoNV+hQqssavyXRZdBXYvm4TscuIG96yaBG86uEooRS85MuhnVPinc5HPYQu1XNEDsZDmvylCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:38:44.337856Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.14500","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0d047070c88b0e1cf9f19265c23f745823bec27f1d983e0d4d82e81dbcacdf6d","sha256:821b2559857922a970b0071c0c5b40609a3e60ec45366177b8195495a60eead7"],"state_sha256":"320670624eafd78a7ec24494cddb3638ac680a80f4c1c13417386dbc1eea62a8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gucUErF8IygZAKWs6Mj7+6jvwq3/nOrQpNWwd1lmQ0zhRf6qEumIqeaDgYIEwDE8QEmc0c7aDaoASmEMBb+wAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:19:20.530408Z","bundle_sha256":"8904486a6e2a94ba6f414f6e9406915b474641c23c76885d8acd97bf9b8abb5d"}}