{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:NCRT4WY7OEB42PGRT4SCIPDXC6","short_pith_number":"pith:NCRT4WY7","canonical_record":{"source":{"id":"2304.05970","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-12T16:47:15Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e237eddf5718af28b1a4cc576481600d01fe1efddad49fb03c052492d467a859","abstract_canon_sha256":"c507c79c1e2e4cb672cea0e49df61787c0fcf14c3dff6b0d4a4f9bb2687b56df"},"schema_version":"1.0"},"canonical_sha256":"68a33e5b1f7103cd3cd19f24243c7717ac4915f4b55e5d969e784949dfd75efe","source":{"kind":"arxiv","id":"2304.05970","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.05970","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"arxiv_version","alias_value":"2304.05970v1","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.05970","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_12","alias_value":"NCRT4WY7OEB4","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_16","alias_value":"NCRT4WY7OEB42PGR","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_8","alias_value":"NCRT4WY7","created_at":"2026-07-05T06:00:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:NCRT4WY7OEB42PGRT4SCIPDXC6","target":"record","payload":{"canonical_record":{"source":{"id":"2304.05970","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-12T16:47:15Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e237eddf5718af28b1a4cc576481600d01fe1efddad49fb03c052492d467a859","abstract_canon_sha256":"c507c79c1e2e4cb672cea0e49df61787c0fcf14c3dff6b0d4a4f9bb2687b56df"},"schema_version":"1.0"},"canonical_sha256":"68a33e5b1f7103cd3cd19f24243c7717ac4915f4b55e5d969e784949dfd75efe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:00:26.588833Z","signature_b64":"zoFJuc2qTpDjrIZjJRcTbLokxn80EiUTpFZJVdSuFWN62kTeYXbUW+7cCCKAZPuqG2I22iEUAr5uEoKHVZN6BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"68a33e5b1f7103cd3cd19f24243c7717ac4915f4b55e5d969e784949dfd75efe","last_reissued_at":"2026-07-05T06:00:26.588404Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:00:26.588404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.05970","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":"2026-07-05T06:00:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iQurTzbZv4XiU/2DHVsxhqYn1tV3AeYI15V7TxHMOeXWdvmIvUzdrvNNclQz9/zOGcKmeJE5MOyqo8FJnmZuBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:11:12.534182Z"},"content_sha256":"5256f4d643c60690a47c741e980ad2c097c1c5da2aba1b7e99a618809a85d7bd","schema_version":"1.0","event_id":"sha256:5256f4d643c60690a47c741e980ad2c097c1c5da2aba1b7e99a618809a85d7bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:NCRT4WY7OEB42PGRT4SCIPDXC6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Boosted Prompt Ensembles for Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Andrew Wang, Jimmy Ba, Michael R. Zhang, Silviu Pitis","submitted_at":"2023-04-12T16:47:15Z","abstract_excerpt":"Methods such as chain-of-thought prompting and self-consistency have pushed the frontier of language model reasoning performance with no additional training. To further improve performance, we propose a prompt ensembling method for large language models, which uses a small dataset to construct a set of few shot prompts that together comprise a ``boosted prompt ensemble''. The few shot examples for each prompt are chosen in a stepwise fashion to be ``hard'' examples on which the previous step's ensemble is uncertain. We show that this outperforms single-prompt output-space ensembles and bagged "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.05970","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/2304.05970/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":"2026-07-05T06:00:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BdjNXVSrMy6M0zgDciYLO2p6W34ajEcQQSfZjXf6Rd1EBicMZHMIoDt1nn3ovvgJUWMF/ALgKmU/8siX7hDwAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T10:11:12.534655Z"},"content_sha256":"c06966963f0ebaefdb3ee2391fe428fbd0f1896145c01244fce7f6eb087fb453","schema_version":"1.0","event_id":"sha256:c06966963f0ebaefdb3ee2391fe428fbd0f1896145c01244fce7f6eb087fb453"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/bundle.json","state_url":"https://pith.science/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/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":"2026-08-05T10:11:12Z","links":{"resolver":"https://pith.science/pith/NCRT4WY7OEB42PGRT4SCIPDXC6","bundle":"https://pith.science/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/bundle.json","state":"https://pith.science/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NCRT4WY7OEB42PGRT4SCIPDXC6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NCRT4WY7OEB42PGRT4SCIPDXC6","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":"c507c79c1e2e4cb672cea0e49df61787c0fcf14c3dff6b0d4a4f9bb2687b56df","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-12T16:47:15Z","title_canon_sha256":"e237eddf5718af28b1a4cc576481600d01fe1efddad49fb03c052492d467a859"},"schema_version":"1.0","source":{"id":"2304.05970","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.05970","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"arxiv_version","alias_value":"2304.05970v1","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.05970","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_12","alias_value":"NCRT4WY7OEB4","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_16","alias_value":"NCRT4WY7OEB42PGR","created_at":"2026-07-05T06:00:26Z"},{"alias_kind":"pith_short_8","alias_value":"NCRT4WY7","created_at":"2026-07-05T06:00:26Z"}],"graph_snapshots":[{"event_id":"sha256:c06966963f0ebaefdb3ee2391fe428fbd0f1896145c01244fce7f6eb087fb453","target":"graph","created_at":"2026-07-05T06:00:26Z","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/2304.05970/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Methods such as chain-of-thought prompting and self-consistency have pushed the frontier of language model reasoning performance with no additional training. To further improve performance, we propose a prompt ensembling method for large language models, which uses a small dataset to construct a set of few shot prompts that together comprise a ``boosted prompt ensemble''. The few shot examples for each prompt are chosen in a stepwise fashion to be ``hard'' examples on which the previous step's ensemble is uncertain. We show that this outperforms single-prompt output-space ensembles and bagged ","authors_text":"Andrew Wang, Jimmy Ba, Michael R. Zhang, Silviu Pitis","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-12T16:47:15Z","title":"Boosted Prompt Ensembles for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.05970","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":"sha256:5256f4d643c60690a47c741e980ad2c097c1c5da2aba1b7e99a618809a85d7bd","target":"record","created_at":"2026-07-05T06:00:26Z","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":"c507c79c1e2e4cb672cea0e49df61787c0fcf14c3dff6b0d4a4f9bb2687b56df","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-12T16:47:15Z","title_canon_sha256":"e237eddf5718af28b1a4cc576481600d01fe1efddad49fb03c052492d467a859"},"schema_version":"1.0","source":{"id":"2304.05970","kind":"arxiv","version":1}},"canonical_sha256":"68a33e5b1f7103cd3cd19f24243c7717ac4915f4b55e5d969e784949dfd75efe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"68a33e5b1f7103cd3cd19f24243c7717ac4915f4b55e5d969e784949dfd75efe","first_computed_at":"2026-07-05T06:00:26.588404Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:00:26.588404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zoFJuc2qTpDjrIZjJRcTbLokxn80EiUTpFZJVdSuFWN62kTeYXbUW+7cCCKAZPuqG2I22iEUAr5uEoKHVZN6BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:00:26.588833Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.05970","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5256f4d643c60690a47c741e980ad2c097c1c5da2aba1b7e99a618809a85d7bd","sha256:c06966963f0ebaefdb3ee2391fe428fbd0f1896145c01244fce7f6eb087fb453"],"state_sha256":"f877c26ec0ab1c64cd16d453fa969d56885af184c073f0b3fbdcca17f333a80c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2USOzCspb0MoTg+Kl+SeUWMH1tp07OWX6i1XFbkEaE8LWw77VKLnjAtJkQZpOl1Hs50WbHe37hGIxwqYLJj9BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T10:11:12.539482Z","bundle_sha256":"066e473f4709c844a1e7725538b397828f1fdd6198ca8cfdb9250b333b86a545"}}