{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:LWRLABI5Z3JJCS4LTQGFVWCTBV","short_pith_number":"pith:LWRLABI5","canonical_record":{"source":{"id":"2311.04954","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-08T18:57:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1cac55120a13993e870173beb283c0561e6cddba01920b30ce01935170fe5c01","abstract_canon_sha256":"5031a140dc1a1f2f27e56866d0b981a731fda6ebbc6907b3885b80e32f32a12a"},"schema_version":"1.0"},"canonical_sha256":"5da2b0051dced2914b8b9c0c5ad8530d7d2b4db6d10f97b2886b99b06ae77031","source":{"kind":"arxiv","id":"2311.04954","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04954","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04954v1","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04954","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_12","alias_value":"LWRLABI5Z3JJ","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_16","alias_value":"LWRLABI5Z3JJCS4L","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_8","alias_value":"LWRLABI5","created_at":"2026-07-05T07:10:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:LWRLABI5Z3JJCS4LTQGFVWCTBV","target":"record","payload":{"canonical_record":{"source":{"id":"2311.04954","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-08T18:57:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1cac55120a13993e870173beb283c0561e6cddba01920b30ce01935170fe5c01","abstract_canon_sha256":"5031a140dc1a1f2f27e56866d0b981a731fda6ebbc6907b3885b80e32f32a12a"},"schema_version":"1.0"},"canonical_sha256":"5da2b0051dced2914b8b9c0c5ad8530d7d2b4db6d10f97b2886b99b06ae77031","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:10:52.607716Z","signature_b64":"xcZp/naoDlKR+E68ag2O1bOVvRgGxBoyGISb2wTKqNuhPwEgToId2dQOjQgU9EWtzBP9n+6qNJRKK0+NxrQUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5da2b0051dced2914b8b9c0c5ad8530d7d2b4db6d10f97b2886b99b06ae77031","last_reissued_at":"2026-07-05T07:10:52.607259Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:10:52.607259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.04954","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":"2026-07-05T07:10:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7WD69a/B5G86I7ja2Pn6nxLBTOlH2Xy8A2z0k4CQjOqP9kXEnygxcz6lbU/AzNuK/ru67yrOap4sReyVDWTdDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:20:12.705630Z"},"content_sha256":"6f5b63aa9643e5b567a31d2493dbee710f7fbe5f5349438236b23edd943cbfe2","schema_version":"1.0","event_id":"sha256:6f5b63aa9643e5b567a31d2493dbee710f7fbe5f5349438236b23edd943cbfe2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:LWRLABI5Z3JJCS4LTQGFVWCTBV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prompt Sketching for Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Luca Beurer-Kellner, Marc Fischer, Mark Niklas M\\\"uller, Martin Vechev","submitted_at":"2023-11-08T18:57:23Z","abstract_excerpt":"Many recent prompting strategies for large language models (LLMs) query the model multiple times sequentially -- first to produce intermediate results and then the final answer. However, using these methods, both decoder and model are unaware of potential follow-up prompts, leading to disconnected and undesirably wordy intermediate responses. In this work, we address this issue by proposing prompt sketching, a new prompting paradigm in which an LLM does not only respond by completing a prompt, but by predicting values for multiple variables in a template. This way, sketching grants users more "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04954","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/2311.04954/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":"2026-07-05T07:10:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k2n3CBNkZ3FH75QpRA5krDxhRmixUKqBLrmaKjS4wvSnwJqjG1DjjAwqUdwJJ3gRaf3UiOn1LUuTZCqkm6c5AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T07:20:12.706162Z"},"content_sha256":"1043305bb6736d6ea364ffab5c0c88f63ded38460fbe308a3e153d1bbd87dc8d","schema_version":"1.0","event_id":"sha256:1043305bb6736d6ea364ffab5c0c88f63ded38460fbe308a3e153d1bbd87dc8d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/bundle.json","state_url":"https://pith.science/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/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":"2026-08-07T07:20:12Z","links":{"resolver":"https://pith.science/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV","bundle":"https://pith.science/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/bundle.json","state":"https://pith.science/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LWRLABI5Z3JJCS4LTQGFVWCTBV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LWRLABI5Z3JJCS4LTQGFVWCTBV","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":"5031a140dc1a1f2f27e56866d0b981a731fda6ebbc6907b3885b80e32f32a12a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-08T18:57:23Z","title_canon_sha256":"1cac55120a13993e870173beb283c0561e6cddba01920b30ce01935170fe5c01"},"schema_version":"1.0","source":{"id":"2311.04954","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04954","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04954v1","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04954","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_12","alias_value":"LWRLABI5Z3JJ","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_16","alias_value":"LWRLABI5Z3JJCS4L","created_at":"2026-07-05T07:10:52Z"},{"alias_kind":"pith_short_8","alias_value":"LWRLABI5","created_at":"2026-07-05T07:10:52Z"}],"graph_snapshots":[{"event_id":"sha256:1043305bb6736d6ea364ffab5c0c88f63ded38460fbe308a3e153d1bbd87dc8d","target":"graph","created_at":"2026-07-05T07:10:52Z","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/2311.04954/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many recent prompting strategies for large language models (LLMs) query the model multiple times sequentially -- first to produce intermediate results and then the final answer. However, using these methods, both decoder and model are unaware of potential follow-up prompts, leading to disconnected and undesirably wordy intermediate responses. In this work, we address this issue by proposing prompt sketching, a new prompting paradigm in which an LLM does not only respond by completing a prompt, but by predicting values for multiple variables in a template. This way, sketching grants users more ","authors_text":"Luca Beurer-Kellner, Marc Fischer, Mark Niklas M\\\"uller, Martin Vechev","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-08T18:57:23Z","title":"Prompt Sketching for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04954","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":"sha256:6f5b63aa9643e5b567a31d2493dbee710f7fbe5f5349438236b23edd943cbfe2","target":"record","created_at":"2026-07-05T07:10:52Z","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":"5031a140dc1a1f2f27e56866d0b981a731fda6ebbc6907b3885b80e32f32a12a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-11-08T18:57:23Z","title_canon_sha256":"1cac55120a13993e870173beb283c0561e6cddba01920b30ce01935170fe5c01"},"schema_version":"1.0","source":{"id":"2311.04954","kind":"arxiv","version":1}},"canonical_sha256":"5da2b0051dced2914b8b9c0c5ad8530d7d2b4db6d10f97b2886b99b06ae77031","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5da2b0051dced2914b8b9c0c5ad8530d7d2b4db6d10f97b2886b99b06ae77031","first_computed_at":"2026-07-05T07:10:52.607259Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:10:52.607259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xcZp/naoDlKR+E68ag2O1bOVvRgGxBoyGISb2wTKqNuhPwEgToId2dQOjQgU9EWtzBP9n+6qNJRKK0+NxrQUBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:10:52.607716Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.04954","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6f5b63aa9643e5b567a31d2493dbee710f7fbe5f5349438236b23edd943cbfe2","sha256:1043305bb6736d6ea364ffab5c0c88f63ded38460fbe308a3e153d1bbd87dc8d"],"state_sha256":"f17da6e85cfd3f631543574b6265c64877b54f0f6e70255de30009625778289e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TBz+LhXBzVFoJkIviWKH8p0hSP5EBoeJBKwa7Xome/3Vj8PG2+IQA0pUZIBvWmH/5X7bmNB1OEJBQ5zpnzAQAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T07:20:12.711038Z","bundle_sha256":"bd97897979f8dcaf5670d460491c1a737310a5bd0b76121b3deba9a32753bbf1"}}