{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QPOFSL4BZFIXVRR3RBQ5BCOIFY","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":"453b6f1042452fcb2dacad4b0c4114024f2c804974019ae5d0beda38863cb33a","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-10-30T19:45:50Z","title_canon_sha256":"d307c26679dc48c026a35f2a41018787e563f32490d0ef5f502e1eaf92bc394c"},"schema_version":"1.0","source":{"id":"2411.00865","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.00865","created_at":"2026-07-05T10:37:36Z"},{"alias_kind":"arxiv_version","alias_value":"2411.00865v2","created_at":"2026-07-05T10:37:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.00865","created_at":"2026-07-05T10:37:36Z"},{"alias_kind":"pith_short_12","alias_value":"QPOFSL4BZFIX","created_at":"2026-07-05T10:37:36Z"},{"alias_kind":"pith_short_16","alias_value":"QPOFSL4BZFIXVRR3","created_at":"2026-07-05T10:37:36Z"},{"alias_kind":"pith_short_8","alias_value":"QPOFSL4B","created_at":"2026-07-05T10:37:36Z"}],"graph_snapshots":[{"event_id":"sha256:ca6b9236f34ee0fe644bbd684dca76e81457164bb33aadb59d091b1e39daaeb8","target":"graph","created_at":"2026-07-05T10:37:36Z","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/2411.00865/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generating executable code from natural language instructions using Large Language Models (LLMs) poses challenges such as semantic ambiguity and understanding taskspecific contexts. To address these issues, we propose a system called DemoCraft, which enhances code generation by leveraging in-context learning and demonstration selection, combined with latent concept learning. Latent concept learning introduces additional concept tokens, which are trainable embeddings that capture task-specific knowledge. We then test our system on two major datasets: MBPP and Humaneval. Our experimental results","authors_text":"Mihit Sreejith, Nirmal Joshua Kapu","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-10-30T19:45:50Z","title":"Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.00865","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:e77edb4b5f3f0b0874c9c566a82c78d4a524939feb6280b8c683b8dcf01e1e08","target":"record","created_at":"2026-07-05T10:37:36Z","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":"453b6f1042452fcb2dacad4b0c4114024f2c804974019ae5d0beda38863cb33a","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-10-30T19:45:50Z","title_canon_sha256":"d307c26679dc48c026a35f2a41018787e563f32490d0ef5f502e1eaf92bc394c"},"schema_version":"1.0","source":{"id":"2411.00865","kind":"arxiv","version":2}},"canonical_sha256":"83dc592f81c9517ac63b8861d089c82e1e228098986d6c00b21a1c0c6d48189a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83dc592f81c9517ac63b8861d089c82e1e228098986d6c00b21a1c0c6d48189a","first_computed_at":"2026-07-05T10:37:36.446414Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:37:36.446414Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LIlPCCboJM3w5OvQIPNE9cGHp0UAZxrh9D7Yz2HgtDQECaStFVnsds7sHLICR/nEjcFKu+Vt1oa7IrjYiuyPAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:37:36.446917Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.00865","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e77edb4b5f3f0b0874c9c566a82c78d4a524939feb6280b8c683b8dcf01e1e08","sha256:ca6b9236f34ee0fe644bbd684dca76e81457164bb33aadb59d091b1e39daaeb8"],"state_sha256":"1af5834f2b778468f4cbc8860a883a84e1f46be429b1a0369b32e0ea57151823"}