{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PW6S6ZDZZQ4DHL3XLJXG27C4F3","short_pith_number":"pith:PW6S6ZDZ","canonical_record":{"source":{"id":"2405.20519","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-30T22:31:16Z","cross_cats_sorted":[],"title_canon_sha256":"9f83030043b1ec28f5ddb0767571fc9623a265585b6fc0a560b16db5f18cfa66","abstract_canon_sha256":"0965bfce12fd0309a8b30e3f79833c6fcc3e2e99df3aa460abd3a4ae4c750085"},"schema_version":"1.0"},"canonical_sha256":"7dbd2f6479cc3833af775a6e6d7c5c2ed75fed536cffe2a7a1eef14521332722","source":{"kind":"arxiv","id":"2405.20519","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.20519","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"arxiv_version","alias_value":"2405.20519v1","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.20519","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_12","alias_value":"PW6S6ZDZZQ4D","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_16","alias_value":"PW6S6ZDZZQ4DHL3X","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_8","alias_value":"PW6S6ZDZ","created_at":"2026-07-05T08:25:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PW6S6ZDZZQ4DHL3XLJXG27C4F3","target":"record","payload":{"canonical_record":{"source":{"id":"2405.20519","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-30T22:31:16Z","cross_cats_sorted":[],"title_canon_sha256":"9f83030043b1ec28f5ddb0767571fc9623a265585b6fc0a560b16db5f18cfa66","abstract_canon_sha256":"0965bfce12fd0309a8b30e3f79833c6fcc3e2e99df3aa460abd3a4ae4c750085"},"schema_version":"1.0"},"canonical_sha256":"7dbd2f6479cc3833af775a6e6d7c5c2ed75fed536cffe2a7a1eef14521332722","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:25:38.504486Z","signature_b64":"FVfcpj563EgF8eRcqMp48uxp7OmTAXB/rm4ad4v/HqC7Kjain0VqM6gdMISBZJ7ZB0VnQD+HlNP+v99FWVOtCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7dbd2f6479cc3833af775a6e6d7c5c2ed75fed536cffe2a7a1eef14521332722","last_reissued_at":"2026-07-05T08:25:38.504082Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:25:38.504082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.20519","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":"2026-07-05T08:25:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wV9SR91nMT6cFOO4HzbPYL7VmUbC9EHt0A0wsfpUz3v+/N7aHTSNLIyRQ9C3wUlKmTthfnbBOe7+fpYMhRJcDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T20:03:42.574507Z"},"content_sha256":"9d3d94db342b1d50246dfe8b651f6d300464a190788e65056288b6560a009d35","schema_version":"1.0","event_id":"sha256:9d3d94db342b1d50246dfe8b651f6d300464a190788e65056288b6560a009d35"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PW6S6ZDZZQ4DHL3XLJXG27C4F3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion On Syntax Trees For Program Synthesis","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Erik Jenner, Shreyas Kapur, Stuart Russell","submitted_at":"2024-05-30T22:31:16Z","abstract_excerpt":"Large language models generate code one token at a time. Their autoregressive generation process lacks the feedback of observing the program's output. Training LLMs to suggest edits directly can be challenging due to the scarcity of rich edit data. To address these problems, we propose neural diffusion models that operate on syntax trees of any context-free grammar. Similar to image diffusion models, our method also inverts ``noise'' applied to syntax trees. Rather than generating code sequentially, we iteratively edit it while preserving syntactic validity, which makes it easy to combine this"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.20519","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/2405.20519/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":"2026-07-05T08:25:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IeT9PIRNDtPVikCjlTh0PeXaOJzXN7JyAOAsWNn68G9nMa1cJew1Mcnw4MEGYOAHZCefkxRjxpetxSmNDVcnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T20:03:42.574876Z"},"content_sha256":"ede49d13f0ac7f6d29470746aadbec958fcc96fb4a48882a9f76400454037ca3","schema_version":"1.0","event_id":"sha256:ede49d13f0ac7f6d29470746aadbec958fcc96fb4a48882a9f76400454037ca3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/bundle.json","state_url":"https://pith.science/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/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":"2026-08-20T20:03:42Z","links":{"resolver":"https://pith.science/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3","bundle":"https://pith.science/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/bundle.json","state":"https://pith.science/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PW6S6ZDZZQ4DHL3XLJXG27C4F3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PW6S6ZDZZQ4DHL3XLJXG27C4F3","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":"0965bfce12fd0309a8b30e3f79833c6fcc3e2e99df3aa460abd3a4ae4c750085","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-30T22:31:16Z","title_canon_sha256":"9f83030043b1ec28f5ddb0767571fc9623a265585b6fc0a560b16db5f18cfa66"},"schema_version":"1.0","source":{"id":"2405.20519","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.20519","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"arxiv_version","alias_value":"2405.20519v1","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.20519","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_12","alias_value":"PW6S6ZDZZQ4D","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_16","alias_value":"PW6S6ZDZZQ4DHL3X","created_at":"2026-07-05T08:25:38Z"},{"alias_kind":"pith_short_8","alias_value":"PW6S6ZDZ","created_at":"2026-07-05T08:25:38Z"}],"graph_snapshots":[{"event_id":"sha256:ede49d13f0ac7f6d29470746aadbec958fcc96fb4a48882a9f76400454037ca3","target":"graph","created_at":"2026-07-05T08:25:38Z","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/2405.20519/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models generate code one token at a time. Their autoregressive generation process lacks the feedback of observing the program's output. Training LLMs to suggest edits directly can be challenging due to the scarcity of rich edit data. To address these problems, we propose neural diffusion models that operate on syntax trees of any context-free grammar. Similar to image diffusion models, our method also inverts ``noise'' applied to syntax trees. Rather than generating code sequentially, we iteratively edit it while preserving syntactic validity, which makes it easy to combine this","authors_text":"Erik Jenner, Shreyas Kapur, Stuart Russell","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-30T22:31:16Z","title":"Diffusion On Syntax Trees For Program Synthesis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.20519","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":"sha256:9d3d94db342b1d50246dfe8b651f6d300464a190788e65056288b6560a009d35","target":"record","created_at":"2026-07-05T08:25:38Z","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":"0965bfce12fd0309a8b30e3f79833c6fcc3e2e99df3aa460abd3a4ae4c750085","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-30T22:31:16Z","title_canon_sha256":"9f83030043b1ec28f5ddb0767571fc9623a265585b6fc0a560b16db5f18cfa66"},"schema_version":"1.0","source":{"id":"2405.20519","kind":"arxiv","version":1}},"canonical_sha256":"7dbd2f6479cc3833af775a6e6d7c5c2ed75fed536cffe2a7a1eef14521332722","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7dbd2f6479cc3833af775a6e6d7c5c2ed75fed536cffe2a7a1eef14521332722","first_computed_at":"2026-07-05T08:25:38.504082Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:25:38.504082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FVfcpj563EgF8eRcqMp48uxp7OmTAXB/rm4ad4v/HqC7Kjain0VqM6gdMISBZJ7ZB0VnQD+HlNP+v99FWVOtCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:25:38.504486Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.20519","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9d3d94db342b1d50246dfe8b651f6d300464a190788e65056288b6560a009d35","sha256:ede49d13f0ac7f6d29470746aadbec958fcc96fb4a48882a9f76400454037ca3"],"state_sha256":"5155b2bf6193009b980b16666c1015f859f4b5bc43fe4d9b31b9c29571aaa18c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JyjEvmjuICtzBBYutsLUbcX78ROf+wf8cAdkvYemdQZXlu1lHH8iUT9EEOzjkf7xVgTl8msGMN/05pQttx4XDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T20:03:42.577136Z","bundle_sha256":"4c209c60250a493cf4c1aa0802eadafef112c5bd9c6291d98f1c93921dd796af"}}