{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EKZJ7WFQNL2HSGLK3YY2V2I2EG","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":"c231f91adeda1073c68f2faa6f1c8df209ef0a8a172f5f744e06ea64b8974619","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-16T17:35:52Z","title_canon_sha256":"0dba5113c43ab46216e684f3bd233134f25b5d4c37a6b76ebd02affa5cad053a"},"schema_version":"1.0","source":{"id":"2211.09070","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.09070","created_at":"2026-07-05T05:16:47Z"},{"alias_kind":"arxiv_version","alias_value":"2211.09070v1","created_at":"2026-07-05T05:16:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.09070","created_at":"2026-07-05T05:16:47Z"},{"alias_kind":"pith_short_12","alias_value":"EKZJ7WFQNL2H","created_at":"2026-07-05T05:16:47Z"},{"alias_kind":"pith_short_16","alias_value":"EKZJ7WFQNL2HSGLK","created_at":"2026-07-05T05:16:47Z"},{"alias_kind":"pith_short_8","alias_value":"EKZJ7WFQ","created_at":"2026-07-05T05:16:47Z"}],"graph_snapshots":[{"event_id":"sha256:24d2096c5116016aa0bff68e12a95298de0906998774a8ca7fc2a100802585bb","target":"graph","created_at":"2026-07-05T05:16:47Z","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/2211.09070/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The paper presents an approach to semantic grounding of language models (LMs) that conceptualizes the LM as a conditional model generating text given a desired semantic message formalized as a set of entity-relationship triples. It embeds the LM in an auto-encoder by feeding its output to a semantic parser whose output is in the same representation domain as the input message. Compared to a baseline that generates text using greedy search, we demonstrate two techniques that improve the fluency and semantic accuracy of the generated text: The first technique samples multiple candidate text sequ","authors_text":"Chris Alberti, Ciprian Chelba, Kuzman Ganchev, Michael Collins, Sebastian Gehrmann","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-16T17:35:52Z","title":"Towards Computationally Verifiable Semantic Grounding for Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.09070","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":"sha256:5aa719fb63b74b29a9be51d0ef59418bc50632200a3e57fa4aa47f3593fa74ec","target":"record","created_at":"2026-07-05T05:16:47Z","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":"c231f91adeda1073c68f2faa6f1c8df209ef0a8a172f5f744e06ea64b8974619","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-16T17:35:52Z","title_canon_sha256":"0dba5113c43ab46216e684f3bd233134f25b5d4c37a6b76ebd02affa5cad053a"},"schema_version":"1.0","source":{"id":"2211.09070","kind":"arxiv","version":1}},"canonical_sha256":"22b29fd8b06af479196ade31aae91a2194cff36ed99327da8639928f1a147de7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22b29fd8b06af479196ade31aae91a2194cff36ed99327da8639928f1a147de7","first_computed_at":"2026-07-05T05:16:47.375594Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:16:47.375594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4kAStHvO8Uj3EDK20bw0K3OIwBhFOLL+BpmQajSASSkRWqfgTJmR/rBh33kSSirFbvxBo4j/mgmkHHVXpGQiCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:16:47.376116Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.09070","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5aa719fb63b74b29a9be51d0ef59418bc50632200a3e57fa4aa47f3593fa74ec","sha256:24d2096c5116016aa0bff68e12a95298de0906998774a8ca7fc2a100802585bb"],"state_sha256":"456201f90842b57a296fe43ec108b8af18a3fc98d5f6f8420a5c4d9e35f744c0"}