{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:UX4IYI3XOVK4FO5SKMSS6OYEE3","short_pith_number":"pith:UX4IYI3X","canonical_record":{"source":{"id":"2310.17140","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-26T04:22:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cb14942afca279d1165108a1016fbb354b8a60d4b93a6a5b424b43ffac63b163","abstract_canon_sha256":"afddc72be8a3cc803f5d60a375a0c70fba1a451cd8bb8067e734d67bff37b2a4"},"schema_version":"1.0"},"canonical_sha256":"a5f88c23777555c2bbb253252f3b0426e19c8512d7014e5c279563d07a278cf2","source":{"kind":"arxiv","id":"2310.17140","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.17140","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"2310.17140v1","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.17140","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"UX4IYI3XOVK4","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_16","alias_value":"UX4IYI3XOVK4FO5S","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_8","alias_value":"UX4IYI3X","created_at":"2026-07-05T07:05:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:UX4IYI3XOVK4FO5SKMSS6OYEE3","target":"record","payload":{"canonical_record":{"source":{"id":"2310.17140","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-26T04:22:23Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cb14942afca279d1165108a1016fbb354b8a60d4b93a6a5b424b43ffac63b163","abstract_canon_sha256":"afddc72be8a3cc803f5d60a375a0c70fba1a451cd8bb8067e734d67bff37b2a4"},"schema_version":"1.0"},"canonical_sha256":"a5f88c23777555c2bbb253252f3b0426e19c8512d7014e5c279563d07a278cf2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:05:20.390540Z","signature_b64":"Aw3AtzuogFvltoUahUqV2XvGXPqcHxiaZWBZ+mB76ezqu7yfF7MbsSng66kzKLuIkoYXXdY2fqFHSvY3aFPDDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a5f88c23777555c2bbb253252f3b0426e19c8512d7014e5c279563d07a278cf2","last_reissued_at":"2026-07-05T07:05:20.390049Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:05:20.390049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.17140","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":"2026-07-05T07:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5U2pGMtasQ4V1iZPDGDF1LwFF0NBURdY779V4fJmgLibmPuxWDEF9COG8STYS1M/dnFGnrpuPhPf9ynQofNrBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:29:00.801166Z"},"content_sha256":"67b82cc883137406c34ca069caef856280f192ef902244c53298324ca42c7fdb","schema_version":"1.0","event_id":"sha256:67b82cc883137406c34ca069caef856280f192ef902244c53298324ca42c7fdb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:UX4IYI3XOVK4FO5SKMSS6OYEE3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Symbolic Planning and Code Generation for Grounded Dialogue","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Alexander M. Rush, Daniel Fried, Derek Chen, Justin T. Chiu, Saujas Vaduguru, Wenting Zhao","submitted_at":"2023-10-26T04:22:23Z","abstract_excerpt":"Large language models (LLMs) excel at processing and generating both text and code. However, LLMs have had limited applicability in grounded task-oriented dialogue as they are difficult to steer toward task objectives and fail to handle novel grounding. We present a modular and interpretable grounded dialogue system that addresses these shortcomings by composing LLMs with a symbolic planner and grounded code execution. Our system consists of a reader and planner: the reader leverages an LLM to convert partner utterances into executable code, calling functions that perform grounding. The transl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.17140","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/2310.17140/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":"2026-07-05T07:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5I1S9f6Ono7dviP9W6Syx8ybnqVMfB9PL7JoBJmk5pzqIfgOd0HBRV+mEthsjk7VDWaaulz+ybR5ZAbW7nLqCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T19:29:00.801732Z"},"content_sha256":"e4b523d01d87995de98ac021d65c22874cc31bc1df5c38b7f1b7fd1f97ce89e6","schema_version":"1.0","event_id":"sha256:e4b523d01d87995de98ac021d65c22874cc31bc1df5c38b7f1b7fd1f97ce89e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/bundle.json","state_url":"https://pith.science/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/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":"2026-08-06T19:29:00Z","links":{"resolver":"https://pith.science/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3","bundle":"https://pith.science/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/bundle.json","state":"https://pith.science/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UX4IYI3XOVK4FO5SKMSS6OYEE3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:UX4IYI3XOVK4FO5SKMSS6OYEE3","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":"afddc72be8a3cc803f5d60a375a0c70fba1a451cd8bb8067e734d67bff37b2a4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-26T04:22:23Z","title_canon_sha256":"cb14942afca279d1165108a1016fbb354b8a60d4b93a6a5b424b43ffac63b163"},"schema_version":"1.0","source":{"id":"2310.17140","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.17140","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"2310.17140v1","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.17140","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"UX4IYI3XOVK4","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_16","alias_value":"UX4IYI3XOVK4FO5S","created_at":"2026-07-05T07:05:20Z"},{"alias_kind":"pith_short_8","alias_value":"UX4IYI3X","created_at":"2026-07-05T07:05:20Z"}],"graph_snapshots":[{"event_id":"sha256:e4b523d01d87995de98ac021d65c22874cc31bc1df5c38b7f1b7fd1f97ce89e6","target":"graph","created_at":"2026-07-05T07:05:20Z","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/2310.17140/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) excel at processing and generating both text and code. However, LLMs have had limited applicability in grounded task-oriented dialogue as they are difficult to steer toward task objectives and fail to handle novel grounding. We present a modular and interpretable grounded dialogue system that addresses these shortcomings by composing LLMs with a symbolic planner and grounded code execution. Our system consists of a reader and planner: the reader leverages an LLM to convert partner utterances into executable code, calling functions that perform grounding. The transl","authors_text":"Alexander M. Rush, Daniel Fried, Derek Chen, Justin T. Chiu, Saujas Vaduguru, Wenting Zhao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-26T04:22:23Z","title":"Symbolic Planning and Code Generation for Grounded Dialogue"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.17140","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":"sha256:67b82cc883137406c34ca069caef856280f192ef902244c53298324ca42c7fdb","target":"record","created_at":"2026-07-05T07:05:20Z","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":"afddc72be8a3cc803f5d60a375a0c70fba1a451cd8bb8067e734d67bff37b2a4","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-10-26T04:22:23Z","title_canon_sha256":"cb14942afca279d1165108a1016fbb354b8a60d4b93a6a5b424b43ffac63b163"},"schema_version":"1.0","source":{"id":"2310.17140","kind":"arxiv","version":1}},"canonical_sha256":"a5f88c23777555c2bbb253252f3b0426e19c8512d7014e5c279563d07a278cf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5f88c23777555c2bbb253252f3b0426e19c8512d7014e5c279563d07a278cf2","first_computed_at":"2026-07-05T07:05:20.390049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:05:20.390049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Aw3AtzuogFvltoUahUqV2XvGXPqcHxiaZWBZ+mB76ezqu7yfF7MbsSng66kzKLuIkoYXXdY2fqFHSvY3aFPDDA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:05:20.390540Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.17140","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:67b82cc883137406c34ca069caef856280f192ef902244c53298324ca42c7fdb","sha256:e4b523d01d87995de98ac021d65c22874cc31bc1df5c38b7f1b7fd1f97ce89e6"],"state_sha256":"1ca665ed44ba2b7952023e40702655126d88edfc7fc3e1a7ce137f0767411b4b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JlOraeBbpxXHl/yKNOP54FOqgy2misZ+E23syryC6Mc3ce61ZiRfNnKcboVztDDE1fHCyBgvL/vZWleQ6ILsCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T19:29:00.808057Z","bundle_sha256":"da248830ed50d25c9aa96288207527156b54b7133f9db22884d09fa1ddfc05b4"}}