{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:F6JR6UEXRIJCVNR434E3BYQPOD","short_pith_number":"pith:F6JR6UEX","canonical_record":{"source":{"id":"2408.05948","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-12T06:48:43Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"4c10c0d2a808d27b3a51f3c1ede73bcabfd515f8a2de191ee109888bde01a2a2","abstract_canon_sha256":"82d72b9c4d82463b4e9695764eae15c68c788d16a1eb0dc57b17754b2adf1a45"},"schema_version":"1.0"},"canonical_sha256":"2f931f50978a122ab63cdf09b0e20f70e423ef0be317a7aa761b60f8369bd0ce","source":{"kind":"arxiv","id":"2408.05948","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.05948","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.05948v1","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.05948","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"F6JR6UEXRIJC","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_16","alias_value":"F6JR6UEXRIJCVNR4","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_8","alias_value":"F6JR6UEX","created_at":"2026-07-05T08:54:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:F6JR6UEXRIJCVNR434E3BYQPOD","target":"record","payload":{"canonical_record":{"source":{"id":"2408.05948","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-12T06:48:43Z","cross_cats_sorted":["cs.IR","cs.LG"],"title_canon_sha256":"4c10c0d2a808d27b3a51f3c1ede73bcabfd515f8a2de191ee109888bde01a2a2","abstract_canon_sha256":"82d72b9c4d82463b4e9695764eae15c68c788d16a1eb0dc57b17754b2adf1a45"},"schema_version":"1.0"},"canonical_sha256":"2f931f50978a122ab63cdf09b0e20f70e423ef0be317a7aa761b60f8369bd0ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:54:27.466742Z","signature_b64":"KduU/eUnSZocporaumEPEE2LbflZfmPUjTAA+CzFekAQG0aFl0Hg0DRwReiLxz+wMefG13iTQfxV3h0fvOVOAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2f931f50978a122ab63cdf09b0e20f70e423ef0be317a7aa761b60f8369bd0ce","last_reissued_at":"2026-07-05T08:54:27.466201Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:54:27.466201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.05948","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":"2026-07-05T08:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KS5hRPvyyoUqXVqqAs/UViv3JvrWLJw1sYrx9xyGWZO/gkBtxTiGIX5ziWcOvPzgyd+dMhmEubYmIp1/l6t/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T14:19:15.512793Z"},"content_sha256":"6c89f2925bae66ed56c666b045bc5547e9ffe0a290b7fe1618958663cbe39400","schema_version":"1.0","event_id":"sha256:6c89f2925bae66ed56c666b045bc5547e9ffe0a290b7fe1618958663cbe39400"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:F6JR6UEXRIJCVNR434E3BYQPOD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.LG"],"primary_cat":"cs.CL","authors_text":"Ali Mousavi, Daniel Lee, Ihab Ilyas, Jeff Pound, Jimmy Lin, Mostafa Arefiyan, Ronak Pradeep, Saloni Potdar, Yisi Sang, Yunyao Li","submitted_at":"2024-08-12T06:48:43Z","abstract_excerpt":"The rapid advancement of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evaluation. These datasets must accommodate diverse user interaction modes, including text and voice, each presenting unique modeling challenges. Knowledge Graphs (KGs), with their structured and evolving nature, offer an ideal foundation for current and precise knowledge. Although human-curated KG-based conversational datasets exist, they struggle to keep pace with the rapidly changing user information needs. We present C"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.05948","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/2408.05948/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":"2026-07-05T08:54:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4f9Ri2PuZKBbPCqcZhn2HnfK7yNSMkqDXeq1bShj8Kw4KY1W4VCT1jcxTsGRcoHtIBnMvA6QPHrOljKStiNhCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T14:19:15.513653Z"},"content_sha256":"03135c182986f5225b67afa33019f6b52f49ad7f2a6172f2b631158c7c7f072d","schema_version":"1.0","event_id":"sha256:03135c182986f5225b67afa33019f6b52f49ad7f2a6172f2b631158c7c7f072d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F6JR6UEXRIJCVNR434E3BYQPOD/bundle.json","state_url":"https://pith.science/pith/F6JR6UEXRIJCVNR434E3BYQPOD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F6JR6UEXRIJCVNR434E3BYQPOD/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":"2026-07-31T14:19:15Z","links":{"resolver":"https://pith.science/pith/F6JR6UEXRIJCVNR434E3BYQPOD","bundle":"https://pith.science/pith/F6JR6UEXRIJCVNR434E3BYQPOD/bundle.json","state":"https://pith.science/pith/F6JR6UEXRIJCVNR434E3BYQPOD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F6JR6UEXRIJCVNR434E3BYQPOD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:F6JR6UEXRIJCVNR434E3BYQPOD","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":"82d72b9c4d82463b4e9695764eae15c68c788d16a1eb0dc57b17754b2adf1a45","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-12T06:48:43Z","title_canon_sha256":"4c10c0d2a808d27b3a51f3c1ede73bcabfd515f8a2de191ee109888bde01a2a2"},"schema_version":"1.0","source":{"id":"2408.05948","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.05948","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.05948v1","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.05948","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_12","alias_value":"F6JR6UEXRIJC","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_16","alias_value":"F6JR6UEXRIJCVNR4","created_at":"2026-07-05T08:54:27Z"},{"alias_kind":"pith_short_8","alias_value":"F6JR6UEX","created_at":"2026-07-05T08:54:27Z"}],"graph_snapshots":[{"event_id":"sha256:03135c182986f5225b67afa33019f6b52f49ad7f2a6172f2b631158c7c7f072d","target":"graph","created_at":"2026-07-05T08:54:27Z","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/2408.05948/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid advancement of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evaluation. These datasets must accommodate diverse user interaction modes, including text and voice, each presenting unique modeling challenges. Knowledge Graphs (KGs), with their structured and evolving nature, offer an ideal foundation for current and precise knowledge. Although human-curated KG-based conversational datasets exist, they struggle to keep pace with the rapidly changing user information needs. We present C","authors_text":"Ali Mousavi, Daniel Lee, Ihab Ilyas, Jeff Pound, Jimmy Lin, Mostafa Arefiyan, Ronak Pradeep, Saloni Potdar, Yisi Sang, Yunyao Li","cross_cats":["cs.IR","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-12T06:48:43Z","title":"ConvKGYarn: Spinning Configurable and Scalable Conversational Knowledge Graph QA datasets with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.05948","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":"sha256:6c89f2925bae66ed56c666b045bc5547e9ffe0a290b7fe1618958663cbe39400","target":"record","created_at":"2026-07-05T08:54:27Z","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":"82d72b9c4d82463b4e9695764eae15c68c788d16a1eb0dc57b17754b2adf1a45","cross_cats_sorted":["cs.IR","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-12T06:48:43Z","title_canon_sha256":"4c10c0d2a808d27b3a51f3c1ede73bcabfd515f8a2de191ee109888bde01a2a2"},"schema_version":"1.0","source":{"id":"2408.05948","kind":"arxiv","version":1}},"canonical_sha256":"2f931f50978a122ab63cdf09b0e20f70e423ef0be317a7aa761b60f8369bd0ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2f931f50978a122ab63cdf09b0e20f70e423ef0be317a7aa761b60f8369bd0ce","first_computed_at":"2026-07-05T08:54:27.466201Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:27.466201Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KduU/eUnSZocporaumEPEE2LbflZfmPUjTAA+CzFekAQG0aFl0Hg0DRwReiLxz+wMefG13iTQfxV3h0fvOVOAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:27.466742Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.05948","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6c89f2925bae66ed56c666b045bc5547e9ffe0a290b7fe1618958663cbe39400","sha256:03135c182986f5225b67afa33019f6b52f49ad7f2a6172f2b631158c7c7f072d"],"state_sha256":"73a337e8c81f49f58fd65f2a9d28a6ee184a3efc836f3266580307ed47fe2c48"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BIUphuZAFqv26O5N5N/vwx18PWc5cfDpSfLpf52hn+GVhppEC42eiPmRWPw1/+V0kxR0G3pddKc6E2QLvB47CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T14:19:15.519615Z","bundle_sha256":"a3f4370561841427c04520c367efccd5c5b99d85d9609bff429f55800b12709e"}}