{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:FFQR4J6ECQRIZ5HAMSX4BAK6UE","short_pith_number":"pith:FFQR4J6E","canonical_record":{"source":{"id":"2608.01879","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-03T08:24:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4d031e69f9ffaca3438245c0be4f861688016d4f21b3d008a504a45abe1a8854","abstract_canon_sha256":"b53c7e91137246f34a5804dfd6fb723517d0f772d6a5e7481380393ba0b08f37"},"schema_version":"1.0"},"canonical_sha256":"29611e27c414228cf4e064afc0815ea13eedc1d0fa985c5b8ce2c40c34241902","source":{"kind":"arxiv","id":"2608.01879","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01879","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01879v1","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01879","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_12","alias_value":"FFQR4J6ECQRI","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_16","alias_value":"FFQR4J6ECQRIZ5HA","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_8","alias_value":"FFQR4J6E","created_at":"2026-08-04T02:07:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:FFQR4J6ECQRIZ5HAMSX4BAK6UE","target":"record","payload":{"canonical_record":{"source":{"id":"2608.01879","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-03T08:24:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4d031e69f9ffaca3438245c0be4f861688016d4f21b3d008a504a45abe1a8854","abstract_canon_sha256":"b53c7e91137246f34a5804dfd6fb723517d0f772d6a5e7481380393ba0b08f37"},"schema_version":"1.0"},"canonical_sha256":"29611e27c414228cf4e064afc0815ea13eedc1d0fa985c5b8ce2c40c34241902","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T02:07:31.131697Z","signature_b64":"n66aCu5sRNs7gIZAGeWJSL/kmklu6VN8/GIGvXCzCpdMhh3s563Zkhq00nMfxV9kqR1rWV6OtTp/FSSO+Lg4Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"29611e27c414228cf4e064afc0815ea13eedc1d0fa985c5b8ce2c40c34241902","last_reissued_at":"2026-08-04T02:07:31.129881Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T02:07:31.129881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.01879","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":"2026-08-04T02:07:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qVa5u2SaWveQ+SwdT+Xe8vxbX21sIwXT1aKk/vmxENtE/dPk+9KxwDi5+sKPGHkPf5W8J3pzsKzmo2vnoja5CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:28:14.105274Z"},"content_sha256":"06f4d2b26a6a359708e30904c086f05495efe693311742209c89c38dd8c4dc99","schema_version":"1.0","event_id":"sha256:06f4d2b26a6a359708e30904c086f05495efe693311742209c89c38dd8c4dc99"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:FFQR4J6ECQRIZ5HAMSX4BAK6UE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Bin Zhou, Jintao Ke, Taijie Chen, Zijian Shen, Ziyang Jiang","submitted_at":"2026-08-03T08:24:35Z","abstract_excerpt":"Tabular data generation supports analysis and decision-making when target-domain data are scarce, yet collecting complete target samples is often costly. A practical but underexplored setting provides only a few target records together with richer source data from a related domain. Existing few-shot tabular generators often either fit sparse target statistics directly, which can overfit incidental patterns, or reuse source-domain generators, which may preserve dependencies that no longer hold in the target domain. To address this problem, we propose LAB-Tab, an LLM-augmented Bayesian network ("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01879","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/2608.01879/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":"2026-08-04T02:07:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1B81HncXkiNJeH0geJt9pAP85tvG4r0nKs/1wgc6CB8pRWU0OpAKzQ985khVcxKC3p0sSIR0PHi2vluSCdkwCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T18:28:14.105816Z"},"content_sha256":"8efe5184a502472a357d66a18402a1e3901e6177cb62d2d09342cfa7dd77253b","schema_version":"1.0","event_id":"sha256:8efe5184a502472a357d66a18402a1e3901e6177cb62d2d09342cfa7dd77253b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/bundle.json","state_url":"https://pith.science/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/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":"2026-08-06T18:28:14Z","links":{"resolver":"https://pith.science/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE","bundle":"https://pith.science/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/bundle.json","state":"https://pith.science/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FFQR4J6ECQRIZ5HAMSX4BAK6UE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FFQR4J6ECQRIZ5HAMSX4BAK6UE","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":"b53c7e91137246f34a5804dfd6fb723517d0f772d6a5e7481380393ba0b08f37","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-03T08:24:35Z","title_canon_sha256":"4d031e69f9ffaca3438245c0be4f861688016d4f21b3d008a504a45abe1a8854"},"schema_version":"1.0","source":{"id":"2608.01879","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01879","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01879v1","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01879","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_12","alias_value":"FFQR4J6ECQRI","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_16","alias_value":"FFQR4J6ECQRIZ5HA","created_at":"2026-08-04T02:07:31Z"},{"alias_kind":"pith_short_8","alias_value":"FFQR4J6E","created_at":"2026-08-04T02:07:31Z"}],"graph_snapshots":[{"event_id":"sha256:8efe5184a502472a357d66a18402a1e3901e6177cb62d2d09342cfa7dd77253b","target":"graph","created_at":"2026-08-04T02:07:31Z","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/2608.01879/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Tabular data generation supports analysis and decision-making when target-domain data are scarce, yet collecting complete target samples is often costly. A practical but underexplored setting provides only a few target records together with richer source data from a related domain. Existing few-shot tabular generators often either fit sparse target statistics directly, which can overfit incidental patterns, or reuse source-domain generators, which may preserve dependencies that no longer hold in the target domain. To address this problem, we propose LAB-Tab, an LLM-augmented Bayesian network (","authors_text":"Bin Zhou, Jintao Ke, Taijie Chen, Zijian Shen, Ziyang Jiang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-03T08:24:35Z","title":"LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01879","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":"sha256:06f4d2b26a6a359708e30904c086f05495efe693311742209c89c38dd8c4dc99","target":"record","created_at":"2026-08-04T02:07:31Z","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":"b53c7e91137246f34a5804dfd6fb723517d0f772d6a5e7481380393ba0b08f37","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-03T08:24:35Z","title_canon_sha256":"4d031e69f9ffaca3438245c0be4f861688016d4f21b3d008a504a45abe1a8854"},"schema_version":"1.0","source":{"id":"2608.01879","kind":"arxiv","version":1}},"canonical_sha256":"29611e27c414228cf4e064afc0815ea13eedc1d0fa985c5b8ce2c40c34241902","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29611e27c414228cf4e064afc0815ea13eedc1d0fa985c5b8ce2c40c34241902","first_computed_at":"2026-08-04T02:07:31.129881Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:07:31.129881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n66aCu5sRNs7gIZAGeWJSL/kmklu6VN8/GIGvXCzCpdMhh3s563Zkhq00nMfxV9kqR1rWV6OtTp/FSSO+Lg4Cg==","signature_status":"signed_v1","signed_at":"2026-08-04T02:07:31.131697Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.01879","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:06f4d2b26a6a359708e30904c086f05495efe693311742209c89c38dd8c4dc99","sha256:8efe5184a502472a357d66a18402a1e3901e6177cb62d2d09342cfa7dd77253b"],"state_sha256":"5732242330e60b72c4a83a5a7f792a79653c6618f1149d94c7349af15d9b6ec4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v/Zu1S57Z/ELMmRDIBFSYjpKe5kmhJoxauz7B598TYCwjE6XRcd1EsqxZN/47IOy1r+QvALzpI7NJb4QqtxIBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T18:28:14.118998Z","bundle_sha256":"9418d118382897ad85a5c103716e8d24df7cb66f02234fbc3d8973c85c59c0e4"}}