{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:C2OTJFQBNTNCNWG25RZRRGGEIQ","short_pith_number":"pith:C2OTJFQB","canonical_record":{"source":{"id":"2310.13196","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-19T23:11:37Z","cross_cats_sorted":["cs.DB","cs.LG"],"title_canon_sha256":"792af62666ae7ad627ef8f7918b017488167ffac309e9e93ba6ba81e86a7137b","abstract_canon_sha256":"a90d4ed448943bb7c6996822cbcf648274110e2d8cac058114b6b0b74c3398e0"},"schema_version":"1.0"},"canonical_sha256":"169d3496016cda26d8daec731898c44402924b4488343063c551f4bc47bc7b6e","source":{"kind":"arxiv","id":"2310.13196","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.13196","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"arxiv_version","alias_value":"2310.13196v1","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.13196","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_12","alias_value":"C2OTJFQBNTNC","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_16","alias_value":"C2OTJFQBNTNCNWG2","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_8","alias_value":"C2OTJFQB","created_at":"2026-07-05T07:02:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:C2OTJFQBNTNCNWG25RZRRGGEIQ","target":"record","payload":{"canonical_record":{"source":{"id":"2310.13196","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-19T23:11:37Z","cross_cats_sorted":["cs.DB","cs.LG"],"title_canon_sha256":"792af62666ae7ad627ef8f7918b017488167ffac309e9e93ba6ba81e86a7137b","abstract_canon_sha256":"a90d4ed448943bb7c6996822cbcf648274110e2d8cac058114b6b0b74c3398e0"},"schema_version":"1.0"},"canonical_sha256":"169d3496016cda26d8daec731898c44402924b4488343063c551f4bc47bc7b6e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:02:58.768861Z","signature_b64":"/BDWx3qcfalVhRPxrxT4OxIjJawVjoCboDdP2i4DX0I+vM445EexZ6fJpyn50a5ZvnmMUoiEno926Z8t8kppAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"169d3496016cda26d8daec731898c44402924b4488343063c551f4bc47bc7b6e","last_reissued_at":"2026-07-05T07:02:58.768376Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:02:58.768376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.13196","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":"2026-07-05T07:02:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V1eMESR1MC5utYIbfnTJNurL1r+R4xU/3VkDGN7fGjZuFDZnDYuPTFo//dzGcxvzNqx4ZrVfXsF6/RDSTassCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:42:21.998946Z"},"content_sha256":"8a88e07b3c5db304accee1d32fb3a3cb90927fdf00ff64a68feeed882f2d6419","schema_version":"1.0","event_id":"sha256:8a88e07b3c5db304accee1d32fb3a3cb90927fdf00ff64a68feeed882f2d6419"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:C2OTJFQBNTNCNWG25RZRRGGEIQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NameGuess: Column Name Expansion for Tabular Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DB","cs.LG"],"primary_cat":"cs.CL","authors_text":"Balasubramaniam Srinivasan, George Karypis, Huzefa Rangwala, Jiani Zhang, Shen Wang, Zhengyuan Shen","submitted_at":"2023-10-19T23:11:37Z","abstract_excerpt":"Recent advances in large language models have revolutionized many sectors, including the database industry. One common challenge when dealing with large volumes of tabular data is the pervasive use of abbreviated column names, which can negatively impact performance on various data search, access, and understanding tasks. To address this issue, we introduce a new task, called NameGuess, to expand column names (used in database schema) as a natural language generation problem. We create a training dataset of 384K abbreviated-expanded column pairs using a new data fabrication method and a human-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.13196","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/2310.13196/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":"2026-07-05T07:02:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"16nc4OQkYCCLuOUjMGeBQco4rtc5l0e3dQIM9T6dHIJgPWpBEH27jfp0uqtWBu6qZokr6E+p5qds7f/qqMpZBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:42:21.999477Z"},"content_sha256":"4b3aea93536b0c72d639e1eebd14ab5c6a047222773fdf55588fffcd07599824","schema_version":"1.0","event_id":"sha256:4b3aea93536b0c72d639e1eebd14ab5c6a047222773fdf55588fffcd07599824"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/bundle.json","state_url":"https://pith.science/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/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":"2026-08-03T20:42:22Z","links":{"resolver":"https://pith.science/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ","bundle":"https://pith.science/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/bundle.json","state":"https://pith.science/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C2OTJFQBNTNCNWG25RZRRGGEIQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:C2OTJFQBNTNCNWG25RZRRGGEIQ","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":"a90d4ed448943bb7c6996822cbcf648274110e2d8cac058114b6b0b74c3398e0","cross_cats_sorted":["cs.DB","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-19T23:11:37Z","title_canon_sha256":"792af62666ae7ad627ef8f7918b017488167ffac309e9e93ba6ba81e86a7137b"},"schema_version":"1.0","source":{"id":"2310.13196","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.13196","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"arxiv_version","alias_value":"2310.13196v1","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.13196","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_12","alias_value":"C2OTJFQBNTNC","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_16","alias_value":"C2OTJFQBNTNCNWG2","created_at":"2026-07-05T07:02:58Z"},{"alias_kind":"pith_short_8","alias_value":"C2OTJFQB","created_at":"2026-07-05T07:02:58Z"}],"graph_snapshots":[{"event_id":"sha256:4b3aea93536b0c72d639e1eebd14ab5c6a047222773fdf55588fffcd07599824","target":"graph","created_at":"2026-07-05T07:02:58Z","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/2310.13196/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in large language models have revolutionized many sectors, including the database industry. One common challenge when dealing with large volumes of tabular data is the pervasive use of abbreviated column names, which can negatively impact performance on various data search, access, and understanding tasks. To address this issue, we introduce a new task, called NameGuess, to expand column names (used in database schema) as a natural language generation problem. We create a training dataset of 384K abbreviated-expanded column pairs using a new data fabrication method and a human-","authors_text":"Balasubramaniam Srinivasan, George Karypis, Huzefa Rangwala, Jiani Zhang, Shen Wang, Zhengyuan Shen","cross_cats":["cs.DB","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-19T23:11:37Z","title":"NameGuess: Column Name Expansion for Tabular Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.13196","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":"sha256:8a88e07b3c5db304accee1d32fb3a3cb90927fdf00ff64a68feeed882f2d6419","target":"record","created_at":"2026-07-05T07:02:58Z","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":"a90d4ed448943bb7c6996822cbcf648274110e2d8cac058114b6b0b74c3398e0","cross_cats_sorted":["cs.DB","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-19T23:11:37Z","title_canon_sha256":"792af62666ae7ad627ef8f7918b017488167ffac309e9e93ba6ba81e86a7137b"},"schema_version":"1.0","source":{"id":"2310.13196","kind":"arxiv","version":1}},"canonical_sha256":"169d3496016cda26d8daec731898c44402924b4488343063c551f4bc47bc7b6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"169d3496016cda26d8daec731898c44402924b4488343063c551f4bc47bc7b6e","first_computed_at":"2026-07-05T07:02:58.768376Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:02:58.768376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/BDWx3qcfalVhRPxrxT4OxIjJawVjoCboDdP2i4DX0I+vM445EexZ6fJpyn50a5ZvnmMUoiEno926Z8t8kppAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:02:58.768861Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.13196","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8a88e07b3c5db304accee1d32fb3a3cb90927fdf00ff64a68feeed882f2d6419","sha256:4b3aea93536b0c72d639e1eebd14ab5c6a047222773fdf55588fffcd07599824"],"state_sha256":"dd39378e4eabd0c72295791209faac4d63a367efbb58de03baa842c5c0657d7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DcrcW+tICyl9N1taYm2ZALo7DmoOYcjNsMer+2aFwwFEAVeN983yMG1v+1Rcx18tkio4ppQM7kqbIS5d/60hBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T20:42:22.003064Z","bundle_sha256":"df17bb701484dcf98404e4b9f40d9c55fcab9548f4020d903f2899a83165a85a"}}