{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7AV53LGIFCGZ2CNEC4JXGSAEXK","short_pith_number":"pith:7AV53LGI","canonical_record":{"source":{"id":"2402.03774","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-06T07:40:53Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"394724c63204440c8fa45d077ac6640276cff0f9941463adb28a6c41230a8bc2","abstract_canon_sha256":"53f25a12c5bbe788463c444f818c88fb2464a9434e9487e9978dbd75d06352f1"},"schema_version":"1.0"},"canonical_sha256":"f82bddacc8288d9d09a41713734804ba826093a51b48cd9af820747a3d7662be","source":{"kind":"arxiv","id":"2402.03774","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.03774","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"arxiv_version","alias_value":"2402.03774v2","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.03774","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_12","alias_value":"7AV53LGIFCGZ","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_16","alias_value":"7AV53LGIFCGZ2CNE","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_8","alias_value":"7AV53LGI","created_at":"2026-07-05T08:58:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7AV53LGIFCGZ2CNEC4JXGSAEXK","target":"record","payload":{"canonical_record":{"source":{"id":"2402.03774","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-06T07:40:53Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"394724c63204440c8fa45d077ac6640276cff0f9941463adb28a6c41230a8bc2","abstract_canon_sha256":"53f25a12c5bbe788463c444f818c88fb2464a9434e9487e9978dbd75d06352f1"},"schema_version":"1.0"},"canonical_sha256":"f82bddacc8288d9d09a41713734804ba826093a51b48cd9af820747a3d7662be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:58:42.443648Z","signature_b64":"7pSwOhXPliVsbHx1lWZnQOfd9LaZJwWcYFvo+x0qolurfJpwPCdSgsKUWCjChFJlOZS98ulcMuzcROzUae91Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f82bddacc8288d9d09a41713734804ba826093a51b48cd9af820747a3d7662be","last_reissued_at":"2026-07-05T08:58:42.443161Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:58:42.443161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.03774","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:58:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LI94SB5XcK2khLXPAWy74FuVhsFrlikiMTzRRymly7uJRtvjqXteJn/ndWlnszTV3+s27TSo26TQ1gy7his6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:25:24.864614Z"},"content_sha256":"19d2811d5c52f2f89ab77b6e0e9999c05a1967922e6f1b4d6499506d124360e9","schema_version":"1.0","event_id":"sha256:19d2811d5c52f2f89ab77b6e0e9999c05a1967922e6f1b4d6499506d124360e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7AV53LGIFCGZ2CNEC4JXGSAEXK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning a Decision Tree Algorithm with Transformers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"Chandan Singh, Jianfeng Gao, Jingbo Shang, Liyuan Liu, Yufan Zhuang","submitted_at":"2024-02-06T07:40:53Z","abstract_excerpt":"Decision trees are renowned for their ability to achieve high predictive performance while remaining interpretable, especially on tabular data. Traditionally, they are constructed through recursive algorithms, where they partition the data at every node in a tree. However, identifying a good partition is challenging, as decision trees optimized for local segments may not yield global generalization. To address this, we introduce MetaTree, a transformer-based model trained via meta-learning to directly produce strong decision trees. Specifically, we fit both greedy decision trees and globally o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.03774","kind":"arxiv","version":2},"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/2402.03774/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":"2026-07-05T08:58:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"azeIsMnwAzkho3/Zb4+V158BZY4YDfYGYdJ0bihcUiga+hUzw/QtN/Q4GCf5Inw0BYwXdUwn8EXzPQG10Xi1CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:25:24.865119Z"},"content_sha256":"e92f204d81955a54b78047b20e203b599a54d23efa252a178368f20a215ab7a8","schema_version":"1.0","event_id":"sha256:e92f204d81955a54b78047b20e203b599a54d23efa252a178368f20a215ab7a8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/bundle.json","state_url":"https://pith.science/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/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":"2026-08-17T18:25:24Z","links":{"resolver":"https://pith.science/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK","bundle":"https://pith.science/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/bundle.json","state":"https://pith.science/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7AV53LGIFCGZ2CNEC4JXGSAEXK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7AV53LGIFCGZ2CNEC4JXGSAEXK","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":"53f25a12c5bbe788463c444f818c88fb2464a9434e9487e9978dbd75d06352f1","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-06T07:40:53Z","title_canon_sha256":"394724c63204440c8fa45d077ac6640276cff0f9941463adb28a6c41230a8bc2"},"schema_version":"1.0","source":{"id":"2402.03774","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.03774","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"arxiv_version","alias_value":"2402.03774v2","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.03774","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_12","alias_value":"7AV53LGIFCGZ","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_16","alias_value":"7AV53LGIFCGZ2CNE","created_at":"2026-07-05T08:58:42Z"},{"alias_kind":"pith_short_8","alias_value":"7AV53LGI","created_at":"2026-07-05T08:58:42Z"}],"graph_snapshots":[{"event_id":"sha256:e92f204d81955a54b78047b20e203b599a54d23efa252a178368f20a215ab7a8","target":"graph","created_at":"2026-07-05T08:58:42Z","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/2402.03774/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Decision trees are renowned for their ability to achieve high predictive performance while remaining interpretable, especially on tabular data. Traditionally, they are constructed through recursive algorithms, where they partition the data at every node in a tree. However, identifying a good partition is challenging, as decision trees optimized for local segments may not yield global generalization. To address this, we introduce MetaTree, a transformer-based model trained via meta-learning to directly produce strong decision trees. Specifically, we fit both greedy decision trees and globally o","authors_text":"Chandan Singh, Jianfeng Gao, Jingbo Shang, Liyuan Liu, Yufan Zhuang","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-06T07:40:53Z","title":"Learning a Decision Tree Algorithm with Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.03774","kind":"arxiv","version":2},"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":"sha256:19d2811d5c52f2f89ab77b6e0e9999c05a1967922e6f1b4d6499506d124360e9","target":"record","created_at":"2026-07-05T08:58:42Z","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":"53f25a12c5bbe788463c444f818c88fb2464a9434e9487e9978dbd75d06352f1","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-06T07:40:53Z","title_canon_sha256":"394724c63204440c8fa45d077ac6640276cff0f9941463adb28a6c41230a8bc2"},"schema_version":"1.0","source":{"id":"2402.03774","kind":"arxiv","version":2}},"canonical_sha256":"f82bddacc8288d9d09a41713734804ba826093a51b48cd9af820747a3d7662be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f82bddacc8288d9d09a41713734804ba826093a51b48cd9af820747a3d7662be","first_computed_at":"2026-07-05T08:58:42.443161Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:58:42.443161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7pSwOhXPliVsbHx1lWZnQOfd9LaZJwWcYFvo+x0qolurfJpwPCdSgsKUWCjChFJlOZS98ulcMuzcROzUae91Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:58:42.443648Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.03774","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:19d2811d5c52f2f89ab77b6e0e9999c05a1967922e6f1b4d6499506d124360e9","sha256:e92f204d81955a54b78047b20e203b599a54d23efa252a178368f20a215ab7a8"],"state_sha256":"5936eaaed2796bccc86c2514852254f3cc82a7c6a9fb9323c161d493ca9ca8d8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HeNXH6Gn4xOcUltMMh5WZID4xkPJlZSfeIKAm8DNn1bBNiqQESyJNARjq2VpXHlG+JLHN7OO41StHsZfMYZ9DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T18:25:24.870499Z","bundle_sha256":"b108026a2a30d10752e502065e7b74775f900efa677f0e8ba931798e426ec540"}}