{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:SMLLJBPXUWA2UUXSSEXEHCVQ7C","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":"e840c39f6c4cc64ac52357df16f864bd45a8d8313c9cc798e60d1d22690e6cd3","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-03-02T20:23:18Z","title_canon_sha256":"8b47c26e132559472340e73c55bcb5d560f034e99466b5e4a00dbae93eeac3b6"},"schema_version":"1.0","source":{"id":"1503.00693","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.00693","created_at":"2026-05-18T02:25:49Z"},{"alias_kind":"arxiv_version","alias_value":"1503.00693v1","created_at":"2026-05-18T02:25:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.00693","created_at":"2026-05-18T02:25:49Z"},{"alias_kind":"pith_short_12","alias_value":"SMLLJBPXUWA2","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"SMLLJBPXUWA2UUXS","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"SMLLJBPX","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:e0dd3b5aaa933f9da8d816bf11cfff38266a2fc7f5dbf0b47273c4ce0787b2a1","target":"graph","created_at":"2026-05-18T02:25:49Z","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"},"paper":{"abstract_excerpt":"When applying machine learning to problems in NLP, there are many choices to make about how to represent input texts. These choices can have a big effect on performance, but they are often uninteresting to researchers or practitioners who simply need a module that performs well. We propose an approach to optimizing over this space of choices, formulating the problem as global optimization. We apply a sequential model-based optimization technique and show that our method makes standard linear models competitive with more sophisticated, expensive state-of-the-art methods based on latent variable","authors_text":"Dani Yogatama, Noah A. Smith","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-03-02T20:23:18Z","title":"Bayesian Optimization of Text Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.00693","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":"sha256:351a410cc0520efc590632185347d0d2b7311de4f5086a674aa9fe20673031f6","target":"record","created_at":"2026-05-18T02:25:49Z","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":"e840c39f6c4cc64ac52357df16f864bd45a8d8313c9cc798e60d1d22690e6cd3","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-03-02T20:23:18Z","title_canon_sha256":"8b47c26e132559472340e73c55bcb5d560f034e99466b5e4a00dbae93eeac3b6"},"schema_version":"1.0","source":{"id":"1503.00693","kind":"arxiv","version":1}},"canonical_sha256":"9316b485f7a581aa52f2912e438ab0f895f17ba40b47951fc1ddfa8aa6844614","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9316b485f7a581aa52f2912e438ab0f895f17ba40b47951fc1ddfa8aa6844614","first_computed_at":"2026-05-18T02:25:49.496089Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:25:49.496089Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/NEoOP0KsWdlZsAnTJwCdrdUqASvIZoe8rmrIHjL/NK0n/U0W20fu9bhKEc4jAZCleRyeZB5NJeom6y1CID2Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:25:49.496481Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.00693","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:351a410cc0520efc590632185347d0d2b7311de4f5086a674aa9fe20673031f6","sha256:e0dd3b5aaa933f9da8d816bf11cfff38266a2fc7f5dbf0b47273c4ce0787b2a1"],"state_sha256":"ad81a5b3ac964a3db885ba6617f3056558041af0632c53698de9a0f8a13e5227"}