{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZHVCFC6G2WCDYRZU72YMYQTKIX","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":"80115dcbd8756ce5fc8b0af3c553a3f20c1d62c1c4cd01b89506c36ebe27a74d","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-26T23:01:47Z","title_canon_sha256":"f0c3f6c5f073f420e70688524e48e41dba2f38878d7b626ee3826b47732eafe2"},"schema_version":"1.0","source":{"id":"1906.11829","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.11829","created_at":"2026-07-05T01:46:11Z"},{"alias_kind":"arxiv_version","alias_value":"1906.11829v4","created_at":"2026-07-05T01:46:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.11829","created_at":"2026-07-05T01:46:11Z"},{"alias_kind":"pith_short_12","alias_value":"ZHVCFC6G2WCD","created_at":"2026-07-05T01:46:11Z"},{"alias_kind":"pith_short_16","alias_value":"ZHVCFC6G2WCDYRZU","created_at":"2026-07-05T01:46:11Z"},{"alias_kind":"pith_short_8","alias_value":"ZHVCFC6G","created_at":"2026-07-05T01:46:11Z"}],"graph_snapshots":[{"event_id":"sha256:469568cd7aa3946cc1bb036a7ed291798b506472a8dd1708435b7b2c4e1eebc8","target":"graph","created_at":"2026-07-05T01:46:11Z","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/1906.11829/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data selection methods, such as active learning and core-set selection, are useful tools for machine learning on large datasets. However, they can be prohibitively expensive to apply in deep learning because they depend on feature representations that need to be learned. In this work, we show that we can greatly improve the computational efficiency by using a small proxy model to perform data selection (e.g., selecting data points to label for active learning). By removing hidden layers from the target model, using smaller architectures, and training for fewer epochs, we create proxies that ar","authors_text":"Baharan Mirzasoleiman, Christopher Yeh, Cody Coleman, Jure Leskovec, Matei Zaharia, Percy Liang, Peter Bailis, Stephen Mussmann","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-26T23:01:47Z","title":"Selection via Proxy: Efficient Data Selection for Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.11829","kind":"arxiv","version":4},"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":"sha256:5eba022edf726950efc02b1c402d51132e4c60b55b00066c6a668ddd059097c4","target":"record","created_at":"2026-07-05T01:46:11Z","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":"80115dcbd8756ce5fc8b0af3c553a3f20c1d62c1c4cd01b89506c36ebe27a74d","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-26T23:01:47Z","title_canon_sha256":"f0c3f6c5f073f420e70688524e48e41dba2f38878d7b626ee3826b47732eafe2"},"schema_version":"1.0","source":{"id":"1906.11829","kind":"arxiv","version":4}},"canonical_sha256":"c9ea228bc6d5843c4734feb0cc426a45d6b6b12c45bcd9b3f10ce7e12e551a2a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9ea228bc6d5843c4734feb0cc426a45d6b6b12c45bcd9b3f10ce7e12e551a2a","first_computed_at":"2026-07-05T01:46:11.538196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:46:11.538196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Lz7gLz2oSr9fkvqlVEatwEQdrymgYRqGR4kEJ67O4pWn1LZ0+5XWVj++ZgFqmD1yVOwYku1gNViLBBKUTxmhBg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:46:11.538764Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.11829","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5eba022edf726950efc02b1c402d51132e4c60b55b00066c6a668ddd059097c4","sha256:469568cd7aa3946cc1bb036a7ed291798b506472a8dd1708435b7b2c4e1eebc8"],"state_sha256":"14260bfffc312ce65b26643c11c8005e2933efb2b9297dea52a0937021283a84"}