{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:K7HOCLNDWRERBKRN44FXMGP5EM","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":"de476f6073cbd47e877226777de3f277e7937325f47c64542a54c22a275c1a09","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-18T11:43:01Z","title_canon_sha256":"7afa9a2d8d314f74f6f3f04af2fdb769b19ed8fd94ca5fffceb94b304fabdc94"},"schema_version":"1.0","source":{"id":"2307.09165","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.09165","created_at":"2026-07-05T08:54:02Z"},{"alias_kind":"arxiv_version","alias_value":"2307.09165v2","created_at":"2026-07-05T08:54:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.09165","created_at":"2026-07-05T08:54:02Z"},{"alias_kind":"pith_short_12","alias_value":"K7HOCLNDWRER","created_at":"2026-07-05T08:54:02Z"},{"alias_kind":"pith_short_16","alias_value":"K7HOCLNDWRERBKRN","created_at":"2026-07-05T08:54:02Z"},{"alias_kind":"pith_short_8","alias_value":"K7HOCLND","created_at":"2026-07-05T08:54:02Z"}],"graph_snapshots":[{"event_id":"sha256:576a9400d69f529e735c6364d1b19a86965f72850a4fe81f99186b5739a089a1","target":"graph","created_at":"2026-07-05T08:54:02Z","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/2307.09165/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Efficiency and trustworthiness are two eternal pursuits when applying deep learning in real-world applications. With regard to efficiency, dataset distillation (DD) endeavors to reduce training costs by distilling the large dataset into a tiny synthetic dataset. However, existing methods merely concentrate on in-distribution (InD) classification in a closed-world setting, disregarding out-of-distribution (OOD) samples. On the other hand, OOD detection aims to enhance models' trustworthiness, which is always inefficiently achieved in full-data settings. For the first time, we simultaneously con","authors_text":"Fei Zhu, Shijie Ma, Xu-Yao Zhang, Zhen Cheng","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-18T11:43:01Z","title":"Towards Trustworthy Dataset Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.09165","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:f4c1d22f5607c13794d044fc0d91882f24ef780d2a6574f776d9824fb3f94a84","target":"record","created_at":"2026-07-05T08:54:02Z","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":"de476f6073cbd47e877226777de3f277e7937325f47c64542a54c22a275c1a09","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-18T11:43:01Z","title_canon_sha256":"7afa9a2d8d314f74f6f3f04af2fdb769b19ed8fd94ca5fffceb94b304fabdc94"},"schema_version":"1.0","source":{"id":"2307.09165","kind":"arxiv","version":2}},"canonical_sha256":"57cee12da3b44910aa2de70b7619fd233d2d1acdcbfcac54f421c5323c718ca9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"57cee12da3b44910aa2de70b7619fd233d2d1acdcbfcac54f421c5323c718ca9","first_computed_at":"2026-07-05T08:54:02.882925Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:02.882925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h6lO8On5sbFbfoiEZr/l2yjnYZA+tBfbeQd6Lc+wxznz/hctQ0o8DeqYAyHvN4Hn6mI2C0SZ2dZXbSzI3etXCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:02.883282Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.09165","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f4c1d22f5607c13794d044fc0d91882f24ef780d2a6574f776d9824fb3f94a84","sha256:576a9400d69f529e735c6364d1b19a86965f72850a4fe81f99186b5739a089a1"],"state_sha256":"f4a332a38482f8cba36fdf3b68de6962c5e8719a16f04bb5b331d29d6851811b"}