{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:TFMOYJLW7TIFLKSZYGXGQS6HIR","short_pith_number":"pith:TFMOYJLW","canonical_record":{"source":{"id":"2207.09639","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-20T03:54:05Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"58b395c63f1c4516be44bd6a73e34a06c1e154799dfc6177fba46a065416e3ea","abstract_canon_sha256":"34deb480ac6049507549262af5636d7427fce33ddfc993e5d6486102b552a922"},"schema_version":"1.0"},"canonical_sha256":"9958ec2576fcd055aa59c1ae684bc7445c82e5ec4b623e80112850e5fee03743","source":{"kind":"arxiv","id":"2207.09639","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.09639","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"arxiv_version","alias_value":"2207.09639v2","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.09639","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_12","alias_value":"TFMOYJLW7TIF","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_16","alias_value":"TFMOYJLW7TIFLKSZ","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_8","alias_value":"TFMOYJLW","created_at":"2026-07-05T05:07:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:TFMOYJLW7TIFLKSZYGXGQS6HIR","target":"record","payload":{"canonical_record":{"source":{"id":"2207.09639","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-20T03:54:05Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"58b395c63f1c4516be44bd6a73e34a06c1e154799dfc6177fba46a065416e3ea","abstract_canon_sha256":"34deb480ac6049507549262af5636d7427fce33ddfc993e5d6486102b552a922"},"schema_version":"1.0"},"canonical_sha256":"9958ec2576fcd055aa59c1ae684bc7445c82e5ec4b623e80112850e5fee03743","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:07:01.475810Z","signature_b64":"k3PR7sozoTghdO6Al3YzMMFhI1vHP6hZHfaxBJ2/Zv5pyUeBHTDtmR3+Smz2xM2LQzMcBrRFb2dxB/KM7NXrDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9958ec2576fcd055aa59c1ae684bc7445c82e5ec4b623e80112850e5fee03743","last_reissued_at":"2026-07-05T05:07:01.475341Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:07:01.475341Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.09639","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":"2026-07-05T05:07:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hyb8Du75PSsfZaGZ8ddQOOQMgRXIXJ61J5neDttU+BPYt61i+7a/fF/K3xnCTcEjESReCqELSLsC5oGvnElnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T01:09:05.030522Z"},"content_sha256":"137524aa57352cc1ebfd3a7e95842091b692c5560ba3d6788484901bf32b59bc","schema_version":"1.0","event_id":"sha256:137524aa57352cc1ebfd3a7e95842091b692c5560ba3d6788484901bf32b59bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:TFMOYJLW7TIFLKSZYGXGQS6HIR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DC-BENCH: Dataset Condensation Benchmark","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Cho-Jui Hsieh, Justin Cui, Ruochen Wang, Si Si","submitted_at":"2022-07-20T03:54:05Z","abstract_excerpt":"Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that captures the rich information encoded in the original dataset. As the size of datasets contemporary machine learning models rely on becomes increasingly large, condensation methods become a prominent direction for accelerating network training and reducing data storage. Despite numerous methods have been proposed in this rapidly growing field, evaluating and comparing different condensation methods is non-trivial and still remains an open issue. The quality of condensed dataset are often shadowed by many "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.09639","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/2207.09639/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":"2026-07-05T05:07:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SBeNUARZB98ddHpBgtOeUVkPhYZ1kZJtkcsZOOcfLKOUEBqnitS3V5TY5CFbZtvigA5Yd78iy9ZY/SrXICwRBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T01:09:05.030909Z"},"content_sha256":"86f6e041a7bbf05cf89be64fa1074fd2100fecf8fa89f577ae438516678141d1","schema_version":"1.0","event_id":"sha256:86f6e041a7bbf05cf89be64fa1074fd2100fecf8fa89f577ae438516678141d1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/bundle.json","state_url":"https://pith.science/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/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":"2026-08-19T01:09:05Z","links":{"resolver":"https://pith.science/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR","bundle":"https://pith.science/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/bundle.json","state":"https://pith.science/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TFMOYJLW7TIFLKSZYGXGQS6HIR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:TFMOYJLW7TIFLKSZYGXGQS6HIR","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":"34deb480ac6049507549262af5636d7427fce33ddfc993e5d6486102b552a922","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-20T03:54:05Z","title_canon_sha256":"58b395c63f1c4516be44bd6a73e34a06c1e154799dfc6177fba46a065416e3ea"},"schema_version":"1.0","source":{"id":"2207.09639","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.09639","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"arxiv_version","alias_value":"2207.09639v2","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.09639","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_12","alias_value":"TFMOYJLW7TIF","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_16","alias_value":"TFMOYJLW7TIFLKSZ","created_at":"2026-07-05T05:07:01Z"},{"alias_kind":"pith_short_8","alias_value":"TFMOYJLW","created_at":"2026-07-05T05:07:01Z"}],"graph_snapshots":[{"event_id":"sha256:86f6e041a7bbf05cf89be64fa1074fd2100fecf8fa89f577ae438516678141d1","target":"graph","created_at":"2026-07-05T05:07:01Z","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/2207.09639/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that captures the rich information encoded in the original dataset. As the size of datasets contemporary machine learning models rely on becomes increasingly large, condensation methods become a prominent direction for accelerating network training and reducing data storage. Despite numerous methods have been proposed in this rapidly growing field, evaluating and comparing different condensation methods is non-trivial and still remains an open issue. The quality of condensed dataset are often shadowed by many ","authors_text":"Cho-Jui Hsieh, Justin Cui, Ruochen Wang, Si Si","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-20T03:54:05Z","title":"DC-BENCH: Dataset Condensation Benchmark"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.09639","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":"sha256:137524aa57352cc1ebfd3a7e95842091b692c5560ba3d6788484901bf32b59bc","target":"record","created_at":"2026-07-05T05:07:01Z","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":"34deb480ac6049507549262af5636d7427fce33ddfc993e5d6486102b552a922","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-20T03:54:05Z","title_canon_sha256":"58b395c63f1c4516be44bd6a73e34a06c1e154799dfc6177fba46a065416e3ea"},"schema_version":"1.0","source":{"id":"2207.09639","kind":"arxiv","version":2}},"canonical_sha256":"9958ec2576fcd055aa59c1ae684bc7445c82e5ec4b623e80112850e5fee03743","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9958ec2576fcd055aa59c1ae684bc7445c82e5ec4b623e80112850e5fee03743","first_computed_at":"2026-07-05T05:07:01.475341Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:07:01.475341Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k3PR7sozoTghdO6Al3YzMMFhI1vHP6hZHfaxBJ2/Zv5pyUeBHTDtmR3+Smz2xM2LQzMcBrRFb2dxB/KM7NXrDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:07:01.475810Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.09639","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:137524aa57352cc1ebfd3a7e95842091b692c5560ba3d6788484901bf32b59bc","sha256:86f6e041a7bbf05cf89be64fa1074fd2100fecf8fa89f577ae438516678141d1"],"state_sha256":"389a1265d2944048bd80136173c7281745fc3dbbee2226d9581a5731a144825b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1a37tEPB9w1aHK7xHFBjrzD9/kUAfponXzhGg9SO9VdHT+uaAaWr1djgpxNe4cgQ1FEVC/7o00b5ztoSsloaAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T01:09:05.033392Z","bundle_sha256":"458730c308d9308aa1a4dfd507a59e36e3dc595f0808e632e151804de5ac56ea"}}