{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WNUMPSP3PYHXATVPQHGA2LZJAD","short_pith_number":"pith:WNUMPSP3","canonical_record":{"source":{"id":"2605.20606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-20T01:49:39Z","cross_cats_sorted":[],"title_canon_sha256":"b9ac42e8b222f47b8a3d75a27fe563aa2892082d757ed6445f0422e6bdd3c82f","abstract_canon_sha256":"23385aadd46ee297d8d77a540966d620460ec12403afc9e00827541496ab696f"},"schema_version":"1.0"},"canonical_sha256":"b368c7c9fb7e0f704eaf81cc0d2f2900da99c944a3983338c8b2b6355fcf88a0","source":{"kind":"arxiv","id":"2605.20606","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20606","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20606v1","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20606","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"WNUMPSP3PYHX","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_16","alias_value":"WNUMPSP3PYHXATVP","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_8","alias_value":"WNUMPSP3","created_at":"2026-05-21T01:04:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WNUMPSP3PYHXATVPQHGA2LZJAD","target":"record","payload":{"canonical_record":{"source":{"id":"2605.20606","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-20T01:49:39Z","cross_cats_sorted":[],"title_canon_sha256":"b9ac42e8b222f47b8a3d75a27fe563aa2892082d757ed6445f0422e6bdd3c82f","abstract_canon_sha256":"23385aadd46ee297d8d77a540966d620460ec12403afc9e00827541496ab696f"},"schema_version":"1.0"},"canonical_sha256":"b368c7c9fb7e0f704eaf81cc0d2f2900da99c944a3983338c8b2b6355fcf88a0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:04:44.328468Z","signature_b64":"MPNb+qYx2E4KPL9qhCsFdmzvidS6A4B9pj2hUHhTCOtQdQVnHSPJNbjBytz9VUmqvFGliMgFVyhB7xq7qyX6Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b368c7c9fb7e0f704eaf81cc0d2f2900da99c944a3983338c8b2b6355fcf88a0","last_reissued_at":"2026-05-21T01:04:44.327811Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:04:44.327811Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.20606","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-21T01:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h0q4NRKdqLK3ms7oJD09eQ7VzMZ5rzJ+UF+nwlRokXgQq7pmri/jphZNQI6Xw2guBE/TdB5t/UYuqgJNb30jCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T18:38:27.834988Z"},"content_sha256":"f1ccc781b97da34baea25375a2cd0c7ba3a90e7b4bf6ede3e38a7056705eec9d","schema_version":"1.0","event_id":"sha256:f1ccc781b97da34baea25375a2cd0c7ba3a90e7b4bf6ede3e38a7056705eec9d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WNUMPSP3PYHXATVPQHGA2LZJAD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hang Gou, Ke Qin, Ming Li, Muquan Li, Tao He, Yihong Huang, Yingyi Ma, Yuan-Fang Li","submitted_at":"2026-05-20T01:49:39Z","abstract_excerpt":"Dataset distillation (DD) compresses a large training set into a small synthetic set for efficient training, but most DD methods optimize only clean accuracy and leave robustness uncontrolled. Recent robust DD methods improve robustness, yet they often suffer from a poor accuracy-robustness trade-off because they (i) treat all adversarially perturbed examples uniformly, despite robust risk being dominated by near-zero robust margins, and (ii) do not explicitly increase inter-class separation in the decision boundary where attacks concentrate. We present Contrastive Curriculum for Robust Datase"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20606","kind":"arxiv","version":1},"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/2605.20606/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":"2026-05-21T01:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C1WaSFzTbm+Bm51KmqKVHO53sJTc6sDnLuGx206NpIu5EPZbiRQnkJIVVtwnDzrpeotGkQzYT0yMdHa2Gh8XAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T18:38:27.835381Z"},"content_sha256":"215574ef501f670374ee3cb33bc791c7a8e128ffacda6c7d0fbc3bd0fc1893a0","schema_version":"1.0","event_id":"sha256:215574ef501f670374ee3cb33bc791c7a8e128ffacda6c7d0fbc3bd0fc1893a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/bundle.json","state_url":"https://pith.science/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/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":"2026-05-22T18:38:27Z","links":{"resolver":"https://pith.science/pith/WNUMPSP3PYHXATVPQHGA2LZJAD","bundle":"https://pith.science/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/bundle.json","state":"https://pith.science/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WNUMPSP3PYHXATVPQHGA2LZJAD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WNUMPSP3PYHXATVPQHGA2LZJAD","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":"23385aadd46ee297d8d77a540966d620460ec12403afc9e00827541496ab696f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-20T01:49:39Z","title_canon_sha256":"b9ac42e8b222f47b8a3d75a27fe563aa2892082d757ed6445f0422e6bdd3c82f"},"schema_version":"1.0","source":{"id":"2605.20606","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20606","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20606v1","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20606","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"WNUMPSP3PYHX","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_16","alias_value":"WNUMPSP3PYHXATVP","created_at":"2026-05-21T01:04:44Z"},{"alias_kind":"pith_short_8","alias_value":"WNUMPSP3","created_at":"2026-05-21T01:04:44Z"}],"graph_snapshots":[{"event_id":"sha256:215574ef501f670374ee3cb33bc791c7a8e128ffacda6c7d0fbc3bd0fc1893a0","target":"graph","created_at":"2026-05-21T01:04:44Z","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/2605.20606/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dataset distillation (DD) compresses a large training set into a small synthetic set for efficient training, but most DD methods optimize only clean accuracy and leave robustness uncontrolled. Recent robust DD methods improve robustness, yet they often suffer from a poor accuracy-robustness trade-off because they (i) treat all adversarially perturbed examples uniformly, despite robust risk being dominated by near-zero robust margins, and (ii) do not explicitly increase inter-class separation in the decision boundary where attacks concentrate. We present Contrastive Curriculum for Robust Datase","authors_text":"Hang Gou, Ke Qin, Ming Li, Muquan Li, Tao He, Yihong Huang, Yingyi Ma, Yuan-Fang Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-20T01:49:39Z","title":"Mind Your Margin and Boundary: Are Your Distilled Datasets Truly Robust?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20606","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:f1ccc781b97da34baea25375a2cd0c7ba3a90e7b4bf6ede3e38a7056705eec9d","target":"record","created_at":"2026-05-21T01:04:44Z","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":"23385aadd46ee297d8d77a540966d620460ec12403afc9e00827541496ab696f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-20T01:49:39Z","title_canon_sha256":"b9ac42e8b222f47b8a3d75a27fe563aa2892082d757ed6445f0422e6bdd3c82f"},"schema_version":"1.0","source":{"id":"2605.20606","kind":"arxiv","version":1}},"canonical_sha256":"b368c7c9fb7e0f704eaf81cc0d2f2900da99c944a3983338c8b2b6355fcf88a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b368c7c9fb7e0f704eaf81cc0d2f2900da99c944a3983338c8b2b6355fcf88a0","first_computed_at":"2026-05-21T01:04:44.327811Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T01:04:44.327811Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MPNb+qYx2E4KPL9qhCsFdmzvidS6A4B9pj2hUHhTCOtQdQVnHSPJNbjBytz9VUmqvFGliMgFVyhB7xq7qyX6Cw==","signature_status":"signed_v1","signed_at":"2026-05-21T01:04:44.328468Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.20606","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1ccc781b97da34baea25375a2cd0c7ba3a90e7b4bf6ede3e38a7056705eec9d","sha256:215574ef501f670374ee3cb33bc791c7a8e128ffacda6c7d0fbc3bd0fc1893a0"],"state_sha256":"4c6cc775e5357642b4647ef0353d6555ee469ed21cd12edd7d25f6515890fef0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dd80kTjvzQAnqW55g9EanVq4HwMjD1rMtyMzJWVB9OA8QYJkXYrP+CeiDy0jQXGqtBwGlpDftBqII2F6bqoNBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T18:38:27.837513Z","bundle_sha256":"d8d57b3ca2792e36ca0868107fe0845d8e658c29ca35d4d1b0d02c81be99072b"}}