{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5MMRIMHNHTH7F7QWHVZFSMC5QM","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":"30432b8aff992e3c084ef59c2d250785cc9be53064b846ed2d85d79e2078e558","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T06:24:53Z","title_canon_sha256":"fd9aad2ceee6cd5cf51aac2021497c27ccb6a0677ed8744ead0c94b6fa63b7a4"},"schema_version":"1.0","source":{"id":"2606.29837","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.29837","created_at":"2026-06-30T02:17:37Z"},{"alias_kind":"arxiv_version","alias_value":"2606.29837v1","created_at":"2026-06-30T02:17:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29837","created_at":"2026-06-30T02:17:37Z"},{"alias_kind":"pith_short_12","alias_value":"5MMRIMHNHTH7","created_at":"2026-06-30T02:17:37Z"},{"alias_kind":"pith_short_16","alias_value":"5MMRIMHNHTH7F7QW","created_at":"2026-06-30T02:17:37Z"},{"alias_kind":"pith_short_8","alias_value":"5MMRIMHN","created_at":"2026-06-30T02:17:37Z"}],"graph_snapshots":[{"event_id":"sha256:8581df190546ce094861707d86ea9e80b799be3b85b2975560a3272d80a70f18","target":"graph","created_at":"2026-06-30T02:17:37Z","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/2606.29837/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dataset distillation (DD) condenses large corpora into compact, information-rich subsets for efficient training and reuse. However, under noisy supervision, DD risks condensing corrupted associations together with useful signals, degrading robustness. Conventional noisy-label remedies (sample selection, loss weighting, label correction) tightly couple noise estimation with model optimization, often require clean anchors, and can amplify confirmation bias-assumptions that are misaligned with DD's goal of compact, plug-and-play supervision. We therefore propose a trajectory-based DD framework th","authors_text":"Fan Zhang, Jiyang Li, Kaifeng Chen, Lechao Cheng, Shengeng Tang, Tuanrui Hui, Yantao Pan, Yaxiong Wang, Zhun Zhong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T06:24:53Z","title":"Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29837","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":"sha256:6d7843047ad2e3168fc5816e4b47a292e437cce752066a9dadf626d2eae718d3","target":"record","created_at":"2026-06-30T02:17:37Z","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":"30432b8aff992e3c084ef59c2d250785cc9be53064b846ed2d85d79e2078e558","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T06:24:53Z","title_canon_sha256":"fd9aad2ceee6cd5cf51aac2021497c27ccb6a0677ed8744ead0c94b6fa63b7a4"},"schema_version":"1.0","source":{"id":"2606.29837","kind":"arxiv","version":1}},"canonical_sha256":"eb191430ed3ccff2fe163d7259305d8312bdd9872b8bcd36a84f8e236421cc8a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb191430ed3ccff2fe163d7259305d8312bdd9872b8bcd36a84f8e236421cc8a","first_computed_at":"2026-06-30T02:17:37.543557Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T02:17:37.543557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LTDm4WXsUm6T4Qf2QJBr7cwscMrxi5QHPh6vRREMM7OJhQ8SwzeNqBpwvnoJBE54jQlmn7wXYBfugG8quoPPBg==","signature_status":"signed_v1","signed_at":"2026-06-30T02:17:37.544008Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.29837","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6d7843047ad2e3168fc5816e4b47a292e437cce752066a9dadf626d2eae718d3","sha256:8581df190546ce094861707d86ea9e80b799be3b85b2975560a3272d80a70f18"],"state_sha256":"f2e4baa97a34b1e042de94212fa8c0989b0a566d1c48246f068e7cd1f4410350"}