{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3FFBPGSXWV7WZRVVQ3NP2FG42K","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":"698fc0c82417de64eb084d0831a06db7713fe41cb4381504c624d7baf3dc7f21","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-11T10:17:32Z","title_canon_sha256":"e23c62470369b7a44a7a0aa3c0b1b093fb0f2e486fd903e3f3d3bca0875e11eb"},"schema_version":"1.0","source":{"id":"2503.08253","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.08253","created_at":"2026-07-05T10:28:54Z"},{"alias_kind":"arxiv_version","alias_value":"2503.08253v1","created_at":"2026-07-05T10:28:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.08253","created_at":"2026-07-05T10:28:54Z"},{"alias_kind":"pith_short_12","alias_value":"3FFBPGSXWV7W","created_at":"2026-07-05T10:28:54Z"},{"alias_kind":"pith_short_16","alias_value":"3FFBPGSXWV7WZRVV","created_at":"2026-07-05T10:28:54Z"},{"alias_kind":"pith_short_8","alias_value":"3FFBPGSX","created_at":"2026-07-05T10:28:54Z"}],"graph_snapshots":[{"event_id":"sha256:29dcbe61a2bed0a96b9d8fdf86db59c2dc5cdd5e960b67aa99697d80b0a3c174","target":"graph","created_at":"2026-07-05T10:28:54Z","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/2503.08253/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Modern diffusion models encounter a fundamental trade-off between training efficiency and generation quality. While existing representation alignment methods, such as REPA, accelerate convergence through patch-wise alignment, they often fail to capture structural relationships within visual representations and ensure global distribution consistency between pretrained encoders and denoising networks. To address these limitations, we introduce SARA, a hierarchical alignment framework that enforces multi-level representation constraints: (1) patch-wise alignment to preserve local semantic details","authors_text":"Hao Li, Hesen Chen, Junyan Wang, Zhiyu Tan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-11T10:17:32Z","title":"SARA: Structural and Adversarial Representation Alignment for Training-efficient Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.08253","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:f9ca9e7bdd9b371fbd1344201849f318cea87e54852dc25c1405872d6fa496af","target":"record","created_at":"2026-07-05T10:28:54Z","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":"698fc0c82417de64eb084d0831a06db7713fe41cb4381504c624d7baf3dc7f21","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-11T10:17:32Z","title_canon_sha256":"e23c62470369b7a44a7a0aa3c0b1b093fb0f2e486fd903e3f3d3bca0875e11eb"},"schema_version":"1.0","source":{"id":"2503.08253","kind":"arxiv","version":1}},"canonical_sha256":"d94a179a57b57f6cc6b586dafd14dcd2beed673740046d712e1f65a441e81156","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d94a179a57b57f6cc6b586dafd14dcd2beed673740046d712e1f65a441e81156","first_computed_at":"2026-07-05T10:28:54.764846Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:28:54.764846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s4TT4drwNuHil+jMCAJws2OGyQh4JvSxoEJujK6Rg35gWQtHZ478bqS2jFPPslwcVKaXimdDKBk5D7jbnUBbAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:28:54.765443Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.08253","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9ca9e7bdd9b371fbd1344201849f318cea87e54852dc25c1405872d6fa496af","sha256:29dcbe61a2bed0a96b9d8fdf86db59c2dc5cdd5e960b67aa99697d80b0a3c174"],"state_sha256":"6b7a1e3f782f00b5c22883f0cec1c009e7e94f7686f91aefcb107a7750dce32a"}