{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SDYWGEYXEQIEEWDVJKJYBRIZGW","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":"edbe746be230fe80c541717b200a370a9aa843f5364ac575d8719c798db3aa98","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-10-02T01:23:32Z","title_canon_sha256":"dd7a9467eb3b6b0d14612b13e3879e042c31d254e570912c01d9fcbd53156d9a"},"schema_version":"1.0","source":{"id":"2510.01565","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.01565","created_at":"2026-06-19T16:12:15Z"},{"alias_kind":"arxiv_version","alias_value":"2510.01565v4","created_at":"2026-06-19T16:12:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.01565","created_at":"2026-06-19T16:12:15Z"},{"alias_kind":"pith_short_12","alias_value":"SDYWGEYXEQIE","created_at":"2026-06-19T16:12:15Z"},{"alias_kind":"pith_short_16","alias_value":"SDYWGEYXEQIEEWDV","created_at":"2026-06-19T16:12:15Z"},{"alias_kind":"pith_short_8","alias_value":"SDYWGEYX","created_at":"2026-06-19T16:12:15Z"}],"graph_snapshots":[{"event_id":"sha256:b4c7c90ea6aa848f9b4ae7ea37e2e5e89ad5c06dd86dbc1a2d0b4ac4e0593eeb","target":"graph","created_at":"2026-06-19T16:12:15Z","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/2510.01565/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion Transformer (DiT) models excel at generating high-quality images through iterative denoising steps, but serving them under strict Service Level Objectives (SLOs) is challenging due to their high computational cost, particularly at larger resolutions. Existing serving systems use fixed-degree sequence parallelism, which is inefficient for heterogeneous workloads with mixed resolutions and deadlines, leading to poor GPU utilization and low SLO attainment.\n  In this paper, we propose step-level sequence parallelism to dynamically adjust the degree of parallelism of individual requests a","authors_text":"Ang Chen, Jeff J. Ma, Mosharaf Chowdhury, Runyu Lu, Ruofan Wu, Shenggui Li, Shiqi He, Wenxuan Tan","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-10-02T01:23:32Z","title":"TetriServe: Efficiently Serving Mixed DiT Workloads"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.01565","kind":"arxiv","version":4},"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":"sha256:021ffe37ee0b6908294a454e6728001e319203f930a6218423cab4e9d9f93844","target":"record","created_at":"2026-06-19T16:12:15Z","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":"edbe746be230fe80c541717b200a370a9aa843f5364ac575d8719c798db3aa98","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-10-02T01:23:32Z","title_canon_sha256":"dd7a9467eb3b6b0d14612b13e3879e042c31d254e570912c01d9fcbd53156d9a"},"schema_version":"1.0","source":{"id":"2510.01565","kind":"arxiv","version":4}},"canonical_sha256":"90f163131724104258754a9380c519359fcb7e80b9c333d2f2831c04d944bebb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90f163131724104258754a9380c519359fcb7e80b9c333d2f2831c04d944bebb","first_computed_at":"2026-06-19T16:12:15.495503Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:15.495503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ye7milWq0L2T/dCW/7THnvLyWpnLXYYdngpGaaLL62X31c0YRNFXA95PZ4zIw8PX6el94cmG8577vTaDMcWPBQ==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:15.495939Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.01565","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:021ffe37ee0b6908294a454e6728001e319203f930a6218423cab4e9d9f93844","sha256:b4c7c90ea6aa848f9b4ae7ea37e2e5e89ad5c06dd86dbc1a2d0b4ac4e0593eeb"],"state_sha256":"f3aa242c578853413a28850cb41cece6e2f2528ac156028ea7650631d37f704f"}