{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5XIMMDEOXAMERNOV6ONYLFVHVF","short_pith_number":"pith:5XIMMDEO","canonical_record":{"source":{"id":"2605.25110","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-24T14:49:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"e8a3d4b573585332c47fbc6503a478bb49cf0645346c2a14c4bcc2538e9cf122","abstract_canon_sha256":"bc9c5b967eb92035ab4ed58f027f677b4091ba17f2b7f3258ff8e0ea727ca48d"},"schema_version":"1.0"},"canonical_sha256":"edd0c60c8eb81848b5d5f39b8596a7a961bafe8e9298be40d9771a1e93b5bffc","source":{"kind":"arxiv","id":"2605.25110","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25110","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25110v1","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25110","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_12","alias_value":"5XIMMDEOXAME","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_16","alias_value":"5XIMMDEOXAMERNOV","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_8","alias_value":"5XIMMDEO","created_at":"2026-05-26T02:04:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5XIMMDEOXAMERNOV6ONYLFVHVF","target":"record","payload":{"canonical_record":{"source":{"id":"2605.25110","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-24T14:49:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"e8a3d4b573585332c47fbc6503a478bb49cf0645346c2a14c4bcc2538e9cf122","abstract_canon_sha256":"bc9c5b967eb92035ab4ed58f027f677b4091ba17f2b7f3258ff8e0ea727ca48d"},"schema_version":"1.0"},"canonical_sha256":"edd0c60c8eb81848b5d5f39b8596a7a961bafe8e9298be40d9771a1e93b5bffc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:04:18.474574Z","signature_b64":"C/kppoabYsG5CagYfEJQZoO6Xy7BNnEFmmDL93dCZ5ti/L35H3fFMz48vIz9i91OWHaHs02RCcUFlta/u9nPDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"edd0c60c8eb81848b5d5f39b8596a7a961bafe8e9298be40d9771a1e93b5bffc","last_reissued_at":"2026-05-26T02:04:18.473636Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:04:18.473636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.25110","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":"2026-05-26T02:04:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8+u65E+R75GNfC49/mhC/roihwiP3WjyGKTt1eJv4lLNyEkrPIuYDUp6rziotFKpuLu6U4GPANeOYB1g9YHdCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T03:32:15.223596Z"},"content_sha256":"42a83e1328391e0ec2e0373c0d9a1045fdcba2145931f51aa255599301a5a2b9","schema_version":"1.0","event_id":"sha256:42a83e1328391e0ec2e0373c0d9a1045fdcba2145931f51aa255599301a5a2b9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5XIMMDEOXAMERNOV6ONYLFVHVF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Uncertainty-DTW for Sequences and Visual Tokens","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Lei Wang, Piotr Koniusz, Syuan-Hao Li, Yongsheng Gao","submitted_at":"2026-05-24T14:49:43Z","abstract_excerpt":"Aligning structured data is a fundamental problem in computer vision and machine learning, underlying tasks such as time series analysis, human action recognition, and visual representation learning. Existing alignment methods, including Dynamic Time Warping (DTW) and its differentiable variants, rely on deterministic similarity measures and are therefore sensitive to heterogeneous and noisy features. In this work, we introduce uncertainty-aware alignment, a probabilistic framework that models pairwise correspondences with heteroscedastic uncertainty and performs structured matching along alig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25110","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/2605.25110/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":"2026-05-26T02:04:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8NmfXDVYXmBgn9XKW3MNR71U4HBFCGr6Fa4DUvR0bGbwt6ca/+AI6vbhCl7nA8HvU6ASOsTpbG9h6YDfBAvjAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T03:32:15.224329Z"},"content_sha256":"8555b12133a46dbeddebc266882bc921f807ed07c8cdd6b28e42732119f32aab","schema_version":"1.0","event_id":"sha256:8555b12133a46dbeddebc266882bc921f807ed07c8cdd6b28e42732119f32aab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/bundle.json","state_url":"https://pith.science/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/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":"2026-05-31T03:32:15Z","links":{"resolver":"https://pith.science/pith/5XIMMDEOXAMERNOV6ONYLFVHVF","bundle":"https://pith.science/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/bundle.json","state":"https://pith.science/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5XIMMDEOXAMERNOV6ONYLFVHVF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5XIMMDEOXAMERNOV6ONYLFVHVF","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":"bc9c5b967eb92035ab4ed58f027f677b4091ba17f2b7f3258ff8e0ea727ca48d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-24T14:49:43Z","title_canon_sha256":"e8a3d4b573585332c47fbc6503a478bb49cf0645346c2a14c4bcc2538e9cf122"},"schema_version":"1.0","source":{"id":"2605.25110","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25110","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25110v1","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25110","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_12","alias_value":"5XIMMDEOXAME","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_16","alias_value":"5XIMMDEOXAMERNOV","created_at":"2026-05-26T02:04:18Z"},{"alias_kind":"pith_short_8","alias_value":"5XIMMDEO","created_at":"2026-05-26T02:04:18Z"}],"graph_snapshots":[{"event_id":"sha256:8555b12133a46dbeddebc266882bc921f807ed07c8cdd6b28e42732119f32aab","target":"graph","created_at":"2026-05-26T02:04:18Z","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/2605.25110/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aligning structured data is a fundamental problem in computer vision and machine learning, underlying tasks such as time series analysis, human action recognition, and visual representation learning. Existing alignment methods, including Dynamic Time Warping (DTW) and its differentiable variants, rely on deterministic similarity measures and are therefore sensitive to heterogeneous and noisy features. In this work, we introduce uncertainty-aware alignment, a probabilistic framework that models pairwise correspondences with heteroscedastic uncertainty and performs structured matching along alig","authors_text":"Lei Wang, Piotr Koniusz, Syuan-Hao Li, Yongsheng Gao","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-24T14:49:43Z","title":"Uncertainty-DTW for Sequences and Visual Tokens"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25110","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":"sha256:42a83e1328391e0ec2e0373c0d9a1045fdcba2145931f51aa255599301a5a2b9","target":"record","created_at":"2026-05-26T02:04:18Z","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":"bc9c5b967eb92035ab4ed58f027f677b4091ba17f2b7f3258ff8e0ea727ca48d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-24T14:49:43Z","title_canon_sha256":"e8a3d4b573585332c47fbc6503a478bb49cf0645346c2a14c4bcc2538e9cf122"},"schema_version":"1.0","source":{"id":"2605.25110","kind":"arxiv","version":1}},"canonical_sha256":"edd0c60c8eb81848b5d5f39b8596a7a961bafe8e9298be40d9771a1e93b5bffc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"edd0c60c8eb81848b5d5f39b8596a7a961bafe8e9298be40d9771a1e93b5bffc","first_computed_at":"2026-05-26T02:04:18.473636Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:18.473636Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"C/kppoabYsG5CagYfEJQZoO6Xy7BNnEFmmDL93dCZ5ti/L35H3fFMz48vIz9i91OWHaHs02RCcUFlta/u9nPDQ==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:18.474574Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.25110","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42a83e1328391e0ec2e0373c0d9a1045fdcba2145931f51aa255599301a5a2b9","sha256:8555b12133a46dbeddebc266882bc921f807ed07c8cdd6b28e42732119f32aab"],"state_sha256":"2eb2e4b94bb8c0eabbc34a5ea420dcf2492da5c9d90334470834e8b9ce795bb6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SDmvKT8oU0HPuWsSYst1MpNzFkQ40KU34+s0R1BFVvVS8jHPu850UxgxoKhc0Dpwp/W8gEUYRUOpucrQ1BuQAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T03:32:15.227851Z","bundle_sha256":"3e05387d165caca4440388ba10fe4806d1a7843cd8afde0d637e23dbb6a7bd3e"}}