{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:KJXX6MUTAA5VCSSYXVAE6GRREI","short_pith_number":"pith:KJXX6MUT","canonical_record":{"source":{"id":"2605.22540","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2026-05-21T14:25:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"86b9aa5fd80af3270a22afc7b9364af6976694e4a8a53f855116ebd673f276a5","abstract_canon_sha256":"a92d28a0f7c1f37eacf9cb3bed628ba148e3d2c589af73d7199d9bcad92e5946"},"schema_version":"1.0"},"canonical_sha256":"526f7f3293003b514a58bd404f1a31221fad6f321a9e25afa734cccddfc652ab","source":{"kind":"arxiv","id":"2605.22540","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.22540","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"arxiv_version","alias_value":"2605.22540v1","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.22540","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_12","alias_value":"KJXX6MUTAA5V","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_16","alias_value":"KJXX6MUTAA5VCSSY","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_8","alias_value":"KJXX6MUT","created_at":"2026-05-22T01:04:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:KJXX6MUTAA5VCSSYXVAE6GRREI","target":"record","payload":{"canonical_record":{"source":{"id":"2605.22540","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2026-05-21T14:25:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"86b9aa5fd80af3270a22afc7b9364af6976694e4a8a53f855116ebd673f276a5","abstract_canon_sha256":"a92d28a0f7c1f37eacf9cb3bed628ba148e3d2c589af73d7199d9bcad92e5946"},"schema_version":"1.0"},"canonical_sha256":"526f7f3293003b514a58bd404f1a31221fad6f321a9e25afa734cccddfc652ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:04:56.394737Z","signature_b64":"DZLRB6IqLwBJJbmvfMCB7AV+dYy+vD2rC97RljZNlobpwBlr0Rw5ejctz/dIRpJNqm8RehH1FePtyBlNRIaUAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"526f7f3293003b514a58bd404f1a31221fad6f321a9e25afa734cccddfc652ab","last_reissued_at":"2026-05-22T01:04:56.393779Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:04:56.393779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.22540","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":"2026-05-22T01:04:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MVQh3axfGETFjojMX3wBDhf39aXFCZg4RwgaK9FDYjo6W6vRtSWmr4U2dWqanrDIL6IhhcSS0OhNu/NIioazDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:14:03.973033Z"},"content_sha256":"f0e6eb4e0767790c5f445a0a4cecd785e1cc856b29f1264ff232bfe8c31444a2","schema_version":"1.0","event_id":"sha256:f0e6eb4e0767790c5f445a0a4cecd785e1cc856b29f1264ff232bfe8c31444a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:KJXX6MUTAA5VCSSYXVAE6GRREI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dynamic Hypergraph Representation Learning for Multivariate Time Series without Prior Knowledge","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CE","authors_text":"Giorgio Gnecco, Johannes De Smedt, Marco Gregnanin, Maurizio Parton","submitted_at":"2026-05-21T14:25:51Z","abstract_excerpt":"Hypergraphs have the capacity to capture higher-dimensional relationships among entities across various domains, making them a subject of growing interest within the research community for understanding the structure and dynamics of complex systems. However, a key challenge is the derivation of hypergraph representations from time series data in situations where the structure of the hypergraph is limited or absent. In this study, we propose a model that constructs a dynamic hypergraph representation for multivariate time series without relying on prior knowledge of the data. This is achieved b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22540","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/2605.22540/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":"2026-05-22T01:04:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bmiYbofvfJ4mgS2xGnC3XcjaFYR0L00cA4WPYYWTt7/a5boy/Zz+CQkwM/BItWbhlOXqETdPZpw9g10nJ8V4AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:14:03.973797Z"},"content_sha256":"d28d5130eb32e440c06ca246b6eccac2a52029102e3b1065b1da0e41d0a06895","schema_version":"1.0","event_id":"sha256:d28d5130eb32e440c06ca246b6eccac2a52029102e3b1065b1da0e41d0a06895"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/bundle.json","state_url":"https://pith.science/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/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":"2026-05-26T19:14:03Z","links":{"resolver":"https://pith.science/pith/KJXX6MUTAA5VCSSYXVAE6GRREI","bundle":"https://pith.science/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/bundle.json","state":"https://pith.science/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KJXX6MUTAA5VCSSYXVAE6GRREI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KJXX6MUTAA5VCSSYXVAE6GRREI","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":"a92d28a0f7c1f37eacf9cb3bed628ba148e3d2c589af73d7199d9bcad92e5946","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2026-05-21T14:25:51Z","title_canon_sha256":"86b9aa5fd80af3270a22afc7b9364af6976694e4a8a53f855116ebd673f276a5"},"schema_version":"1.0","source":{"id":"2605.22540","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.22540","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"arxiv_version","alias_value":"2605.22540v1","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.22540","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_12","alias_value":"KJXX6MUTAA5V","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_16","alias_value":"KJXX6MUTAA5VCSSY","created_at":"2026-05-22T01:04:56Z"},{"alias_kind":"pith_short_8","alias_value":"KJXX6MUT","created_at":"2026-05-22T01:04:56Z"}],"graph_snapshots":[{"event_id":"sha256:d28d5130eb32e440c06ca246b6eccac2a52029102e3b1065b1da0e41d0a06895","target":"graph","created_at":"2026-05-22T01:04:56Z","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/2605.22540/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hypergraphs have the capacity to capture higher-dimensional relationships among entities across various domains, making them a subject of growing interest within the research community for understanding the structure and dynamics of complex systems. However, a key challenge is the derivation of hypergraph representations from time series data in situations where the structure of the hypergraph is limited or absent. In this study, we propose a model that constructs a dynamic hypergraph representation for multivariate time series without relying on prior knowledge of the data. This is achieved b","authors_text":"Giorgio Gnecco, Johannes De Smedt, Marco Gregnanin, Maurizio Parton","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2026-05-21T14:25:51Z","title":"Dynamic Hypergraph Representation Learning for Multivariate Time Series without Prior Knowledge"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22540","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:f0e6eb4e0767790c5f445a0a4cecd785e1cc856b29f1264ff232bfe8c31444a2","target":"record","created_at":"2026-05-22T01:04:56Z","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":"a92d28a0f7c1f37eacf9cb3bed628ba148e3d2c589af73d7199d9bcad92e5946","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2026-05-21T14:25:51Z","title_canon_sha256":"86b9aa5fd80af3270a22afc7b9364af6976694e4a8a53f855116ebd673f276a5"},"schema_version":"1.0","source":{"id":"2605.22540","kind":"arxiv","version":1}},"canonical_sha256":"526f7f3293003b514a58bd404f1a31221fad6f321a9e25afa734cccddfc652ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"526f7f3293003b514a58bd404f1a31221fad6f321a9e25afa734cccddfc652ab","first_computed_at":"2026-05-22T01:04:56.393779Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T01:04:56.393779Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DZLRB6IqLwBJJbmvfMCB7AV+dYy+vD2rC97RljZNlobpwBlr0Rw5ejctz/dIRpJNqm8RehH1FePtyBlNRIaUAg==","signature_status":"signed_v1","signed_at":"2026-05-22T01:04:56.394737Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.22540","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f0e6eb4e0767790c5f445a0a4cecd785e1cc856b29f1264ff232bfe8c31444a2","sha256:d28d5130eb32e440c06ca246b6eccac2a52029102e3b1065b1da0e41d0a06895"],"state_sha256":"b6efeae7be472ca5badc8083ed7ada8070c290659e37ed550d8483f3ce82970e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7o/OTSnJdvrb1rh9+c/HyRPJqGeSjCkb2EdngEm8+IAHO+XFtV8GJwqQ4ATyIhAaMiCCrneWCLo30kRZ3PmgCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T19:14:03.977901Z","bundle_sha256":"cd904426a3143e8fbcc3d5dee23b72fda714c3be16362411e7c266a618cb24db"}}