{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:NIQJKH4O23223KLG5SP4LFDAAT","short_pith_number":"pith:NIQJKH4O","canonical_record":{"source":{"id":"2110.08021","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-15T11:32:17Z","cross_cats_sorted":["cs.CL","cs.MM"],"title_canon_sha256":"a6a97d340b10cc868e123beaec3c27fc19b310a18cd1a846fe465411bd2c54d7","abstract_canon_sha256":"9bc810f95c6d2829ff62b92beda78a311cad8e6d4b5a03daa5b1384e9bf9207b"},"schema_version":"1.0"},"canonical_sha256":"6a20951f8ed6f5ada966ec9fc5946004e6ced4d37c0d5cafd23c617953020ea5","source":{"kind":"arxiv","id":"2110.08021","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.08021","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2110.08021v2","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.08021","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"NIQJKH4O2322","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"NIQJKH4O23223KLG","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"NIQJKH4O","created_at":"2026-07-05T07:47:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:NIQJKH4O23223KLG5SP4LFDAAT","target":"record","payload":{"canonical_record":{"source":{"id":"2110.08021","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-15T11:32:17Z","cross_cats_sorted":["cs.CL","cs.MM"],"title_canon_sha256":"a6a97d340b10cc868e123beaec3c27fc19b310a18cd1a846fe465411bd2c54d7","abstract_canon_sha256":"9bc810f95c6d2829ff62b92beda78a311cad8e6d4b5a03daa5b1384e9bf9207b"},"schema_version":"1.0"},"canonical_sha256":"6a20951f8ed6f5ada966ec9fc5946004e6ced4d37c0d5cafd23c617953020ea5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:47:52.600957Z","signature_b64":"Ad6Dn8iOsuPQRRJc+Ye3cLAslkrrKsF4Y61p6vjrXMfBl5fMsU7ugV/ZGbFww5inyPQuf2IPdrucXKUsErfDCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a20951f8ed6f5ada966ec9fc5946004e6ced4d37c0d5cafd23c617953020ea5","last_reissued_at":"2026-07-05T07:47:52.600439Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:47:52.600439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.08021","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LPjdlO1XrqC43fWV5hdRi9uRVgDhAIgYoFVxewtLQIXy7sQm2scT+10wTRhiQbsixeqafY5zmG7x9aDGTSSUDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T16:46:15.748798Z"},"content_sha256":"25b455bb2831fe656629f9f427894dc462ffe681c32a15aaa739bedf3c5be9e3","schema_version":"1.0","event_id":"sha256:25b455bb2831fe656629f9f427894dc462ffe681c32a15aaa739bedf3c5be9e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:NIQJKH4O23223KLG5SP4LFDAAT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.MM"],"primary_cat":"cs.LG","authors_text":"2), (2) Universit\\'e Paris-Saclay, C\\'eline Hudelot (2) ((1) Institut de Recherche Technologique SystemX, CentraleSup\\'elec, Michel Batteux (1), MICS), Myriam Tami (2), Victor Pellegrain (1","submitted_at":"2021-10-15T11:32:17Z","abstract_excerpt":"The increasing complexity of Industry 4.0 systems brings new challenges regarding predictive maintenance tasks such as fault detection and diagnosis. A corresponding and realistic setting includes multi-source data streams from different modalities, such as sensors measurements time series, machine images, textual maintenance reports, etc. These heterogeneous multimodal streams also differ in their acquisition frequency, may embed temporally unaligned information and can be arbitrarily long, depending on the considered system and task. Whereas multimodal fusion has been largely studied in a st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.08021","kind":"arxiv","version":2},"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/2110.08021/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":"2026-07-05T07:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TuWtjT01IafBTYbAmssjGlsXRg4zQxfsomVgXbmdZjybfQ+F1Ife+q14eAqswcDYrYoqrwcCsoT4Uc9txPYPDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T16:46:15.749180Z"},"content_sha256":"1386824c5b9a346c4aac7b31a03afae92d6f4e87a4ef6182184c67327b402cbd","schema_version":"1.0","event_id":"sha256:1386824c5b9a346c4aac7b31a03afae92d6f4e87a4ef6182184c67327b402cbd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NIQJKH4O23223KLG5SP4LFDAAT/bundle.json","state_url":"https://pith.science/pith/NIQJKH4O23223KLG5SP4LFDAAT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NIQJKH4O23223KLG5SP4LFDAAT/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":"2026-07-12T16:46:15Z","links":{"resolver":"https://pith.science/pith/NIQJKH4O23223KLG5SP4LFDAAT","bundle":"https://pith.science/pith/NIQJKH4O23223KLG5SP4LFDAAT/bundle.json","state":"https://pith.science/pith/NIQJKH4O23223KLG5SP4LFDAAT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NIQJKH4O23223KLG5SP4LFDAAT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:NIQJKH4O23223KLG5SP4LFDAAT","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":"9bc810f95c6d2829ff62b92beda78a311cad8e6d4b5a03daa5b1384e9bf9207b","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-15T11:32:17Z","title_canon_sha256":"a6a97d340b10cc868e123beaec3c27fc19b310a18cd1a846fe465411bd2c54d7"},"schema_version":"1.0","source":{"id":"2110.08021","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.08021","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2110.08021v2","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.08021","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"NIQJKH4O2322","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"NIQJKH4O23223KLG","created_at":"2026-07-05T07:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"NIQJKH4O","created_at":"2026-07-05T07:47:52Z"}],"graph_snapshots":[{"event_id":"sha256:1386824c5b9a346c4aac7b31a03afae92d6f4e87a4ef6182184c67327b402cbd","target":"graph","created_at":"2026-07-05T07:47:52Z","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/2110.08021/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The increasing complexity of Industry 4.0 systems brings new challenges regarding predictive maintenance tasks such as fault detection and diagnosis. A corresponding and realistic setting includes multi-source data streams from different modalities, such as sensors measurements time series, machine images, textual maintenance reports, etc. These heterogeneous multimodal streams also differ in their acquisition frequency, may embed temporally unaligned information and can be arbitrarily long, depending on the considered system and task. Whereas multimodal fusion has been largely studied in a st","authors_text":"2), (2) Universit\\'e Paris-Saclay, C\\'eline Hudelot (2) ((1) Institut de Recherche Technologique SystemX, CentraleSup\\'elec, Michel Batteux (1), MICS), Myriam Tami (2), Victor Pellegrain (1","cross_cats":["cs.CL","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-15T11:32:17Z","title":"StreaMulT: Streaming Multimodal Transformer for Heterogeneous and Arbitrary Long Sequential Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.08021","kind":"arxiv","version":2},"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":"sha256:25b455bb2831fe656629f9f427894dc462ffe681c32a15aaa739bedf3c5be9e3","target":"record","created_at":"2026-07-05T07:47:52Z","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":"9bc810f95c6d2829ff62b92beda78a311cad8e6d4b5a03daa5b1384e9bf9207b","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-15T11:32:17Z","title_canon_sha256":"a6a97d340b10cc868e123beaec3c27fc19b310a18cd1a846fe465411bd2c54d7"},"schema_version":"1.0","source":{"id":"2110.08021","kind":"arxiv","version":2}},"canonical_sha256":"6a20951f8ed6f5ada966ec9fc5946004e6ced4d37c0d5cafd23c617953020ea5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a20951f8ed6f5ada966ec9fc5946004e6ced4d37c0d5cafd23c617953020ea5","first_computed_at":"2026-07-05T07:47:52.600439Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:47:52.600439Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ad6Dn8iOsuPQRRJc+Ye3cLAslkrrKsF4Y61p6vjrXMfBl5fMsU7ugV/ZGbFww5inyPQuf2IPdrucXKUsErfDCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:47:52.600957Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.08021","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25b455bb2831fe656629f9f427894dc462ffe681c32a15aaa739bedf3c5be9e3","sha256:1386824c5b9a346c4aac7b31a03afae92d6f4e87a4ef6182184c67327b402cbd"],"state_sha256":"e0488d3c5918db328e768116c2ba50bb3a2c0f0f4b6e4024045a7a6c4d02fbb0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bw/iqjrpmp2mmvLQ5TgeaB85cNDC3FJ/FdP7KZ3gdPdhgTBJL9tWvcdvJt5YIUfh0fqYuKSd8c8mIjnqr+6yBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T16:46:15.751617Z","bundle_sha256":"49a81b5f9e18b27b2ecad438f598d2c9e6f5bda03a3b71a5f3076463ad8c83d4"}}