{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UICIBPCUL37L5E6DPJYBMMOHAL","short_pith_number":"pith:UICIBPCU","canonical_record":{"source":{"id":"2412.10540","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-13T20:26:35Z","cross_cats_sorted":["q-fin.ST"],"title_canon_sha256":"1f06004e536f45e0902f35b53b1657092ace97939e7759ec711618ac9ca99e5b","abstract_canon_sha256":"9bd54a799b427949d611408f3ca5842b5b65a0a2b477069ed2557b24210d0a47"},"schema_version":"1.0"},"canonical_sha256":"a20480bc545efebe93c37a701631c702eea10ae70bb7a27aa5a20505454c295b","source":{"kind":"arxiv","id":"2412.10540","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.10540","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"arxiv_version","alias_value":"2412.10540v1","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.10540","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_12","alias_value":"UICIBPCUL37L","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_16","alias_value":"UICIBPCUL37L5E6D","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_8","alias_value":"UICIBPCU","created_at":"2026-07-05T09:49:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UICIBPCUL37L5E6DPJYBMMOHAL","target":"record","payload":{"canonical_record":{"source":{"id":"2412.10540","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-13T20:26:35Z","cross_cats_sorted":["q-fin.ST"],"title_canon_sha256":"1f06004e536f45e0902f35b53b1657092ace97939e7759ec711618ac9ca99e5b","abstract_canon_sha256":"9bd54a799b427949d611408f3ca5842b5b65a0a2b477069ed2557b24210d0a47"},"schema_version":"1.0"},"canonical_sha256":"a20480bc545efebe93c37a701631c702eea10ae70bb7a27aa5a20505454c295b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:17.467167Z","signature_b64":"lW2LsYGABaS+RLmSfNkOxMBoyPCr9wylD3olp9JY2BpMeeODSvHJUS9MgStGnMnkqACIlidbb0xVDbC4BCR6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a20480bc545efebe93c37a701631c702eea10ae70bb7a27aa5a20505454c295b","last_reissued_at":"2026-07-05T09:49:17.466711Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:17.466711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.10540","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":"2026-07-05T09:49:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8dzEqFlR1MU7FS0U7YE30VRioYhaEN9EFtiOiIM5Vs4h6dPVkGXj4NeOe7TbmKGaFJZ/KUPfmd9Oqi1RaM8NBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T22:00:57.232214Z"},"content_sha256":"aadea610e12602e41e8d4305e777735a5b4d407b284ac6388052e4d90c102c13","schema_version":"1.0","event_id":"sha256:aadea610e12602e41e8d4305e777735a5b4d407b284ac6388052e4d90c102c13"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UICIBPCUL37L5E6DPJYBMMOHAL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["q-fin.ST"],"primary_cat":"cs.LG","authors_text":"Guillaume Rabusseau, Reihaneh Rabbany, Soroush Omranpour","submitted_at":"2024-12-13T20:26:35Z","abstract_excerpt":"In this paper, we tackle the challenge of predicting stock movements in financial markets by introducing Higher Order Transformers, a novel architecture designed for processing multivariate time-series data. We extend the self-attention mechanism and the transformer architecture to a higher order, effectively capturing complex market dynamics across time and variables. To manage computational complexity, we propose a low-rank approximation of the potentially large attention tensor using tensor decomposition and employ kernel attention, reducing complexity to linear with respect to the data siz"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.10540","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/2412.10540/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":"2026-07-05T09:49:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5U8VsjpzX2gzX7R01BMpaoEyZVf3bPjSVxkfVPrSnt1EXw8NOv2XIU3eC1TBUHz5lV0tw4ibOPVMKmZXUFUxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T22:00:57.232857Z"},"content_sha256":"834b8cb398371cd8ca45e4b730f19cc9925d2aae4b5c234fd8d8b4ec6c9618cf","schema_version":"1.0","event_id":"sha256:834b8cb398371cd8ca45e4b730f19cc9925d2aae4b5c234fd8d8b4ec6c9618cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UICIBPCUL37L5E6DPJYBMMOHAL/bundle.json","state_url":"https://pith.science/pith/UICIBPCUL37L5E6DPJYBMMOHAL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UICIBPCUL37L5E6DPJYBMMOHAL/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":"2026-08-13T22:00:57Z","links":{"resolver":"https://pith.science/pith/UICIBPCUL37L5E6DPJYBMMOHAL","bundle":"https://pith.science/pith/UICIBPCUL37L5E6DPJYBMMOHAL/bundle.json","state":"https://pith.science/pith/UICIBPCUL37L5E6DPJYBMMOHAL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UICIBPCUL37L5E6DPJYBMMOHAL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UICIBPCUL37L5E6DPJYBMMOHAL","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":"9bd54a799b427949d611408f3ca5842b5b65a0a2b477069ed2557b24210d0a47","cross_cats_sorted":["q-fin.ST"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-13T20:26:35Z","title_canon_sha256":"1f06004e536f45e0902f35b53b1657092ace97939e7759ec711618ac9ca99e5b"},"schema_version":"1.0","source":{"id":"2412.10540","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.10540","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"arxiv_version","alias_value":"2412.10540v1","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.10540","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_12","alias_value":"UICIBPCUL37L","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_16","alias_value":"UICIBPCUL37L5E6D","created_at":"2026-07-05T09:49:17Z"},{"alias_kind":"pith_short_8","alias_value":"UICIBPCU","created_at":"2026-07-05T09:49:17Z"}],"graph_snapshots":[{"event_id":"sha256:834b8cb398371cd8ca45e4b730f19cc9925d2aae4b5c234fd8d8b4ec6c9618cf","target":"graph","created_at":"2026-07-05T09:49:17Z","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/2412.10540/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we tackle the challenge of predicting stock movements in financial markets by introducing Higher Order Transformers, a novel architecture designed for processing multivariate time-series data. We extend the self-attention mechanism and the transformer architecture to a higher order, effectively capturing complex market dynamics across time and variables. To manage computational complexity, we propose a low-rank approximation of the potentially large attention tensor using tensor decomposition and employ kernel attention, reducing complexity to linear with respect to the data siz","authors_text":"Guillaume Rabusseau, Reihaneh Rabbany, Soroush Omranpour","cross_cats":["q-fin.ST"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-13T20:26:35Z","title":"Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.10540","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:aadea610e12602e41e8d4305e777735a5b4d407b284ac6388052e4d90c102c13","target":"record","created_at":"2026-07-05T09:49:17Z","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":"9bd54a799b427949d611408f3ca5842b5b65a0a2b477069ed2557b24210d0a47","cross_cats_sorted":["q-fin.ST"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-13T20:26:35Z","title_canon_sha256":"1f06004e536f45e0902f35b53b1657092ace97939e7759ec711618ac9ca99e5b"},"schema_version":"1.0","source":{"id":"2412.10540","kind":"arxiv","version":1}},"canonical_sha256":"a20480bc545efebe93c37a701631c702eea10ae70bb7a27aa5a20505454c295b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a20480bc545efebe93c37a701631c702eea10ae70bb7a27aa5a20505454c295b","first_computed_at":"2026-07-05T09:49:17.466711Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:49:17.466711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lW2LsYGABaS+RLmSfNkOxMBoyPCr9wylD3olp9JY2BpMeeODSvHJUS9MgStGnMnkqACIlidbb0xVDbC4BCR6DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:49:17.467167Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.10540","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aadea610e12602e41e8d4305e777735a5b4d407b284ac6388052e4d90c102c13","sha256:834b8cb398371cd8ca45e4b730f19cc9925d2aae4b5c234fd8d8b4ec6c9618cf"],"state_sha256":"ac519adf98683398ee66c955dde06a64e9b95026ce01c18b527e1f197be8f9e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3KJ31i93Ot9N2tunAY4XtshcXXGNQKQacfpHsJDphG+bgFgZBzeGeQZtWiB8/7fJWj1zuYrXYoSWP9rspIH+Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T22:00:57.240827Z","bundle_sha256":"0ab7da75e3acbc7a3519484713f9b2e6ce34f36853278410b0801341012ab968"}}