{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:C4GM5EX3SEMBMNDEKNH6ASJ56T","short_pith_number":"pith:C4GM5EX3","canonical_record":{"source":{"id":"2505.20048","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-26T14:34:05Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"368293510f2794b9c27878a99bd585ca59c65dac493696a845f5a5612a35d769","abstract_canon_sha256":"4199fa310db6b4de74254c4e8145f06c4951908e217cb4238dd69e08139bf498"},"schema_version":"1.0"},"canonical_sha256":"170cce92fb9118163464534fe0493df4cb7dd61d6d8d7e4d023c11d781f2fcf3","source":{"kind":"arxiv","id":"2505.20048","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20048","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20048v1","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20048","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_12","alias_value":"C4GM5EX3SEMB","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_16","alias_value":"C4GM5EX3SEMBMNDE","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_8","alias_value":"C4GM5EX3","created_at":"2026-07-05T11:09:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:C4GM5EX3SEMBMNDEKNH6ASJ56T","target":"record","payload":{"canonical_record":{"source":{"id":"2505.20048","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-26T14:34:05Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"368293510f2794b9c27878a99bd585ca59c65dac493696a845f5a5612a35d769","abstract_canon_sha256":"4199fa310db6b4de74254c4e8145f06c4951908e217cb4238dd69e08139bf498"},"schema_version":"1.0"},"canonical_sha256":"170cce92fb9118163464534fe0493df4cb7dd61d6d8d7e4d023c11d781f2fcf3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:51.803028Z","signature_b64":"SYRJYAvx3eljDmJf7JDXwA7OyPGRrJsMFoYarDSL0G85+0gXM0khx4A2DMLFtVIdfhwtw7zqnfY2HdpPgGhJAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"170cce92fb9118163464534fe0493df4cb7dd61d6d8d7e4d023c11d781f2fcf3","last_reissued_at":"2026-07-05T11:09:51.802514Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:51.802514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.20048","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":"2026-07-05T11:09:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"05V58orfWXbXSjr7gFUkbGtO7xb8h7cet5e1oEKsYZ2qdGeKTIKNUAfCK+a7wpAw+h6Z841/qTb0txtko9SuAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T07:56:55.837374Z"},"content_sha256":"66d23f1463096a2d9bdd9fb963b92c4d2137ffd65991d5e0c394a39f2d9c5b0a","schema_version":"1.0","event_id":"sha256:66d23f1463096a2d9bdd9fb963b92c4d2137ffd65991d5e0c394a39f2d9c5b0a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:C4GM5EX3SEMBMNDEKNH6ASJ56T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.LG","authors_text":"Ali Forootani, Mohammad Khosravi","submitted_at":"2025-05-26T14:34:05Z","abstract_excerpt":"Time series forecasting plays a critical role in domains such as energy, finance, and healthcare, where accurate predictions inform decision-making under uncertainty. Although Transformer-based models have demonstrated success in sequential modeling, their adoption for time series remains limited by challenges such as noise sensitivity, long-range dependencies, and a lack of inductive bias for temporal structure. In this work, we present a unified and principled framework for benchmarking three prominent Transformer forecasting architectures-Autoformer, Informer, and Patchtst-each evaluated th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20048","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/2505.20048/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":"2026-07-05T11:09:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hgJrmkFgmTJZa/Fib4UZsaheWYK6YDHzkk6zn7t2+ifoThCPiu+PQyeK0/3DXv1Zg9JCo4MZ2pb3eCgD7ou0Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T07:56:55.837714Z"},"content_sha256":"139572962740090c5a66258e19d258941f374926be901408bff9233583800c2a","schema_version":"1.0","event_id":"sha256:139572962740090c5a66258e19d258941f374926be901408bff9233583800c2a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/bundle.json","state_url":"https://pith.science/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/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":"2026-08-22T07:56:55Z","links":{"resolver":"https://pith.science/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T","bundle":"https://pith.science/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/bundle.json","state":"https://pith.science/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C4GM5EX3SEMBMNDEKNH6ASJ56T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:C4GM5EX3SEMBMNDEKNH6ASJ56T","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":"4199fa310db6b4de74254c4e8145f06c4951908e217cb4238dd69e08139bf498","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-26T14:34:05Z","title_canon_sha256":"368293510f2794b9c27878a99bd585ca59c65dac493696a845f5a5612a35d769"},"schema_version":"1.0","source":{"id":"2505.20048","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20048","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20048v1","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20048","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_12","alias_value":"C4GM5EX3SEMB","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_16","alias_value":"C4GM5EX3SEMBMNDE","created_at":"2026-07-05T11:09:51Z"},{"alias_kind":"pith_short_8","alias_value":"C4GM5EX3","created_at":"2026-07-05T11:09:51Z"}],"graph_snapshots":[{"event_id":"sha256:139572962740090c5a66258e19d258941f374926be901408bff9233583800c2a","target":"graph","created_at":"2026-07-05T11:09:51Z","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/2505.20048/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Time series forecasting plays a critical role in domains such as energy, finance, and healthcare, where accurate predictions inform decision-making under uncertainty. Although Transformer-based models have demonstrated success in sequential modeling, their adoption for time series remains limited by challenges such as noise sensitivity, long-range dependencies, and a lack of inductive bias for temporal structure. In this work, we present a unified and principled framework for benchmarking three prominent Transformer forecasting architectures-Autoformer, Informer, and Patchtst-each evaluated th","authors_text":"Ali Forootani, Mohammad Khosravi","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-26T14:34:05Z","title":"Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20048","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":"sha256:66d23f1463096a2d9bdd9fb963b92c4d2137ffd65991d5e0c394a39f2d9c5b0a","target":"record","created_at":"2026-07-05T11:09:51Z","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":"4199fa310db6b4de74254c4e8145f06c4951908e217cb4238dd69e08139bf498","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-26T14:34:05Z","title_canon_sha256":"368293510f2794b9c27878a99bd585ca59c65dac493696a845f5a5612a35d769"},"schema_version":"1.0","source":{"id":"2505.20048","kind":"arxiv","version":1}},"canonical_sha256":"170cce92fb9118163464534fe0493df4cb7dd61d6d8d7e4d023c11d781f2fcf3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"170cce92fb9118163464534fe0493df4cb7dd61d6d8d7e4d023c11d781f2fcf3","first_computed_at":"2026-07-05T11:09:51.802514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:51.802514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SYRJYAvx3eljDmJf7JDXwA7OyPGRrJsMFoYarDSL0G85+0gXM0khx4A2DMLFtVIdfhwtw7zqnfY2HdpPgGhJAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:51.803028Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.20048","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:66d23f1463096a2d9bdd9fb963b92c4d2137ffd65991d5e0c394a39f2d9c5b0a","sha256:139572962740090c5a66258e19d258941f374926be901408bff9233583800c2a"],"state_sha256":"8806ddf31a3921b84a6c57a6d18b7a6c65082295a1c4a51b38e1a93a647494b6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jBjrpBUzvA6q/nhPwfvCZFk/2PYrbGgGZ2cTtPC7QtrAo5MNJe+ewWjxMnFn3xu8V/vdD2VBvU3MI5Qn6tHJCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T07:56:55.840811Z","bundle_sha256":"ce71f3d714d2ae0ebdf3d5710b0d343f2f58fed360313368bdc00a6d00ad72ae"}}