{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SKBVZE5XVURG426WVPEAC34FN4","short_pith_number":"pith:SKBVZE5X","canonical_record":{"source":{"id":"2404.08175","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T00:44:15Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"39b7594477661d0ff8f6a3bd3326e34532caa8478e0cdecd3f4424b12b0285c5","abstract_canon_sha256":"c96b62d51cc1b3478cbb3af2790906a1efb314617675bbba6691191bee23c8a9"},"schema_version":"1.0"},"canonical_sha256":"92835c93b7ad226e6bd6abc8016f856f138289caa26da9a4c975af97dc584682","source":{"kind":"arxiv","id":"2404.08175","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08175","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08175v1","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08175","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_12","alias_value":"SKBVZE5XVURG","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_16","alias_value":"SKBVZE5XVURG426W","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_8","alias_value":"SKBVZE5X","created_at":"2026-07-05T08:07:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SKBVZE5XVURG426WVPEAC34FN4","target":"record","payload":{"canonical_record":{"source":{"id":"2404.08175","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T00:44:15Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"39b7594477661d0ff8f6a3bd3326e34532caa8478e0cdecd3f4424b12b0285c5","abstract_canon_sha256":"c96b62d51cc1b3478cbb3af2790906a1efb314617675bbba6691191bee23c8a9"},"schema_version":"1.0"},"canonical_sha256":"92835c93b7ad226e6bd6abc8016f856f138289caa26da9a4c975af97dc584682","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:07:18.859852Z","signature_b64":"BYcYui3shKc9EIa74EeaOl6pquGgzZzzWi6DansbDLCBZaKd9CcK89wpFIL+O6PUAkhtLaWff6Flu302e3SrAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92835c93b7ad226e6bd6abc8016f856f138289caa26da9a4c975af97dc584682","last_reissued_at":"2026-07-05T08:07:18.859389Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:07:18.859389Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.08175","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":"2026-07-05T08:07:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uj61T1YQ35s5H/ivIEua2ooVCXTIF/1tjKOQBhlbdLtisqPXbgBPyn0CW0kqWgPS7cSJeiaZuT+ELwBXVwSZAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:22:36.474735Z"},"content_sha256":"24e6aabccb58ba3bd4808735543392ae8569a0873ede500cf2fd945af427ae46","schema_version":"1.0","event_id":"sha256:24e6aabccb58ba3bd4808735543392ae8569a0873ede500cf2fd945af427ae46"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SKBVZE5XVURG426WVPEAC34FN4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Novel Vision Transformer based Load Profile Analysis using Load Images as Inputs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Hyeonjin Kim, Kai Ye, Ning Lu, Yi Hu","submitted_at":"2024-04-12T00:44:15Z","abstract_excerpt":"This paper introduces ViT4LPA, an innovative Vision Transformer (ViT) based approach for Load Profile Analysis (LPA). We transform time-series load profiles into load images. This allows us to leverage the ViT architecture, originally designed for image processing, as a pre-trained image encoder to uncover latent patterns within load data. ViT is pre-trained using an extensive load image dataset, comprising 1M load images derived from smart meter data collected over a two-year period from 2,000 residential users. The training methodology is self-supervised, masked image modeling, wherein maske"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08175","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/2404.08175/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":"2026-07-05T08:07:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"niyvZJRWPJI+0+jgkQnUTdWXCV/d3BsYBqaf7jimHE3c7fnVxE8gqEffhoQMOC7qGnUAvuza8JwL39XRA473Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:22:36.475697Z"},"content_sha256":"55938290ff111af83d1838da90924a8179b49d62784d8353db5937e6561d7bf1","schema_version":"1.0","event_id":"sha256:55938290ff111af83d1838da90924a8179b49d62784d8353db5937e6561d7bf1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SKBVZE5XVURG426WVPEAC34FN4/bundle.json","state_url":"https://pith.science/pith/SKBVZE5XVURG426WVPEAC34FN4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SKBVZE5XVURG426WVPEAC34FN4/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":"2026-08-07T06:22:36Z","links":{"resolver":"https://pith.science/pith/SKBVZE5XVURG426WVPEAC34FN4","bundle":"https://pith.science/pith/SKBVZE5XVURG426WVPEAC34FN4/bundle.json","state":"https://pith.science/pith/SKBVZE5XVURG426WVPEAC34FN4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SKBVZE5XVURG426WVPEAC34FN4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SKBVZE5XVURG426WVPEAC34FN4","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":"c96b62d51cc1b3478cbb3af2790906a1efb314617675bbba6691191bee23c8a9","cross_cats_sorted":["cs.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T00:44:15Z","title_canon_sha256":"39b7594477661d0ff8f6a3bd3326e34532caa8478e0cdecd3f4424b12b0285c5"},"schema_version":"1.0","source":{"id":"2404.08175","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08175","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08175v1","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08175","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_12","alias_value":"SKBVZE5XVURG","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_16","alias_value":"SKBVZE5XVURG426W","created_at":"2026-07-05T08:07:18Z"},{"alias_kind":"pith_short_8","alias_value":"SKBVZE5X","created_at":"2026-07-05T08:07:18Z"}],"graph_snapshots":[{"event_id":"sha256:55938290ff111af83d1838da90924a8179b49d62784d8353db5937e6561d7bf1","target":"graph","created_at":"2026-07-05T08:07:18Z","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/2404.08175/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces ViT4LPA, an innovative Vision Transformer (ViT) based approach for Load Profile Analysis (LPA). We transform time-series load profiles into load images. This allows us to leverage the ViT architecture, originally designed for image processing, as a pre-trained image encoder to uncover latent patterns within load data. ViT is pre-trained using an extensive load image dataset, comprising 1M load images derived from smart meter data collected over a two-year period from 2,000 residential users. The training methodology is self-supervised, masked image modeling, wherein maske","authors_text":"Hyeonjin Kim, Kai Ye, Ning Lu, Yi Hu","cross_cats":["cs.SY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T00:44:15Z","title":"A Novel Vision Transformer based Load Profile Analysis using Load Images as Inputs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08175","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":"sha256:24e6aabccb58ba3bd4808735543392ae8569a0873ede500cf2fd945af427ae46","target":"record","created_at":"2026-07-05T08:07:18Z","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":"c96b62d51cc1b3478cbb3af2790906a1efb314617675bbba6691191bee23c8a9","cross_cats_sorted":["cs.SY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-04-12T00:44:15Z","title_canon_sha256":"39b7594477661d0ff8f6a3bd3326e34532caa8478e0cdecd3f4424b12b0285c5"},"schema_version":"1.0","source":{"id":"2404.08175","kind":"arxiv","version":1}},"canonical_sha256":"92835c93b7ad226e6bd6abc8016f856f138289caa26da9a4c975af97dc584682","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92835c93b7ad226e6bd6abc8016f856f138289caa26da9a4c975af97dc584682","first_computed_at":"2026-07-05T08:07:18.859389Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:07:18.859389Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BYcYui3shKc9EIa74EeaOl6pquGgzZzzWi6DansbDLCBZaKd9CcK89wpFIL+O6PUAkhtLaWff6Flu302e3SrAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:07:18.859852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.08175","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24e6aabccb58ba3bd4808735543392ae8569a0873ede500cf2fd945af427ae46","sha256:55938290ff111af83d1838da90924a8179b49d62784d8353db5937e6561d7bf1"],"state_sha256":"8f3012e04d6ffe2008ecb5a63016da380df8a2e29dcba190063853bbf88665db"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y9C9CmQHpG295azAAAaIkOQPueEth7ZCXCHgU5ER6WHbL+2a5qc285pNQWnIJsOzkvuwjDta/vu1ieOwU+VqBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T06:22:36.487889Z","bundle_sha256":"0381db8f51b0629e1250205c08d5e130cd373ca933cf125d0d524f6f784fad4a"}}