{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TJMUFGTMSAIVE3IUN4AZP5OZUG","short_pith_number":"pith:TJMUFGTM","canonical_record":{"source":{"id":"2410.01098","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T21:59:08Z","cross_cats_sorted":["cs.SY","eess.IV","eess.SY"],"title_canon_sha256":"481ba8122f5dc49cee564c2154680c784ce6fb8b43c445b4c5bd089d3ab49710","abstract_canon_sha256":"726816b68d3a6b4bf27bc190b025979ec1e8241946e8b3e128b25c010e41aa1c"},"schema_version":"1.0"},"canonical_sha256":"9a59429a6c9011526d146f0197f5d9a1a7432cb0f34c87e6be3490be9907dea3","source":{"kind":"arxiv","id":"2410.01098","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.01098","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"arxiv_version","alias_value":"2410.01098v2","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.01098","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_12","alias_value":"TJMUFGTMSAIV","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_16","alias_value":"TJMUFGTMSAIVE3IU","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_8","alias_value":"TJMUFGTM","created_at":"2026-07-05T11:01:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TJMUFGTMSAIVE3IUN4AZP5OZUG","target":"record","payload":{"canonical_record":{"source":{"id":"2410.01098","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T21:59:08Z","cross_cats_sorted":["cs.SY","eess.IV","eess.SY"],"title_canon_sha256":"481ba8122f5dc49cee564c2154680c784ce6fb8b43c445b4c5bd089d3ab49710","abstract_canon_sha256":"726816b68d3a6b4bf27bc190b025979ec1e8241946e8b3e128b25c010e41aa1c"},"schema_version":"1.0"},"canonical_sha256":"9a59429a6c9011526d146f0197f5d9a1a7432cb0f34c87e6be3490be9907dea3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:27.177747Z","signature_b64":"i3ml40LPwb9cYNveyCsnqXupGjxXBpO3YuHCXzJNLdAUwDhceULxdTWTl9zP90y2aczv8lRSE+amiuSNYUDhDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9a59429a6c9011526d146f0197f5d9a1a7432cb0f34c87e6be3490be9907dea3","last_reissued_at":"2026-07-05T11:01:27.177280Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:27.177280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.01098","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":"2026-07-05T11:01:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y0BjgYMqOhcCfyAkb6lCmY1N8QKC4Zb6AThEgI3/XbWJLbMd94E+DDprz2R31kx6bObzShZN3nVLkfAatTtLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:23:40.152463Z"},"content_sha256":"d56d2c95509390dfb74efc2cdbe590677beb7aec9ad09f1ce10319e4906c33cd","schema_version":"1.0","event_id":"sha256:d56d2c95509390dfb74efc2cdbe590677beb7aec9ad09f1ce10319e4906c33cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TJMUFGTMSAIVE3IUN4AZP5OZUG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring Gen-AI applications in building research and industry: A review","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.IV","eess.SY"],"primary_cat":"cs.AI","authors_text":"Fan Feng, Hanlong Wan, Jian Zhang, Weili Xu, Yan Chen","submitted_at":"2024-10-01T21:59:08Z","abstract_excerpt":"This paper investigates the transformative potential of Generative AI (Gen-AI) technologies, particularly large language models, within the building industry. By leveraging these advanced AI tools, the study explores their application across key areas such as automated compliance checking and building design assistance. The research highlights how Gen-AI can automate labor-intensive processes, significantly improving efficiency and reducing costs in building practices. The paper first discusses the two widely applied fundamental models-Transformer and Diffusion model-and summarizes current pat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.01098","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/2410.01098/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":"2026-07-05T11:01:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"31Fxe1fDpSGHw0Q432ihGLYz6vuGDZbPW4zOqjbgW2Hlp0ilCywWEBMaqDwXJ2WaItQ7OREhn5NKWuSC+alMAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:23:40.153460Z"},"content_sha256":"baa9777b02a488fe93adc180cb34a446236a9f694ccf674c67c67aaf58d7f9e5","schema_version":"1.0","event_id":"sha256:baa9777b02a488fe93adc180cb34a446236a9f694ccf674c67c67aaf58d7f9e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/bundle.json","state_url":"https://pith.science/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/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":"2026-08-03T21:23:40Z","links":{"resolver":"https://pith.science/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG","bundle":"https://pith.science/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/bundle.json","state":"https://pith.science/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TJMUFGTMSAIVE3IUN4AZP5OZUG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TJMUFGTMSAIVE3IUN4AZP5OZUG","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":"726816b68d3a6b4bf27bc190b025979ec1e8241946e8b3e128b25c010e41aa1c","cross_cats_sorted":["cs.SY","eess.IV","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T21:59:08Z","title_canon_sha256":"481ba8122f5dc49cee564c2154680c784ce6fb8b43c445b4c5bd089d3ab49710"},"schema_version":"1.0","source":{"id":"2410.01098","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.01098","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"arxiv_version","alias_value":"2410.01098v2","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.01098","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_12","alias_value":"TJMUFGTMSAIV","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_16","alias_value":"TJMUFGTMSAIVE3IU","created_at":"2026-07-05T11:01:27Z"},{"alias_kind":"pith_short_8","alias_value":"TJMUFGTM","created_at":"2026-07-05T11:01:27Z"}],"graph_snapshots":[{"event_id":"sha256:baa9777b02a488fe93adc180cb34a446236a9f694ccf674c67c67aaf58d7f9e5","target":"graph","created_at":"2026-07-05T11:01:27Z","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/2410.01098/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper investigates the transformative potential of Generative AI (Gen-AI) technologies, particularly large language models, within the building industry. By leveraging these advanced AI tools, the study explores their application across key areas such as automated compliance checking and building design assistance. The research highlights how Gen-AI can automate labor-intensive processes, significantly improving efficiency and reducing costs in building practices. The paper first discusses the two widely applied fundamental models-Transformer and Diffusion model-and summarizes current pat","authors_text":"Fan Feng, Hanlong Wan, Jian Zhang, Weili Xu, Yan Chen","cross_cats":["cs.SY","eess.IV","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T21:59:08Z","title":"Exploring Gen-AI applications in building research and industry: A review"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.01098","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:d56d2c95509390dfb74efc2cdbe590677beb7aec9ad09f1ce10319e4906c33cd","target":"record","created_at":"2026-07-05T11:01:27Z","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":"726816b68d3a6b4bf27bc190b025979ec1e8241946e8b3e128b25c010e41aa1c","cross_cats_sorted":["cs.SY","eess.IV","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T21:59:08Z","title_canon_sha256":"481ba8122f5dc49cee564c2154680c784ce6fb8b43c445b4c5bd089d3ab49710"},"schema_version":"1.0","source":{"id":"2410.01098","kind":"arxiv","version":2}},"canonical_sha256":"9a59429a6c9011526d146f0197f5d9a1a7432cb0f34c87e6be3490be9907dea3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a59429a6c9011526d146f0197f5d9a1a7432cb0f34c87e6be3490be9907dea3","first_computed_at":"2026-07-05T11:01:27.177280Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:01:27.177280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i3ml40LPwb9cYNveyCsnqXupGjxXBpO3YuHCXzJNLdAUwDhceULxdTWTl9zP90y2aczv8lRSE+amiuSNYUDhDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:01:27.177747Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.01098","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d56d2c95509390dfb74efc2cdbe590677beb7aec9ad09f1ce10319e4906c33cd","sha256:baa9777b02a488fe93adc180cb34a446236a9f694ccf674c67c67aaf58d7f9e5"],"state_sha256":"aa44e966564fc66c29c16ee9c7c6a1592012be8962954c5046e50142e60ea543"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W1sTOKMwbkFRFm/7ami1aKMrCzYnZeCXdiBA7b6JRLv1I2xYEEaw1+cm60zrtWl5y5IsyvInsj/qCGUoXikwCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T21:23:40.159106Z","bundle_sha256":"4a96ec8d2a04571c47f0c07d0d3578ed59fc2d4d0627be2e2be72a6efd3ea1c8"}}