{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LRNF22HDHWULUTBJ6U7ECV5G6K","short_pith_number":"pith:LRNF22HD","canonical_record":{"source":{"id":"2508.09164","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T03:11:27Z","cross_cats_sorted":[],"title_canon_sha256":"b772a204c68333b7651981344e0835db6d0baa05dd129d6c89f78321fb7e7d4f","abstract_canon_sha256":"c99a596c24b6482476c4cebb47c50906fbdf367263f5194d547f231b716e03bc"},"schema_version":"1.0"},"canonical_sha256":"5c5a5d68e33da8ba4c29f53e4157a6f2931adad8a2278ca279a44a1b06c535d6","source":{"kind":"arxiv","id":"2508.09164","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09164","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09164v1","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09164","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_12","alias_value":"LRNF22HDHWUL","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_16","alias_value":"LRNF22HDHWULUTBJ","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_8","alias_value":"LRNF22HD","created_at":"2026-07-05T11:53:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LRNF22HDHWULUTBJ6U7ECV5G6K","target":"record","payload":{"canonical_record":{"source":{"id":"2508.09164","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T03:11:27Z","cross_cats_sorted":[],"title_canon_sha256":"b772a204c68333b7651981344e0835db6d0baa05dd129d6c89f78321fb7e7d4f","abstract_canon_sha256":"c99a596c24b6482476c4cebb47c50906fbdf367263f5194d547f231b716e03bc"},"schema_version":"1.0"},"canonical_sha256":"5c5a5d68e33da8ba4c29f53e4157a6f2931adad8a2278ca279a44a1b06c535d6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:53:09.119377Z","signature_b64":"/gfGKvrMhQgyKwacylmSD2pL0RfMA80g7ddDAiWtf/m+Qwd4z+gk7jqr1iukr35R2oivQ9LtfJN3MWDSEoEsDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c5a5d68e33da8ba4c29f53e4157a6f2931adad8a2278ca279a44a1b06c535d6","last_reissued_at":"2026-07-05T11:53:09.118928Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:53:09.118928Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.09164","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":"2026-07-05T11:53:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xN3Nwah8NyGDiiwKkqgacu/MvwYo18gtpq07xS/NeD9mruahcGBxkdaXa07R1hoP/+FoAEa3P9MPkeopMcZhBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T21:42:10.977714Z"},"content_sha256":"15d211ae2ac50ca0716ce96dab25790a96eea0ecb6da3592c21dde7ff8d8c9f7","schema_version":"1.0","event_id":"sha256:15d211ae2ac50ca0716ce96dab25790a96eea0ecb6da3592c21dde7ff8d8c9f7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LRNF22HDHWULUTBJ6U7ECV5G6K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Feasible and Diverse Synthetic Populations Using Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Min Tang, Peng Lu, Qing Feng","submitted_at":"2025-08-06T03:11:27Z","abstract_excerpt":"Population synthesis is a critical task that involves generating synthetic yet realistic representations of populations. It is a fundamental problem in agent-based modeling (ABM), which has become the standard to analyze intelligent transportation systems. The synthetic population serves as the primary input for ABM transportation simulation, with traveling agents represented by population members. However, when the number of attributes describing agents becomes large, survey data often cannot densely support the joint distribution of the attributes in the population due to the curse of dimens"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09164","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/2508.09164/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":"2026-07-05T11:53:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0ounSBJkRRik1SPFnM7xARf/Yv2avgxudPLFydJ90qtuerBdabLjks1o+CTfQxTATusuHB4rWEZCZmZzlNmTCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T21:42:10.978243Z"},"content_sha256":"b550d11fab32a2d7a65f8e678406aa56c11514e02ecd49152346ab286f8ceea3","schema_version":"1.0","event_id":"sha256:b550d11fab32a2d7a65f8e678406aa56c11514e02ecd49152346ab286f8ceea3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/bundle.json","state_url":"https://pith.science/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/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":"2026-08-17T21:42:10Z","links":{"resolver":"https://pith.science/pith/LRNF22HDHWULUTBJ6U7ECV5G6K","bundle":"https://pith.science/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/bundle.json","state":"https://pith.science/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LRNF22HDHWULUTBJ6U7ECV5G6K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LRNF22HDHWULUTBJ6U7ECV5G6K","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":"c99a596c24b6482476c4cebb47c50906fbdf367263f5194d547f231b716e03bc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T03:11:27Z","title_canon_sha256":"b772a204c68333b7651981344e0835db6d0baa05dd129d6c89f78321fb7e7d4f"},"schema_version":"1.0","source":{"id":"2508.09164","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09164","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09164v1","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09164","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_12","alias_value":"LRNF22HDHWUL","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_16","alias_value":"LRNF22HDHWULUTBJ","created_at":"2026-07-05T11:53:09Z"},{"alias_kind":"pith_short_8","alias_value":"LRNF22HD","created_at":"2026-07-05T11:53:09Z"}],"graph_snapshots":[{"event_id":"sha256:b550d11fab32a2d7a65f8e678406aa56c11514e02ecd49152346ab286f8ceea3","target":"graph","created_at":"2026-07-05T11:53:09Z","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/2508.09164/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Population synthesis is a critical task that involves generating synthetic yet realistic representations of populations. It is a fundamental problem in agent-based modeling (ABM), which has become the standard to analyze intelligent transportation systems. The synthetic population serves as the primary input for ABM transportation simulation, with traveling agents represented by population members. However, when the number of attributes describing agents becomes large, survey data often cannot densely support the joint distribution of the attributes in the population due to the curse of dimens","authors_text":"Min Tang, Peng Lu, Qing Feng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T03:11:27Z","title":"Generating Feasible and Diverse Synthetic Populations Using Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09164","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":"sha256:15d211ae2ac50ca0716ce96dab25790a96eea0ecb6da3592c21dde7ff8d8c9f7","target":"record","created_at":"2026-07-05T11:53:09Z","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":"c99a596c24b6482476c4cebb47c50906fbdf367263f5194d547f231b716e03bc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-06T03:11:27Z","title_canon_sha256":"b772a204c68333b7651981344e0835db6d0baa05dd129d6c89f78321fb7e7d4f"},"schema_version":"1.0","source":{"id":"2508.09164","kind":"arxiv","version":1}},"canonical_sha256":"5c5a5d68e33da8ba4c29f53e4157a6f2931adad8a2278ca279a44a1b06c535d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c5a5d68e33da8ba4c29f53e4157a6f2931adad8a2278ca279a44a1b06c535d6","first_computed_at":"2026-07-05T11:53:09.118928Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:53:09.118928Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/gfGKvrMhQgyKwacylmSD2pL0RfMA80g7ddDAiWtf/m+Qwd4z+gk7jqr1iukr35R2oivQ9LtfJN3MWDSEoEsDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:53:09.119377Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.09164","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:15d211ae2ac50ca0716ce96dab25790a96eea0ecb6da3592c21dde7ff8d8c9f7","sha256:b550d11fab32a2d7a65f8e678406aa56c11514e02ecd49152346ab286f8ceea3"],"state_sha256":"e2facdcf3ca672a4dc73d5b37a21708e6229a0ac23fd8ccd7ebafc8a0a98b773"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aSpZPqgymIraZ3ugLN+0fY5CcV+xWW+ewqbwW4QadAxhZV0GUc5q4ckKZCqeOJmOYXnaXJFNxzm3lfXuvFtaAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T21:42:10.983195Z","bundle_sha256":"d9570e88292d3e08b849cfc4b6da4ef6e6e0f7ff522a343e0c7d66c5c886478b"}}