{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GFZY6PM535IQVK4APVXK2KGLCF","short_pith_number":"pith:GFZY6PM5","canonical_record":{"source":{"id":"2501.00467","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-31T14:34:27Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"5e8ffcaa0cef3909d23d8450664fd5ffaf9a6dfd3145f4cdf69834ed7120cafa","abstract_canon_sha256":"b872a84728d00d7af60a54e614bfc138d240908510ff764d87e16544bb503ceb"},"schema_version":"1.0"},"canonical_sha256":"31738f3d9ddf510aab807d6ead28cb1177a9963eb298be61988271d6c24a9913","source":{"kind":"arxiv","id":"2501.00467","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00467","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00467v2","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00467","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_12","alias_value":"GFZY6PM535IQ","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_16","alias_value":"GFZY6PM535IQVK4A","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_8","alias_value":"GFZY6PM5","created_at":"2026-07-05T10:41:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GFZY6PM535IQVK4APVXK2KGLCF","target":"record","payload":{"canonical_record":{"source":{"id":"2501.00467","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-31T14:34:27Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"5e8ffcaa0cef3909d23d8450664fd5ffaf9a6dfd3145f4cdf69834ed7120cafa","abstract_canon_sha256":"b872a84728d00d7af60a54e614bfc138d240908510ff764d87e16544bb503ceb"},"schema_version":"1.0"},"canonical_sha256":"31738f3d9ddf510aab807d6ead28cb1177a9963eb298be61988271d6c24a9913","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:41:51.589304Z","signature_b64":"8R6A7iTHldB391Kf20FoCAWRcFsbds3/qv5YkYmLygV5bEJDCpqxp5A4oRxtsbgmdH7pT5jsSW5vXMiG+dBaBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"31738f3d9ddf510aab807d6ead28cb1177a9963eb298be61988271d6c24a9913","last_reissued_at":"2026-07-05T10:41:51.588887Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:41:51.588887Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.00467","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":"2026-07-05T10:41:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jWhvatUmYvUpuxeLgF97EygFQg+PGlbP73AGNGNgEBY7KhiZLgnf/rLdC4zuyfcH0cWGux9+q74R7kDhp0NmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:28:39.355168Z"},"content_sha256":"5e7ff83d3977a5f3e8377d31ca6ab462995edbc2b4bdfdece40f05c5554d2702","schema_version":"1.0","event_id":"sha256:5e7ff83d3977a5f3e8377d31ca6ab462995edbc2b4bdfdece40f05c5554d2702"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GFZY6PM535IQVK4APVXK2KGLCF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Score-Based Metropolis-Hastings Algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"cs.LG","authors_text":"Ahmed Aloui, Ali Hasan, Juncheng Dong, Vahid Tarokh, Zihao Wu","submitted_at":"2024-12-31T14:34:27Z","abstract_excerpt":"In this paper, we introduce a new approach for integrating score-based models with the Metropolis-Hastings algorithm. While traditional score-based diffusion models excel in accurately learning the score function from data points, they lack an energy function, making the Metropolis-Hastings adjustment step inaccessible. Consequently, the unadjusted Langevin algorithm is often used for sampling using estimated score functions. The lack of an energy function then prevents the application of the Metropolis-adjusted Langevin algorithm and other Metropolis-Hastings methods, limiting the wealth of o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00467","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/2501.00467/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":"2026-07-05T10:41:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fgg6dwoGZ4h5XpmqGbsCljuoTQ9/vDDL3Bn11blVqrMDF/k7ntclPTyUceQr/rweckTCqDe98aXK1QswHIP/CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:28:39.355568Z"},"content_sha256":"3a0f5d8d3a80dbdd6267c0f704855d5c9f6caf6bbe2a94f7d51b96287cc2d9f3","schema_version":"1.0","event_id":"sha256:3a0f5d8d3a80dbdd6267c0f704855d5c9f6caf6bbe2a94f7d51b96287cc2d9f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GFZY6PM535IQVK4APVXK2KGLCF/bundle.json","state_url":"https://pith.science/pith/GFZY6PM535IQVK4APVXK2KGLCF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GFZY6PM535IQVK4APVXK2KGLCF/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":"2026-07-07T06:28:39Z","links":{"resolver":"https://pith.science/pith/GFZY6PM535IQVK4APVXK2KGLCF","bundle":"https://pith.science/pith/GFZY6PM535IQVK4APVXK2KGLCF/bundle.json","state":"https://pith.science/pith/GFZY6PM535IQVK4APVXK2KGLCF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GFZY6PM535IQVK4APVXK2KGLCF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GFZY6PM535IQVK4APVXK2KGLCF","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":"b872a84728d00d7af60a54e614bfc138d240908510ff764d87e16544bb503ceb","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-31T14:34:27Z","title_canon_sha256":"5e8ffcaa0cef3909d23d8450664fd5ffaf9a6dfd3145f4cdf69834ed7120cafa"},"schema_version":"1.0","source":{"id":"2501.00467","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00467","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00467v2","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00467","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_12","alias_value":"GFZY6PM535IQ","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_16","alias_value":"GFZY6PM535IQVK4A","created_at":"2026-07-05T10:41:51Z"},{"alias_kind":"pith_short_8","alias_value":"GFZY6PM5","created_at":"2026-07-05T10:41:51Z"}],"graph_snapshots":[{"event_id":"sha256:3a0f5d8d3a80dbdd6267c0f704855d5c9f6caf6bbe2a94f7d51b96287cc2d9f3","target":"graph","created_at":"2026-07-05T10:41:51Z","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/2501.00467/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce a new approach for integrating score-based models with the Metropolis-Hastings algorithm. While traditional score-based diffusion models excel in accurately learning the score function from data points, they lack an energy function, making the Metropolis-Hastings adjustment step inaccessible. Consequently, the unadjusted Langevin algorithm is often used for sampling using estimated score functions. The lack of an energy function then prevents the application of the Metropolis-adjusted Langevin algorithm and other Metropolis-Hastings methods, limiting the wealth of o","authors_text":"Ahmed Aloui, Ali Hasan, Juncheng Dong, Vahid Tarokh, Zihao Wu","cross_cats":["stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-31T14:34:27Z","title":"Score-Based Metropolis-Hastings Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00467","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":"sha256:5e7ff83d3977a5f3e8377d31ca6ab462995edbc2b4bdfdece40f05c5554d2702","target":"record","created_at":"2026-07-05T10:41:51Z","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":"b872a84728d00d7af60a54e614bfc138d240908510ff764d87e16544bb503ceb","cross_cats_sorted":["stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-31T14:34:27Z","title_canon_sha256":"5e8ffcaa0cef3909d23d8450664fd5ffaf9a6dfd3145f4cdf69834ed7120cafa"},"schema_version":"1.0","source":{"id":"2501.00467","kind":"arxiv","version":2}},"canonical_sha256":"31738f3d9ddf510aab807d6ead28cb1177a9963eb298be61988271d6c24a9913","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"31738f3d9ddf510aab807d6ead28cb1177a9963eb298be61988271d6c24a9913","first_computed_at":"2026-07-05T10:41:51.588887Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:41:51.588887Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8R6A7iTHldB391Kf20FoCAWRcFsbds3/qv5YkYmLygV5bEJDCpqxp5A4oRxtsbgmdH7pT5jsSW5vXMiG+dBaBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:41:51.589304Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.00467","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e7ff83d3977a5f3e8377d31ca6ab462995edbc2b4bdfdece40f05c5554d2702","sha256:3a0f5d8d3a80dbdd6267c0f704855d5c9f6caf6bbe2a94f7d51b96287cc2d9f3"],"state_sha256":"261f0ca698d98c2a1069a780a92128979ab0dbf5efd62c37528b3765d36fc84e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nYkdT245glbcnNq48xwwq0+zXxr0dVSN/sXajnKJh/k7WtL8oxN3PD4fLjK0kiu3shH9as1NnJWw94t9w+GUDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T06:28:39.358664Z","bundle_sha256":"36930095fa1678896cc569b4ca30350a2b675277ebbf3a5364b330d76c14fea3"}}