{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WPLRHUXRYRHGBIP5FEAAS2WQ35","short_pith_number":"pith:WPLRHUXR","canonical_record":{"source":{"id":"2410.19449","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-10-25T10:23:34Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"a4491717a168b086ed7031b2fb53ca94aff7cb45d0b9974a6c77d69eae0b3b5c","abstract_canon_sha256":"4c2e4337acbb42aceaca7be898aadf7e98ce90d8f1f4cee0767bfa6e1ef85064"},"schema_version":"1.0"},"canonical_sha256":"b3d713d2f1c44e60a1fd2900096ad0df58ee6fdee4bbc4fa5ce6d11f23d5659e","source":{"kind":"arxiv","id":"2410.19449","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.19449","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2410.19449v3","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.19449","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"WPLRHUXRYRHG","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"WPLRHUXRYRHGBIP5","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"WPLRHUXR","created_at":"2026-07-05T10:47:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WPLRHUXRYRHGBIP5FEAAS2WQ35","target":"record","payload":{"canonical_record":{"source":{"id":"2410.19449","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-10-25T10:23:34Z","cross_cats_sorted":["cs.LG","stat.CO"],"title_canon_sha256":"a4491717a168b086ed7031b2fb53ca94aff7cb45d0b9974a6c77d69eae0b3b5c","abstract_canon_sha256":"4c2e4337acbb42aceaca7be898aadf7e98ce90d8f1f4cee0767bfa6e1ef85064"},"schema_version":"1.0"},"canonical_sha256":"b3d713d2f1c44e60a1fd2900096ad0df58ee6fdee4bbc4fa5ce6d11f23d5659e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:47:55.919011Z","signature_b64":"vtVGegpYlD7EqIvmKoCRASROlYGeyDA9nbfja/2f1QQKa49tOhbp1U5FqUXuAi6q6DnrI54Y4OcOT4y1j6IpDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3d713d2f1c44e60a1fd2900096ad0df58ee6fdee4bbc4fa5ce6d11f23d5659e","last_reissued_at":"2026-07-05T10:47:55.918510Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:47:55.918510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.19449","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jqaNQh1hxwQGKnbbJ+kYH++5lHOP8kYn5fHMjpkNo9nuZ6pfOyZb7qwhvk7+5ZCSAhMRS4/YiTdR65Kfb9/nCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:31:56.451041Z"},"content_sha256":"491816cb4c915149fb7d56582128ca810152ebe675ca83986cbe83838a03ba4a","schema_version":"1.0","event_id":"sha256:491816cb4c915149fb7d56582128ca810152ebe675ca83986cbe83838a03ba4a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WPLRHUXRYRHGBIP5FEAAS2WQ35","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learned Reference-based Diffusion Sampling for multi-modal distributions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.CO"],"primary_cat":"stat.ML","authors_text":"Alain Oliviero Durmus, Louis Grenioux, Marylou Gabri\\'e, Maxence Noble","submitted_at":"2024-10-25T10:23:34Z","abstract_excerpt":"Over the past few years, several approaches utilizing score-based diffusion have been proposed to sample from probability distributions, that is without having access to exact samples and relying solely on evaluations of unnormalized densities. The resulting samplers approximate the time-reversal of a noising diffusion process, bridging the target distribution to an easy-to-sample base distribution. In practice, the performance of these methods heavily depends on key hyperparameters that require ground truth samples to be accurately tuned. Our work aims to highlight and address this fundamenta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.19449","kind":"arxiv","version":3},"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/2410.19449/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":"2026-07-05T10:47:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fV3d4KFsVw82liONiel5E71XRKZV5nI2TUC64ChWwCRi+V8zY7esOjM9uvqC+Lmc6Gy5HLmHUkcw+bcAeJ6VCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T21:31:56.451768Z"},"content_sha256":"2d582291f2c0df82002c2f5435b9f93d880c0fe4a5567c474352b68b34bbeeb7","schema_version":"1.0","event_id":"sha256:2d582291f2c0df82002c2f5435b9f93d880c0fe4a5567c474352b68b34bbeeb7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/bundle.json","state_url":"https://pith.science/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/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":"2026-08-10T21:31:56Z","links":{"resolver":"https://pith.science/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35","bundle":"https://pith.science/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/bundle.json","state":"https://pith.science/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WPLRHUXRYRHGBIP5FEAAS2WQ35/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WPLRHUXRYRHGBIP5FEAAS2WQ35","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":"4c2e4337acbb42aceaca7be898aadf7e98ce90d8f1f4cee0767bfa6e1ef85064","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-10-25T10:23:34Z","title_canon_sha256":"a4491717a168b086ed7031b2fb53ca94aff7cb45d0b9974a6c77d69eae0b3b5c"},"schema_version":"1.0","source":{"id":"2410.19449","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.19449","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"arxiv_version","alias_value":"2410.19449v3","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.19449","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_12","alias_value":"WPLRHUXRYRHG","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_16","alias_value":"WPLRHUXRYRHGBIP5","created_at":"2026-07-05T10:47:55Z"},{"alias_kind":"pith_short_8","alias_value":"WPLRHUXR","created_at":"2026-07-05T10:47:55Z"}],"graph_snapshots":[{"event_id":"sha256:2d582291f2c0df82002c2f5435b9f93d880c0fe4a5567c474352b68b34bbeeb7","target":"graph","created_at":"2026-07-05T10:47:55Z","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/2410.19449/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Over the past few years, several approaches utilizing score-based diffusion have been proposed to sample from probability distributions, that is without having access to exact samples and relying solely on evaluations of unnormalized densities. The resulting samplers approximate the time-reversal of a noising diffusion process, bridging the target distribution to an easy-to-sample base distribution. In practice, the performance of these methods heavily depends on key hyperparameters that require ground truth samples to be accurately tuned. Our work aims to highlight and address this fundamenta","authors_text":"Alain Oliviero Durmus, Louis Grenioux, Marylou Gabri\\'e, Maxence Noble","cross_cats":["cs.LG","stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-10-25T10:23:34Z","title":"Learned Reference-based Diffusion Sampling for multi-modal distributions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.19449","kind":"arxiv","version":3},"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":"sha256:491816cb4c915149fb7d56582128ca810152ebe675ca83986cbe83838a03ba4a","target":"record","created_at":"2026-07-05T10:47:55Z","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":"4c2e4337acbb42aceaca7be898aadf7e98ce90d8f1f4cee0767bfa6e1ef85064","cross_cats_sorted":["cs.LG","stat.CO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-10-25T10:23:34Z","title_canon_sha256":"a4491717a168b086ed7031b2fb53ca94aff7cb45d0b9974a6c77d69eae0b3b5c"},"schema_version":"1.0","source":{"id":"2410.19449","kind":"arxiv","version":3}},"canonical_sha256":"b3d713d2f1c44e60a1fd2900096ad0df58ee6fdee4bbc4fa5ce6d11f23d5659e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3d713d2f1c44e60a1fd2900096ad0df58ee6fdee4bbc4fa5ce6d11f23d5659e","first_computed_at":"2026-07-05T10:47:55.918510Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:47:55.918510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vtVGegpYlD7EqIvmKoCRASROlYGeyDA9nbfja/2f1QQKa49tOhbp1U5FqUXuAi6q6DnrI54Y4OcOT4y1j6IpDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:47:55.919011Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.19449","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:491816cb4c915149fb7d56582128ca810152ebe675ca83986cbe83838a03ba4a","sha256:2d582291f2c0df82002c2f5435b9f93d880c0fe4a5567c474352b68b34bbeeb7"],"state_sha256":"b50537c143b012567817a7161b632b8718649615df72523d03946d43a682c8ba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3v+NofHFD0AGVYA0cRGUjRm78SiEcqL/dgg5/GfXwLtu9tr3JyERi4fCtsRjucqAcVJX0TfAEVhvs+zKaFH+Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T21:31:56.456795Z","bundle_sha256":"9f2a0583262e06af3b9c7558576b40ad94e9db9a205a23a0889ad6aac95656f8"}}