{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:657CRF7CYZXRYVI2D42QODYX2M","short_pith_number":"pith:657CRF7C","canonical_record":{"source":{"id":"1905.10768","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-26T09:27:44Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"501bc14cdddae5e81ac6009055b7ebeed068be0d3cb4ed1fb3978efbe1ecf803","abstract_canon_sha256":"c889f5d355842e80f96572c4e70342ad422bbbb659c83e4a165314066e5ceab1"},"schema_version":"1.0"},"canonical_sha256":"f77e2897e2c66f1c551a1f35070f17d32da837382b5d9be7271789d4e5ab8111","source":{"kind":"arxiv","id":"1905.10768","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10768","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10768v2","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10768","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_12","alias_value":"657CRF7CYZXR","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_16","alias_value":"657CRF7CYZXRYVI2","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_8","alias_value":"657CRF7C","created_at":"2026-07-05T01:08:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:657CRF7CYZXRYVI2D42QODYX2M","target":"record","payload":{"canonical_record":{"source":{"id":"1905.10768","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-26T09:27:44Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"501bc14cdddae5e81ac6009055b7ebeed068be0d3cb4ed1fb3978efbe1ecf803","abstract_canon_sha256":"c889f5d355842e80f96572c4e70342ad422bbbb659c83e4a165314066e5ceab1"},"schema_version":"1.0"},"canonical_sha256":"f77e2897e2c66f1c551a1f35070f17d32da837382b5d9be7271789d4e5ab8111","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:08:23.584723Z","signature_b64":"rGNZmu0bPkue+3Oq0dS1wZ12iDrv/dsg6HwTu2Zvpi0fTujOa9GaiB0PfNEgeBZchRqaKPytyM8W8UKMd8s7Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f77e2897e2c66f1c551a1f35070f17d32da837382b5d9be7271789d4e5ab8111","last_reissued_at":"2026-07-05T01:08:23.584295Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:08:23.584295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.10768","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":"2026-07-05T01:08:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iPRUu+ixSiX/OpP241Z8p4UKBS/8NujwOe5e8uh9pwLK7+BofKgQAIhczlHawtUxldN05o3n62jXZ8ZP6nNsBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:25:03.421055Z"},"content_sha256":"2143afdf44cbebba4dded608897d4fc1f831a5249ca0d2500028e1234451d164","schema_version":"1.0","event_id":"sha256:2143afdf44cbebba4dded608897d4fc1f831a5249ca0d2500028e1234451d164"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:657CRF7CYZXRYVI2D42QODYX2M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Precision-Recall Curves Using Information Divergence Frontiers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Josip Djolonga, Marco Cuturi, Mario Lucic, Olivier Bachem, Olivier Bousquet, Sylvain Gelly","submitted_at":"2019-05-26T09:27:44Z","abstract_excerpt":"Despite the tremendous progress in the estimation of generative models, the development of tools for diagnosing their failures and assessing their performance has advanced at a much slower pace. Recent developments have investigated metrics that quantify which parts of the true distribution is modeled well, and, on the contrary, what the model fails to capture, akin to precision and recall in information retrieval. In this paper, we present a general evaluation framework for generative models that measures the trade-off between precision and recall using R\\'enyi divergences. Our framework prov"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10768","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/1905.10768/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":"2026-07-05T01:08:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+xVXzvR0Zz69tkNJfk07dDfJC6ArQbx94w2pcq80b0k15ZTgPbJcCpO9Do8WG1xku6waX6sTgixYO18bRXD3Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T20:25:03.421561Z"},"content_sha256":"3a8f8742dae957d8c89b68e41b412a5ec3bce1df07ad4d537a784c38ef66edd3","schema_version":"1.0","event_id":"sha256:3a8f8742dae957d8c89b68e41b412a5ec3bce1df07ad4d537a784c38ef66edd3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/657CRF7CYZXRYVI2D42QODYX2M/bundle.json","state_url":"https://pith.science/pith/657CRF7CYZXRYVI2D42QODYX2M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/657CRF7CYZXRYVI2D42QODYX2M/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":"2026-08-10T20:25:03Z","links":{"resolver":"https://pith.science/pith/657CRF7CYZXRYVI2D42QODYX2M","bundle":"https://pith.science/pith/657CRF7CYZXRYVI2D42QODYX2M/bundle.json","state":"https://pith.science/pith/657CRF7CYZXRYVI2D42QODYX2M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/657CRF7CYZXRYVI2D42QODYX2M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:657CRF7CYZXRYVI2D42QODYX2M","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":"c889f5d355842e80f96572c4e70342ad422bbbb659c83e4a165314066e5ceab1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-26T09:27:44Z","title_canon_sha256":"501bc14cdddae5e81ac6009055b7ebeed068be0d3cb4ed1fb3978efbe1ecf803"},"schema_version":"1.0","source":{"id":"1905.10768","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10768","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10768v2","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10768","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_12","alias_value":"657CRF7CYZXR","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_16","alias_value":"657CRF7CYZXRYVI2","created_at":"2026-07-05T01:08:23Z"},{"alias_kind":"pith_short_8","alias_value":"657CRF7C","created_at":"2026-07-05T01:08:23Z"}],"graph_snapshots":[{"event_id":"sha256:3a8f8742dae957d8c89b68e41b412a5ec3bce1df07ad4d537a784c38ef66edd3","target":"graph","created_at":"2026-07-05T01:08:23Z","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/1905.10768/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the tremendous progress in the estimation of generative models, the development of tools for diagnosing their failures and assessing their performance has advanced at a much slower pace. Recent developments have investigated metrics that quantify which parts of the true distribution is modeled well, and, on the contrary, what the model fails to capture, akin to precision and recall in information retrieval. In this paper, we present a general evaluation framework for generative models that measures the trade-off between precision and recall using R\\'enyi divergences. Our framework prov","authors_text":"Josip Djolonga, Marco Cuturi, Mario Lucic, Olivier Bachem, Olivier Bousquet, Sylvain Gelly","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-26T09:27:44Z","title":"Precision-Recall Curves Using Information Divergence Frontiers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10768","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":"sha256:2143afdf44cbebba4dded608897d4fc1f831a5249ca0d2500028e1234451d164","target":"record","created_at":"2026-07-05T01:08:23Z","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":"c889f5d355842e80f96572c4e70342ad422bbbb659c83e4a165314066e5ceab1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-26T09:27:44Z","title_canon_sha256":"501bc14cdddae5e81ac6009055b7ebeed068be0d3cb4ed1fb3978efbe1ecf803"},"schema_version":"1.0","source":{"id":"1905.10768","kind":"arxiv","version":2}},"canonical_sha256":"f77e2897e2c66f1c551a1f35070f17d32da837382b5d9be7271789d4e5ab8111","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f77e2897e2c66f1c551a1f35070f17d32da837382b5d9be7271789d4e5ab8111","first_computed_at":"2026-07-05T01:08:23.584295Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:08:23.584295Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rGNZmu0bPkue+3Oq0dS1wZ12iDrv/dsg6HwTu2Zvpi0fTujOa9GaiB0PfNEgeBZchRqaKPytyM8W8UKMd8s7Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:08:23.584723Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.10768","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2143afdf44cbebba4dded608897d4fc1f831a5249ca0d2500028e1234451d164","sha256:3a8f8742dae957d8c89b68e41b412a5ec3bce1df07ad4d537a784c38ef66edd3"],"state_sha256":"7c59a62c8b24c02c93101b647252f1df4deb714c7996715fa24be5bcf8841c63"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XfwQmOJqXnq8YITFfsb3w7ITPO3A0jgN8FWxJIi65bTFonFCJPgNv3DwXE2HqLqev6YpfiO0HDg/2AkJ14j3Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T20:25:03.426465Z","bundle_sha256":"d5828b325c2e48702e05c2dc6e2025d9bfb15287a7917d77c7a5aa5ef0d8631d"}}