{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:E2UZIUOELREYUTRM4HEXTVWTWQ","short_pith_number":"pith:E2UZIUOE","canonical_record":{"source":{"id":"2401.16692","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-30T02:38:23Z","cross_cats_sorted":[],"title_canon_sha256":"87a5e78875746e6680ed324f6822422a2a28eedfe77f1acaf664d84f30d63090","abstract_canon_sha256":"1e625ec62722ffa94c3931c9dfa6f22dbd6089f878818636aa1d6122b011eed7"},"schema_version":"1.0"},"canonical_sha256":"26a99451c45c498a4e2ce1c979d6d3b4117173eb06aaef8e52c171bddb3e8d36","source":{"kind":"arxiv","id":"2401.16692","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.16692","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"arxiv_version","alias_value":"2401.16692v2","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.16692","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_12","alias_value":"E2UZIUOELREY","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_16","alias_value":"E2UZIUOELREYUTRM","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_8","alias_value":"E2UZIUOE","created_at":"2026-07-05T08:20:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:E2UZIUOELREYUTRM4HEXTVWTWQ","target":"record","payload":{"canonical_record":{"source":{"id":"2401.16692","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-30T02:38:23Z","cross_cats_sorted":[],"title_canon_sha256":"87a5e78875746e6680ed324f6822422a2a28eedfe77f1acaf664d84f30d63090","abstract_canon_sha256":"1e625ec62722ffa94c3931c9dfa6f22dbd6089f878818636aa1d6122b011eed7"},"schema_version":"1.0"},"canonical_sha256":"26a99451c45c498a4e2ce1c979d6d3b4117173eb06aaef8e52c171bddb3e8d36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:20:27.415218Z","signature_b64":"bcGj4+9TeZG78LVhD3DntHCwbZPrC7vKL9A9IGCD8spSzgJWnRHSDXN5RkQahP+CrNGGLVKG1cDOma9I2IOhDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"26a99451c45c498a4e2ce1c979d6d3b4117173eb06aaef8e52c171bddb3e8d36","last_reissued_at":"2026-07-05T08:20:27.414754Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:20:27.414754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.16692","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":"2026-07-05T08:20:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bdGIv6dbhop9xEgLfhHD1LYOaEbR2cQx8YdawmcADpIIk769bzJJGSNRCqsD5YFjucT4B6FfgmkX6U3/v1qXAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:02:27.292382Z"},"content_sha256":"663241ebcdd6047b8e5fb9ede39de6d121690fb3194dc7ace8acbecf0b58caa2","schema_version":"1.0","event_id":"sha256:663241ebcdd6047b8e5fb9ede39de6d121690fb3194dc7ace8acbecf0b58caa2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:E2UZIUOELREYUTRM4HEXTVWTWQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kun Zhang, Nian Si, Xiangchen Song, Yewen Fan","submitted_at":"2024-01-30T02:38:23Z","abstract_excerpt":"The adoption of deep learning across various fields has been extensive, yet there is a lack of focus on evaluating the performance of deep learning pipelines. Typically, with the increased use of large datasets and complex models, the training process is run only once and the result is compared to previous benchmarks. This practice can lead to imprecise comparisons due to the variance in neural network evaluation metrics, which stems from the inherent randomness in the training process. Traditional solutions, such as running the training process multiple times, are often infeasible due to comp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.16692","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/2401.16692/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":"2026-07-05T08:20:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vc7q83fyEnNi7+KnBVariQYK5/WqsI2YUrkTjp89JxyNK3+MvZYFN/oEavcypQ34zDz+zGuE76ys2PM94qgnBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T06:02:27.292996Z"},"content_sha256":"0378c1cf92f1921778fd92e5799fdfbaf7dbe3b290f17814e205a0bfbb5cf943","schema_version":"1.0","event_id":"sha256:0378c1cf92f1921778fd92e5799fdfbaf7dbe3b290f17814e205a0bfbb5cf943"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/bundle.json","state_url":"https://pith.science/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/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":"2026-08-15T06:02:27Z","links":{"resolver":"https://pith.science/pith/E2UZIUOELREYUTRM4HEXTVWTWQ","bundle":"https://pith.science/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/bundle.json","state":"https://pith.science/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E2UZIUOELREYUTRM4HEXTVWTWQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:E2UZIUOELREYUTRM4HEXTVWTWQ","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":"1e625ec62722ffa94c3931c9dfa6f22dbd6089f878818636aa1d6122b011eed7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-30T02:38:23Z","title_canon_sha256":"87a5e78875746e6680ed324f6822422a2a28eedfe77f1acaf664d84f30d63090"},"schema_version":"1.0","source":{"id":"2401.16692","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.16692","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"arxiv_version","alias_value":"2401.16692v2","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.16692","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_12","alias_value":"E2UZIUOELREY","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_16","alias_value":"E2UZIUOELREYUTRM","created_at":"2026-07-05T08:20:27Z"},{"alias_kind":"pith_short_8","alias_value":"E2UZIUOE","created_at":"2026-07-05T08:20:27Z"}],"graph_snapshots":[{"event_id":"sha256:0378c1cf92f1921778fd92e5799fdfbaf7dbe3b290f17814e205a0bfbb5cf943","target":"graph","created_at":"2026-07-05T08:20:27Z","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/2401.16692/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The adoption of deep learning across various fields has been extensive, yet there is a lack of focus on evaluating the performance of deep learning pipelines. Typically, with the increased use of large datasets and complex models, the training process is run only once and the result is compared to previous benchmarks. This practice can lead to imprecise comparisons due to the variance in neural network evaluation metrics, which stems from the inherent randomness in the training process. Traditional solutions, such as running the training process multiple times, are often infeasible due to comp","authors_text":"Kun Zhang, Nian Si, Xiangchen Song, Yewen Fan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-30T02:38:23Z","title":"Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.16692","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":"sha256:663241ebcdd6047b8e5fb9ede39de6d121690fb3194dc7ace8acbecf0b58caa2","target":"record","created_at":"2026-07-05T08:20:27Z","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":"1e625ec62722ffa94c3931c9dfa6f22dbd6089f878818636aa1d6122b011eed7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-30T02:38:23Z","title_canon_sha256":"87a5e78875746e6680ed324f6822422a2a28eedfe77f1acaf664d84f30d63090"},"schema_version":"1.0","source":{"id":"2401.16692","kind":"arxiv","version":2}},"canonical_sha256":"26a99451c45c498a4e2ce1c979d6d3b4117173eb06aaef8e52c171bddb3e8d36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26a99451c45c498a4e2ce1c979d6d3b4117173eb06aaef8e52c171bddb3e8d36","first_computed_at":"2026-07-05T08:20:27.414754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:20:27.414754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bcGj4+9TeZG78LVhD3DntHCwbZPrC7vKL9A9IGCD8spSzgJWnRHSDXN5RkQahP+CrNGGLVKG1cDOma9I2IOhDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:20:27.415218Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.16692","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:663241ebcdd6047b8e5fb9ede39de6d121690fb3194dc7ace8acbecf0b58caa2","sha256:0378c1cf92f1921778fd92e5799fdfbaf7dbe3b290f17814e205a0bfbb5cf943"],"state_sha256":"24a1afc5f5dd61f72166e31ff6eb1149190e781a9a4640c1e6773c6b50a66a12"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iiGznt3q+7Mc0jynX3csbiwgqsiijlL+hvekkRc2L2xmJI76TEqYl2Du3DwgDaX8vtInctkBHjZUFq/3A08tBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T06:02:27.298149Z","bundle_sha256":"e28aef9c72d2168dd42f726b210a9ea514109f487729dc4fa34255f30588c3a6"}}