{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HT3JATJRQSBHH4ZT74H2UCRY2A","short_pith_number":"pith:HT3JATJR","canonical_record":{"source":{"id":"2508.01217","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-02T06:19:23Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5fafe6216f6bc400471704fbed361ce84c39758f5d31d3174b3701e52280a461","abstract_canon_sha256":"d2d6f09027f0d6b51a57efb2ff389def655c6965103f1817581e9e4fe5ace8ca"},"schema_version":"1.0"},"canonical_sha256":"3cf6904d31848273f333ff0faa0a38d017254d8b103797100a624719f4b393b1","source":{"kind":"arxiv","id":"2508.01217","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01217","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01217v1","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01217","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_12","alias_value":"HT3JATJRQSBH","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_16","alias_value":"HT3JATJRQSBHH4ZT","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_8","alias_value":"HT3JATJR","created_at":"2026-07-05T11:47:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HT3JATJRQSBHH4ZT74H2UCRY2A","target":"record","payload":{"canonical_record":{"source":{"id":"2508.01217","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-02T06:19:23Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5fafe6216f6bc400471704fbed361ce84c39758f5d31d3174b3701e52280a461","abstract_canon_sha256":"d2d6f09027f0d6b51a57efb2ff389def655c6965103f1817581e9e4fe5ace8ca"},"schema_version":"1.0"},"canonical_sha256":"3cf6904d31848273f333ff0faa0a38d017254d8b103797100a624719f4b393b1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:47:35.045140Z","signature_b64":"aN5Mj/YtjYSLaQw7fg4DxO/PbR4wjr+AXwEgN61Gv7wfiWmyn6RcUhTzqf0qgq+JM1Sx3Kr++4vXfj5/cCHeAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3cf6904d31848273f333ff0faa0a38d017254d8b103797100a624719f4b393b1","last_reissued_at":"2026-07-05T11:47:35.044676Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:47:35.044676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.01217","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":"2026-07-05T11:47:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qHn9KC+QsRg9VxAuGeZKCUI1auqS3JdwCptqVbFb26B2JWTdN38FFJ050b46hdAZ6TTvzThHqhvl+DJ64BhuCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:34:21.372526Z"},"content_sha256":"a17c6328bb25030932b93a5a9e04c5191292e888dae9e72671a29d0dd3057fa0","schema_version":"1.0","event_id":"sha256:a17c6328bb25030932b93a5a9e04c5191292e888dae9e72671a29d0dd3057fa0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HT3JATJRQSBHH4ZT74H2UCRY2A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Uncertainty Quantification for Large-Scale Deep Networks via Post-StoNet Modeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Faming Liang, Yan Sun","submitted_at":"2025-08-02T06:19:23Z","abstract_excerpt":"Deep learning has revolutionized modern data science. However, how to accurately quantify the uncertainty of predictions from large-scale deep neural networks (DNNs) remains an unresolved issue. To address this issue, we introduce a novel post-processing approach. This approach feeds the output from the last hidden layer of a pre-trained large-scale DNN model into a stochastic neural network (StoNet), then trains the StoNet with a sparse penalty on a validation dataset and constructs prediction intervals for future observations. We establish a theoretical guarantee for the validity of this app"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01217","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/2508.01217/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":"2026-07-05T11:47:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WHA68/xAEMS+vS9CE82AvwgnanAnEPU1ipxQ5cgYek6tg2TvkVqSHEvgMzHWi3P56PpLT/J2sfBr1BSCn8OuDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:34:21.373288Z"},"content_sha256":"e319539deb7f37fdd86aaf49743cb4a08ee7a464f10b6013e6ad57c530af604d","schema_version":"1.0","event_id":"sha256:e319539deb7f37fdd86aaf49743cb4a08ee7a464f10b6013e6ad57c530af604d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/bundle.json","state_url":"https://pith.science/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/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":"2026-08-05T18:34:21Z","links":{"resolver":"https://pith.science/pith/HT3JATJRQSBHH4ZT74H2UCRY2A","bundle":"https://pith.science/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/bundle.json","state":"https://pith.science/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HT3JATJRQSBHH4ZT74H2UCRY2A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HT3JATJRQSBHH4ZT74H2UCRY2A","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":"d2d6f09027f0d6b51a57efb2ff389def655c6965103f1817581e9e4fe5ace8ca","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-02T06:19:23Z","title_canon_sha256":"5fafe6216f6bc400471704fbed361ce84c39758f5d31d3174b3701e52280a461"},"schema_version":"1.0","source":{"id":"2508.01217","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01217","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01217v1","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01217","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_12","alias_value":"HT3JATJRQSBH","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_16","alias_value":"HT3JATJRQSBHH4ZT","created_at":"2026-07-05T11:47:35Z"},{"alias_kind":"pith_short_8","alias_value":"HT3JATJR","created_at":"2026-07-05T11:47:35Z"}],"graph_snapshots":[{"event_id":"sha256:e319539deb7f37fdd86aaf49743cb4a08ee7a464f10b6013e6ad57c530af604d","target":"graph","created_at":"2026-07-05T11:47:35Z","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/2508.01217/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has revolutionized modern data science. However, how to accurately quantify the uncertainty of predictions from large-scale deep neural networks (DNNs) remains an unresolved issue. To address this issue, we introduce a novel post-processing approach. This approach feeds the output from the last hidden layer of a pre-trained large-scale DNN model into a stochastic neural network (StoNet), then trains the StoNet with a sparse penalty on a validation dataset and constructs prediction intervals for future observations. We establish a theoretical guarantee for the validity of this app","authors_text":"Faming Liang, Yan Sun","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-02T06:19:23Z","title":"Uncertainty Quantification for Large-Scale Deep Networks via Post-StoNet Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01217","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:a17c6328bb25030932b93a5a9e04c5191292e888dae9e72671a29d0dd3057fa0","target":"record","created_at":"2026-07-05T11:47:35Z","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":"d2d6f09027f0d6b51a57efb2ff389def655c6965103f1817581e9e4fe5ace8ca","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-02T06:19:23Z","title_canon_sha256":"5fafe6216f6bc400471704fbed361ce84c39758f5d31d3174b3701e52280a461"},"schema_version":"1.0","source":{"id":"2508.01217","kind":"arxiv","version":1}},"canonical_sha256":"3cf6904d31848273f333ff0faa0a38d017254d8b103797100a624719f4b393b1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3cf6904d31848273f333ff0faa0a38d017254d8b103797100a624719f4b393b1","first_computed_at":"2026-07-05T11:47:35.044676Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:47:35.044676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aN5Mj/YtjYSLaQw7fg4DxO/PbR4wjr+AXwEgN61Gv7wfiWmyn6RcUhTzqf0qgq+JM1Sx3Kr++4vXfj5/cCHeAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:47:35.045140Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.01217","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a17c6328bb25030932b93a5a9e04c5191292e888dae9e72671a29d0dd3057fa0","sha256:e319539deb7f37fdd86aaf49743cb4a08ee7a464f10b6013e6ad57c530af604d"],"state_sha256":"5762a7a8231bf92635465cb137ddf5752eb2a6a59ac32c727ed43b5264bb216a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VGVf0m6YN7+rXNnVLQZrDYNgHm5Ay03Swf6zDPJwH2s/YgZo5pZTA8i2GcsetojkJOzutiodAkMBeNc8U24sCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:34:21.378772Z","bundle_sha256":"5ec81768d08be5a26614d5bca1144e1002e4827a31fdbd31169da81473a5d048"}}