{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:6LDB2J3VQVT66NK6QA5OPQ2WQ5","short_pith_number":"pith:6LDB2J3V","canonical_record":{"source":{"id":"2206.00188","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-06-01T02:22:27Z","cross_cats_sorted":[],"title_canon_sha256":"ea8b11499cd957f4acc82583918fd011ce9e2f580cb840f00550daaf9e3a10ac","abstract_canon_sha256":"96c5f589619f45c0ddbd87548cea579f0d2c5417251e0e0486bfced1cdb5753c"},"schema_version":"1.0"},"canonical_sha256":"f2c61d27758567ef355e803ae7c3568776a8bf45d780500e1b854b8249de75c8","source":{"kind":"arxiv","id":"2206.00188","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.00188","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"arxiv_version","alias_value":"2206.00188v1","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.00188","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_12","alias_value":"6LDB2J3VQVT6","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_16","alias_value":"6LDB2J3VQVT66NK6","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_8","alias_value":"6LDB2J3V","created_at":"2026-07-05T04:28:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:6LDB2J3VQVT66NK6QA5OPQ2WQ5","target":"record","payload":{"canonical_record":{"source":{"id":"2206.00188","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-06-01T02:22:27Z","cross_cats_sorted":[],"title_canon_sha256":"ea8b11499cd957f4acc82583918fd011ce9e2f580cb840f00550daaf9e3a10ac","abstract_canon_sha256":"96c5f589619f45c0ddbd87548cea579f0d2c5417251e0e0486bfced1cdb5753c"},"schema_version":"1.0"},"canonical_sha256":"f2c61d27758567ef355e803ae7c3568776a8bf45d780500e1b854b8249de75c8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:28:45.076705Z","signature_b64":"gSxovyRE+jBk8zzMUrdh/000y1pAlQ5N3H2uluYo5W/W1E+kSVfP/GEfJvlH/PDU48JC72NUY70JUfudKeElBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2c61d27758567ef355e803ae7c3568776a8bf45d780500e1b854b8249de75c8","last_reissued_at":"2026-07-05T04:28:45.076292Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:28:45.076292Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.00188","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":"2026-07-05T04:28:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OpldGJCOkaBT8ypcOuuCpYmbt8Sanzj/7fwc+/TyidMezleMAU7LwWmPodAGi0Hek0u3gx4fa5ug7OnMynzQAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T23:50:09.607583Z"},"content_sha256":"3289beebbcb4585778db7ed4c7c13964652148657bc9be63de7b46aba0d77118","schema_version":"1.0","event_id":"sha256:3289beebbcb4585778db7ed4c7c13964652148657bc9be63de7b46aba0d77118"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:6LDB2J3VQVT66NK6QA5OPQ2WQ5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Benchmark of DNN Model Search at Deployment Time","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Amitabh Das, Arindam Jain, Jia Zou, Lixi Zhou, Yingzhen Yang, Zijie Wang","submitted_at":"2022-06-01T02:22:27Z","abstract_excerpt":"Deep learning has become the most popular direction in machine learning and artificial intelligence. However, the preparation of training data, as well as model training, are often time-consuming and become the bottleneck of the end-to-end machine learning lifecycle. Reusing models for inferring a dataset can avoid the costs of retraining. However, when there are multiple candidate models, it is challenging to discover the right model for reuse. Although there exist a number of model sharing platforms such as ModelDB, TensorFlow Hub, PyTorch Hub, and DLHub, most of these systems require model "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.00188","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/2206.00188/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":"2026-07-05T04:28:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/eUK/8fLQ5VxDYLk5kQfy3mPf0GE6b53jmMiJtEnAZqSwO6Z0Yy4SpCkPRHEUAZR9c3SWrWRW0bxZ3Ihslr/DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T23:50:09.608098Z"},"content_sha256":"9be76912a41bfe8d154245e1e19df68814e0bef2abab1c82535186a14e43c9df","schema_version":"1.0","event_id":"sha256:9be76912a41bfe8d154245e1e19df68814e0bef2abab1c82535186a14e43c9df"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/bundle.json","state_url":"https://pith.science/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/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":"2026-07-31T23:50:09Z","links":{"resolver":"https://pith.science/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5","bundle":"https://pith.science/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/bundle.json","state":"https://pith.science/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6LDB2J3VQVT66NK6QA5OPQ2WQ5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6LDB2J3VQVT66NK6QA5OPQ2WQ5","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":"96c5f589619f45c0ddbd87548cea579f0d2c5417251e0e0486bfced1cdb5753c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-06-01T02:22:27Z","title_canon_sha256":"ea8b11499cd957f4acc82583918fd011ce9e2f580cb840f00550daaf9e3a10ac"},"schema_version":"1.0","source":{"id":"2206.00188","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.00188","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"arxiv_version","alias_value":"2206.00188v1","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.00188","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_12","alias_value":"6LDB2J3VQVT6","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_16","alias_value":"6LDB2J3VQVT66NK6","created_at":"2026-07-05T04:28:45Z"},{"alias_kind":"pith_short_8","alias_value":"6LDB2J3V","created_at":"2026-07-05T04:28:45Z"}],"graph_snapshots":[{"event_id":"sha256:9be76912a41bfe8d154245e1e19df68814e0bef2abab1c82535186a14e43c9df","target":"graph","created_at":"2026-07-05T04:28:45Z","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/2206.00188/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has become the most popular direction in machine learning and artificial intelligence. However, the preparation of training data, as well as model training, are often time-consuming and become the bottleneck of the end-to-end machine learning lifecycle. Reusing models for inferring a dataset can avoid the costs of retraining. However, when there are multiple candidate models, it is challenging to discover the right model for reuse. Although there exist a number of model sharing platforms such as ModelDB, TensorFlow Hub, PyTorch Hub, and DLHub, most of these systems require model ","authors_text":"Amitabh Das, Arindam Jain, Jia Zou, Lixi Zhou, Yingzhen Yang, Zijie Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-06-01T02:22:27Z","title":"Benchmark of DNN Model Search at Deployment Time"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.00188","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":"sha256:3289beebbcb4585778db7ed4c7c13964652148657bc9be63de7b46aba0d77118","target":"record","created_at":"2026-07-05T04:28:45Z","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":"96c5f589619f45c0ddbd87548cea579f0d2c5417251e0e0486bfced1cdb5753c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2022-06-01T02:22:27Z","title_canon_sha256":"ea8b11499cd957f4acc82583918fd011ce9e2f580cb840f00550daaf9e3a10ac"},"schema_version":"1.0","source":{"id":"2206.00188","kind":"arxiv","version":1}},"canonical_sha256":"f2c61d27758567ef355e803ae7c3568776a8bf45d780500e1b854b8249de75c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f2c61d27758567ef355e803ae7c3568776a8bf45d780500e1b854b8249de75c8","first_computed_at":"2026-07-05T04:28:45.076292Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:28:45.076292Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gSxovyRE+jBk8zzMUrdh/000y1pAlQ5N3H2uluYo5W/W1E+kSVfP/GEfJvlH/PDU48JC72NUY70JUfudKeElBA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:28:45.076705Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.00188","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3289beebbcb4585778db7ed4c7c13964652148657bc9be63de7b46aba0d77118","sha256:9be76912a41bfe8d154245e1e19df68814e0bef2abab1c82535186a14e43c9df"],"state_sha256":"d1f57196c75a19fa5a1a15b69763a341a10f28fb3ee9bf44fd0039db8547b813"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d79m+eD0vDMNmPMdDQ1UMuIbYrV5TMBF7x7n2x0wGt/xSPiJSEXT6nyauZgHtkMwkTzrgjWB09RWTFARIcbSDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T23:50:09.612991Z","bundle_sha256":"de62ce4a25a087dd06adaa2c3ba0560123d7eeec14fd8fd490e855d84673c8be"}}