{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:MXLXRQY7ZRBWDJ33HTOT43OTTE","short_pith_number":"pith:MXLXRQY7","canonical_record":{"source":{"id":"2212.06905","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-12-13T21:15:41Z","cross_cats_sorted":[],"title_canon_sha256":"d85bfd5f66f9b7ab8ec36510f67136d786791a9258921d9f8f98db2052ad50a7","abstract_canon_sha256":"ac2cf33d2607b57a6b33e687efdeb1286e7582dbeaf16583400471af9563a5aa"},"schema_version":"1.0"},"canonical_sha256":"65d778c31fcc4361a77b3cdd3e6dd399377cd3928791e47c7a5a078e8b4c5454","source":{"kind":"arxiv","id":"2212.06905","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.06905","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"2212.06905v2","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.06905","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"MXLXRQY7ZRBW","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_16","alias_value":"MXLXRQY7ZRBWDJ33","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_8","alias_value":"MXLXRQY7","created_at":"2026-07-05T07:42:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:MXLXRQY7ZRBWDJ33HTOT43OTTE","target":"record","payload":{"canonical_record":{"source":{"id":"2212.06905","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-12-13T21:15:41Z","cross_cats_sorted":[],"title_canon_sha256":"d85bfd5f66f9b7ab8ec36510f67136d786791a9258921d9f8f98db2052ad50a7","abstract_canon_sha256":"ac2cf33d2607b57a6b33e687efdeb1286e7582dbeaf16583400471af9563a5aa"},"schema_version":"1.0"},"canonical_sha256":"65d778c31fcc4361a77b3cdd3e6dd399377cd3928791e47c7a5a078e8b4c5454","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:42:38.492468Z","signature_b64":"7GxsSdtspcZMli39+rLLl6dmvqI4FIS7iElw1/7jdYiOqcjvFL8zGRuFKgK9PzySuFkpkCaQ+vZxm0YF94vUCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65d778c31fcc4361a77b3cdd3e6dd399377cd3928791e47c7a5a078e8b4c5454","last_reissued_at":"2026-07-05T07:42:38.492028Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:42:38.492028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.06905","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":"2026-07-05T07:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2+jmia70y1Lp64QMXgzQPfg9KVAdG7dUhvwX1fzacoC652EosRFKQQTmqvwkUtyTOqGMc6rdhYBPuikZlx3TAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:06:23.681054Z"},"content_sha256":"aaa1b303b52bbe4fb0c2b2c300d77b79f5b9b0183020dcf4a53c7968c894eacf","schema_version":"1.0","event_id":"sha256:aaa1b303b52bbe4fb0c2b2c300d77b79f5b9b0183020dcf4a53c7968c894eacf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:MXLXRQY7ZRBWDJ33HTOT43OTTE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Query Time Optimized Deep Learning Based Video Inference System","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CE","authors_text":"Mingren Shen, Shuoxuan Dong, Xiuyuan He","submitted_at":"2022-12-13T21:15:41Z","abstract_excerpt":"This is a project report about how we tune Focus[1], a video inference system that provides low cost and low latency, through two phases. In this report, we will decrease the query time by saving the middle layer output of the neural network. This is a trade-off strategy that involves using more space to save time. We show how this scheme works using prototype systems, and it saves 20% of the time. The code repository URL is here, https://github.com/iphyer/CS744 FocousIngestOpt."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.06905","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/2212.06905/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":"2026-07-05T07:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FsEP7mF1ZxywvlSg5QXFPAd1eYmBnurMc4pW0nrNTsUc0gSiZ1XBxXa2BvDAaK7rN80FRJFTmBB47ESLRmU3Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:06:23.681444Z"},"content_sha256":"9c79883c97e4e2c10f3cb4b589f264341d7c2458c23c2d4275728f5d97d76751","schema_version":"1.0","event_id":"sha256:9c79883c97e4e2c10f3cb4b589f264341d7c2458c23c2d4275728f5d97d76751"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/bundle.json","state_url":"https://pith.science/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/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":"2026-07-07T09:06:23Z","links":{"resolver":"https://pith.science/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE","bundle":"https://pith.science/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/bundle.json","state":"https://pith.science/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MXLXRQY7ZRBWDJ33HTOT43OTTE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:MXLXRQY7ZRBWDJ33HTOT43OTTE","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":"ac2cf33d2607b57a6b33e687efdeb1286e7582dbeaf16583400471af9563a5aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-12-13T21:15:41Z","title_canon_sha256":"d85bfd5f66f9b7ab8ec36510f67136d786791a9258921d9f8f98db2052ad50a7"},"schema_version":"1.0","source":{"id":"2212.06905","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.06905","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"2212.06905v2","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.06905","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"MXLXRQY7ZRBW","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_16","alias_value":"MXLXRQY7ZRBWDJ33","created_at":"2026-07-05T07:42:38Z"},{"alias_kind":"pith_short_8","alias_value":"MXLXRQY7","created_at":"2026-07-05T07:42:38Z"}],"graph_snapshots":[{"event_id":"sha256:9c79883c97e4e2c10f3cb4b589f264341d7c2458c23c2d4275728f5d97d76751","target":"graph","created_at":"2026-07-05T07:42:38Z","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/2212.06905/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This is a project report about how we tune Focus[1], a video inference system that provides low cost and low latency, through two phases. In this report, we will decrease the query time by saving the middle layer output of the neural network. This is a trade-off strategy that involves using more space to save time. We show how this scheme works using prototype systems, and it saves 20% of the time. The code repository URL is here, https://github.com/iphyer/CS744 FocousIngestOpt.","authors_text":"Mingren Shen, Shuoxuan Dong, Xiuyuan He","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-12-13T21:15:41Z","title":"Query Time Optimized Deep Learning Based Video Inference System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.06905","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:aaa1b303b52bbe4fb0c2b2c300d77b79f5b9b0183020dcf4a53c7968c894eacf","target":"record","created_at":"2026-07-05T07:42:38Z","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":"ac2cf33d2607b57a6b33e687efdeb1286e7582dbeaf16583400471af9563a5aa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CE","submitted_at":"2022-12-13T21:15:41Z","title_canon_sha256":"d85bfd5f66f9b7ab8ec36510f67136d786791a9258921d9f8f98db2052ad50a7"},"schema_version":"1.0","source":{"id":"2212.06905","kind":"arxiv","version":2}},"canonical_sha256":"65d778c31fcc4361a77b3cdd3e6dd399377cd3928791e47c7a5a078e8b4c5454","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65d778c31fcc4361a77b3cdd3e6dd399377cd3928791e47c7a5a078e8b4c5454","first_computed_at":"2026-07-05T07:42:38.492028Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:42:38.492028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7GxsSdtspcZMli39+rLLl6dmvqI4FIS7iElw1/7jdYiOqcjvFL8zGRuFKgK9PzySuFkpkCaQ+vZxm0YF94vUCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:42:38.492468Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.06905","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aaa1b303b52bbe4fb0c2b2c300d77b79f5b9b0183020dcf4a53c7968c894eacf","sha256:9c79883c97e4e2c10f3cb4b589f264341d7c2458c23c2d4275728f5d97d76751"],"state_sha256":"140089d77fc1c28f6bc7dbfe6d30603bc40b047f8478091abb26c68d0ddbb504"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rT9sVarMOVb/MRovUl4qRZ93nDOK58A/KYLYfPtwmg4sgqj8Kv2nQSQwwVBk7u9ve1ynypeUtvQPp9cV90YpAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T09:06:23.683466Z","bundle_sha256":"8579e6730bcd30d262c541308898993dd66838713a81598d5901f684effb1d84"}}