{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:3BMZWTJBUVNYVHFSVAJPOLLLPL","short_pith_number":"pith:3BMZWTJB","canonical_record":{"source":{"id":"2104.04443","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-09T15:44:06Z","cross_cats_sorted":[],"title_canon_sha256":"5b31b1be6051c36a1a69bddb4a9c8af5f7a55866cb4934d959dcac3b827000f1","abstract_canon_sha256":"22fffcb023ed6920663d0e1ac49b57f2cc6e8843ae396b6e9db00861d8e9ef69"},"schema_version":"1.0"},"canonical_sha256":"d8599b4d21a55b8a9cb2a812f72d6b7ae5cb430bc2195d01be2b15e84328960d","source":{"kind":"arxiv","id":"2104.04443","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.04443","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"arxiv_version","alias_value":"2104.04443v2","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.04443","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_12","alias_value":"3BMZWTJBUVNY","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_16","alias_value":"3BMZWTJBUVNYVHFS","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_8","alias_value":"3BMZWTJB","created_at":"2026-07-05T02:36:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:3BMZWTJBUVNYVHFSVAJPOLLLPL","target":"record","payload":{"canonical_record":{"source":{"id":"2104.04443","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-09T15:44:06Z","cross_cats_sorted":[],"title_canon_sha256":"5b31b1be6051c36a1a69bddb4a9c8af5f7a55866cb4934d959dcac3b827000f1","abstract_canon_sha256":"22fffcb023ed6920663d0e1ac49b57f2cc6e8843ae396b6e9db00861d8e9ef69"},"schema_version":"1.0"},"canonical_sha256":"d8599b4d21a55b8a9cb2a812f72d6b7ae5cb430bc2195d01be2b15e84328960d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:36:49.834985Z","signature_b64":"ijOfzJDVaoX2K+bPG1fQdBKRRpju3+PMsf6Cr9IMGQcbvDU6V7oUZb18a6VZC7/tTrFDmb7zUnG0bemEYIxKDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d8599b4d21a55b8a9cb2a812f72d6b7ae5cb430bc2195d01be2b15e84328960d","last_reissued_at":"2026-07-05T02:36:49.834587Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:36:49.834587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.04443","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":"2026-07-05T02:36:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZKvCaJktmE2DnIRt3+0ri5ilpTw9KUC5StapsvabpGHKVnyfyl22y7JWewhU86lgBtd9RLlZdkhzw9A1CLn0AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:53.337544Z"},"content_sha256":"681f8aa3919971b80cd05993b9eaded257a239d1cab8be9c4e9dc7f4e7d7c11e","schema_version":"1.0","event_id":"sha256:681f8aa3919971b80cd05993b9eaded257a239d1cab8be9c4e9dc7f4e7d7c11e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:3BMZWTJBUVNYVHFSVAJPOLLLPL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Da Feng, Dongsheng Li, Li Shang, Mingzhi Dong, Ning Gu, Qin Lv, Robert P. Dick, Tun Lu, Yingying Zhao, Yujiang Wang","submitted_at":"2021-04-09T15:44:06Z","abstract_excerpt":"Deep-learning-based video processing has yielded transformative results in recent years. However, the video analytics pipeline is energy-intensive due to high data rates and reliance on complex inference algorithms, which limits its adoption in energy-constrained applications. Motivated by the observation of high and variable spatial redundancy and temporal dynamics in video data streams, we design and evaluate an adaptive-resolution optimization framework to minimize the energy use of multi-task video analytics pipelines. Instead of heuristically tuning the input data resolution of individual"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.04443","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/2104.04443/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":"2026-07-05T02:36:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8m4q6HX1LUe7VDdwYjMKH9KwEB+eHpBO6pQZXfIElnfj/33KDYzsFr8aVdXHgWn3lqQPkt1UDv1dm4HSOysXBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:31:53.338081Z"},"content_sha256":"06dc1176be4ece6c1365aa9bbc9d595e4b4ccc53a89016539150453b685ab0e0","schema_version":"1.0","event_id":"sha256:06dc1176be4ece6c1365aa9bbc9d595e4b4ccc53a89016539150453b685ab0e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/bundle.json","state_url":"https://pith.science/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/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":"2026-08-05T02:31:53Z","links":{"resolver":"https://pith.science/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL","bundle":"https://pith.science/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/bundle.json","state":"https://pith.science/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3BMZWTJBUVNYVHFSVAJPOLLLPL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:3BMZWTJBUVNYVHFSVAJPOLLLPL","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":"22fffcb023ed6920663d0e1ac49b57f2cc6e8843ae396b6e9db00861d8e9ef69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-09T15:44:06Z","title_canon_sha256":"5b31b1be6051c36a1a69bddb4a9c8af5f7a55866cb4934d959dcac3b827000f1"},"schema_version":"1.0","source":{"id":"2104.04443","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.04443","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"arxiv_version","alias_value":"2104.04443v2","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.04443","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_12","alias_value":"3BMZWTJBUVNY","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_16","alias_value":"3BMZWTJBUVNYVHFS","created_at":"2026-07-05T02:36:49Z"},{"alias_kind":"pith_short_8","alias_value":"3BMZWTJB","created_at":"2026-07-05T02:36:49Z"}],"graph_snapshots":[{"event_id":"sha256:06dc1176be4ece6c1365aa9bbc9d595e4b4ccc53a89016539150453b685ab0e0","target":"graph","created_at":"2026-07-05T02:36:49Z","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/2104.04443/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep-learning-based video processing has yielded transformative results in recent years. However, the video analytics pipeline is energy-intensive due to high data rates and reliance on complex inference algorithms, which limits its adoption in energy-constrained applications. Motivated by the observation of high and variable spatial redundancy and temporal dynamics in video data streams, we design and evaluate an adaptive-resolution optimization framework to minimize the energy use of multi-task video analytics pipelines. Instead of heuristically tuning the input data resolution of individual","authors_text":"Da Feng, Dongsheng Li, Li Shang, Mingzhi Dong, Ning Gu, Qin Lv, Robert P. Dick, Tun Lu, Yingying Zhao, Yujiang Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-09T15:44:06Z","title":"A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.04443","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":"sha256:681f8aa3919971b80cd05993b9eaded257a239d1cab8be9c4e9dc7f4e7d7c11e","target":"record","created_at":"2026-07-05T02:36:49Z","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":"22fffcb023ed6920663d0e1ac49b57f2cc6e8843ae396b6e9db00861d8e9ef69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-04-09T15:44:06Z","title_canon_sha256":"5b31b1be6051c36a1a69bddb4a9c8af5f7a55866cb4934d959dcac3b827000f1"},"schema_version":"1.0","source":{"id":"2104.04443","kind":"arxiv","version":2}},"canonical_sha256":"d8599b4d21a55b8a9cb2a812f72d6b7ae5cb430bc2195d01be2b15e84328960d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8599b4d21a55b8a9cb2a812f72d6b7ae5cb430bc2195d01be2b15e84328960d","first_computed_at":"2026-07-05T02:36:49.834587Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:36:49.834587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ijOfzJDVaoX2K+bPG1fQdBKRRpju3+PMsf6Cr9IMGQcbvDU6V7oUZb18a6VZC7/tTrFDmb7zUnG0bemEYIxKDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:36:49.834985Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.04443","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:681f8aa3919971b80cd05993b9eaded257a239d1cab8be9c4e9dc7f4e7d7c11e","sha256:06dc1176be4ece6c1365aa9bbc9d595e4b4ccc53a89016539150453b685ab0e0"],"state_sha256":"151d115a3afc2825249b4e0456050c50936be38b14af228fd5e2ba36839d5fce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"49DIrEsqAxqwmcE1xQtWNerYY2c+T+bwCww9mLEOmm3SzvkJKP7+lNd10eHaVHeVMUTeL+wyWmbUYhAa3lnVAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:31:53.344852Z","bundle_sha256":"87ce5b41e451abd13a63d997cc08935bda725f1f0c80c7c4bffbdb680e861602"}}