{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:TPZBPZ6EZEU5G43CPACMVK6AXR","short_pith_number":"pith:TPZBPZ6E","schema_version":"1.0","canonical_sha256":"9bf217e7c4c929d373627804caabc0bc4f488206aac97554d394943461542c95","source":{"kind":"arxiv","id":"2411.15290","version":1},"attestation_state":"computed","paper":{"title":"GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Gabriel Cort\\^es, Nuno Louren\\c{c}o, Penousal Machado","submitted_at":"2024-11-22T17:24:19Z","abstract_excerpt":"Artificial Intelligence (AI) has driven innovations and created new opportunities across various sectors. However, leveraging domain-specific knowledge often requires automated tools to design and configure models effectively. In the case of Deep Neural Networks (DNNs), researchers and practitioners usually resort to Neural Architecture Search (NAS) approaches, which are resource- and time-intensive, requiring the training and evaluation of numerous candidate architectures. This raises sustainability concerns, particularly due to the high energy demands involved, creating a paradox: the pursui"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2411.15290","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-22T17:24:19Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"540f21cfbfcdd646392bcd17078dd8f941afb0d58d6837c5f9f4dc5034064ab2","abstract_canon_sha256":"56cabd0203e21aa6faac2ec81b3243b9829f952352f55926a33ccf10074d8c2e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:39:32.605333Z","signature_b64":"bXu4ad4Ks8FUD3Ur6RYu2JR458FwVSLh3aTQCe+qPV3jF0Rsy98JyZRxsWDop2AzFy2y7LR5pCXqdB/C3xsODg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9bf217e7c4c929d373627804caabc0bc4f488206aac97554d394943461542c95","last_reissued_at":"2026-07-05T09:39:32.604860Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:39:32.604860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NAS","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Gabriel Cort\\^es, Nuno Louren\\c{c}o, Penousal Machado","submitted_at":"2024-11-22T17:24:19Z","abstract_excerpt":"Artificial Intelligence (AI) has driven innovations and created new opportunities across various sectors. However, leveraging domain-specific knowledge often requires automated tools to design and configure models effectively. In the case of Deep Neural Networks (DNNs), researchers and practitioners usually resort to Neural Architecture Search (NAS) approaches, which are resource- and time-intensive, requiring the training and evaluation of numerous candidate architectures. This raises sustainability concerns, particularly due to the high energy demands involved, creating a paradox: the pursui"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.15290","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/2411.15290/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2411.15290","created_at":"2026-07-05T09:39:32.604919+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.15290v1","created_at":"2026-07-05T09:39:32.604919+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.15290","created_at":"2026-07-05T09:39:32.604919+00:00"},{"alias_kind":"pith_short_12","alias_value":"TPZBPZ6EZEU5","created_at":"2026-07-05T09:39:32.604919+00:00"},{"alias_kind":"pith_short_16","alias_value":"TPZBPZ6EZEU5G43C","created_at":"2026-07-05T09:39:32.604919+00:00"},{"alias_kind":"pith_short_8","alias_value":"TPZBPZ6E","created_at":"2026-07-05T09:39:32.604919+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR","json":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR.json","graph_json":"https://pith.science/api/pith-number/TPZBPZ6EZEU5G43CPACMVK6AXR/graph.json","events_json":"https://pith.science/api/pith-number/TPZBPZ6EZEU5G43CPACMVK6AXR/events.json","paper":"https://pith.science/paper/TPZBPZ6E"},"agent_actions":{"view_html":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR","download_json":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR.json","view_paper":"https://pith.science/paper/TPZBPZ6E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.15290&json=true","fetch_graph":"https://pith.science/api/pith-number/TPZBPZ6EZEU5G43CPACMVK6AXR/graph.json","fetch_events":"https://pith.science/api/pith-number/TPZBPZ6EZEU5G43CPACMVK6AXR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR/action/storage_attestation","attest_author":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR/action/author_attestation","sign_citation":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR/action/citation_signature","submit_replication":"https://pith.science/pith/TPZBPZ6EZEU5G43CPACMVK6AXR/action/replication_record"}},"created_at":"2026-07-05T09:39:32.604919+00:00","updated_at":"2026-07-05T09:39:32.604919+00:00"}