{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:4YJTTQCNSFMW4NPV6TG2IUPAXU","short_pith_number":"pith:4YJTTQCN","canonical_record":{"source":{"id":"2310.06522","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-10T11:08:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"c4d84959c72c975b9aff6452b6b3043730a6678a42cb1f550e3d959879927593","abstract_canon_sha256":"ed439f50209c2b0d78b2bac37fe9936cd074678cb446062ae9ce841187119f17"},"schema_version":"1.0"},"canonical_sha256":"e61339c04d91596e35f5f4cda451e0bd16ce52f5313e2bb338687e7e02ebacd0","source":{"kind":"arxiv","id":"2310.06522","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.06522","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"arxiv_version","alias_value":"2310.06522v2","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.06522","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_12","alias_value":"4YJTTQCNSFMW","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_16","alias_value":"4YJTTQCNSFMW4NPV","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_8","alias_value":"4YJTTQCN","created_at":"2026-07-05T09:07:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:4YJTTQCNSFMW4NPV6TG2IUPAXU","target":"record","payload":{"canonical_record":{"source":{"id":"2310.06522","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-10T11:08:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"c4d84959c72c975b9aff6452b6b3043730a6678a42cb1f550e3d959879927593","abstract_canon_sha256":"ed439f50209c2b0d78b2bac37fe9936cd074678cb446062ae9ce841187119f17"},"schema_version":"1.0"},"canonical_sha256":"e61339c04d91596e35f5f4cda451e0bd16ce52f5313e2bb338687e7e02ebacd0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:07:44.047881Z","signature_b64":"P18cSjLZ+mYLb+h7/q+bBsG0wYGgq8OExotzND3ptF1u44FKY8ctbDPRWx0pyRQkRTSUFrAtqPRiO4HMEn4aDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e61339c04d91596e35f5f4cda451e0bd16ce52f5313e2bb338687e7e02ebacd0","last_reissued_at":"2026-07-05T09:07:44.047436Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:07:44.047436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.06522","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":"2026-07-05T09:07:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cA5mogWBA+eIAcMmqjpsw3ahs5UALGoDpzIgL3tDTU6uQ8EcVfunsaq21tKibKjwqJ0ZybSdfddQailww0f9DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:41:48.662698Z"},"content_sha256":"3df0529d4cbcbc82f3b8377e123116b528f46b552130c36992cef0d94ad821b6","schema_version":"1.0","event_id":"sha256:3df0529d4cbcbc82f3b8377e123116b528f46b552130c36992cef0d94ad821b6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:4YJTTQCNSFMW4NPV6TG2IUPAXU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Watt For What: Rethinking Deep Learning's Energy-Performance Relationship","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Gen Li, Laura Sevilla-Lara, Shashank Narayana Gowda, Shreyank N Gowda, Xiaobo Jin, Xinyue Hao","submitted_at":"2023-10-10T11:08:31Z","abstract_excerpt":"Deep learning models have revolutionized various fields, from image recognition to natural language processing, by achieving unprecedented levels of accuracy. However, their increasing energy consumption has raised concerns about their environmental impact, disadvantaging smaller entities in research and exacerbating global energy consumption. In this paper, we explore the trade-off between model accuracy and electricity consumption, proposing a metric that penalizes large consumption of electricity. We conduct a comprehensive study on the electricity consumption of various deep learning model"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.06522","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/2310.06522/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":"2026-07-05T09:07:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sr4XrvKkHdNX0BYKw9Q5/RDHKE2xZoEIlEPTbBQ84rQgILHcH2VBLd1WhSlcGj4XjEFZQNLxyJfIuBXcMH8fAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:41:48.663239Z"},"content_sha256":"63d5062a5dedf68cd4a47a18e8a822277b6203914da12e5bf118a558d45c7d88","schema_version":"1.0","event_id":"sha256:63d5062a5dedf68cd4a47a18e8a822277b6203914da12e5bf118a558d45c7d88"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/bundle.json","state_url":"https://pith.science/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/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":"2026-08-10T02:41:48Z","links":{"resolver":"https://pith.science/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU","bundle":"https://pith.science/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/bundle.json","state":"https://pith.science/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4YJTTQCNSFMW4NPV6TG2IUPAXU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4YJTTQCNSFMW4NPV6TG2IUPAXU","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":"ed439f50209c2b0d78b2bac37fe9936cd074678cb446062ae9ce841187119f17","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-10T11:08:31Z","title_canon_sha256":"c4d84959c72c975b9aff6452b6b3043730a6678a42cb1f550e3d959879927593"},"schema_version":"1.0","source":{"id":"2310.06522","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.06522","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"arxiv_version","alias_value":"2310.06522v2","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.06522","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_12","alias_value":"4YJTTQCNSFMW","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_16","alias_value":"4YJTTQCNSFMW4NPV","created_at":"2026-07-05T09:07:44Z"},{"alias_kind":"pith_short_8","alias_value":"4YJTTQCN","created_at":"2026-07-05T09:07:44Z"}],"graph_snapshots":[{"event_id":"sha256:63d5062a5dedf68cd4a47a18e8a822277b6203914da12e5bf118a558d45c7d88","target":"graph","created_at":"2026-07-05T09:07:44Z","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/2310.06522/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning models have revolutionized various fields, from image recognition to natural language processing, by achieving unprecedented levels of accuracy. However, their increasing energy consumption has raised concerns about their environmental impact, disadvantaging smaller entities in research and exacerbating global energy consumption. In this paper, we explore the trade-off between model accuracy and electricity consumption, proposing a metric that penalizes large consumption of electricity. We conduct a comprehensive study on the electricity consumption of various deep learning model","authors_text":"Gen Li, Laura Sevilla-Lara, Shashank Narayana Gowda, Shreyank N Gowda, Xiaobo Jin, Xinyue Hao","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-10T11:08:31Z","title":"Watt For What: Rethinking Deep Learning's Energy-Performance Relationship"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.06522","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":"sha256:3df0529d4cbcbc82f3b8377e123116b528f46b552130c36992cef0d94ad821b6","target":"record","created_at":"2026-07-05T09:07:44Z","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":"ed439f50209c2b0d78b2bac37fe9936cd074678cb446062ae9ce841187119f17","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-10T11:08:31Z","title_canon_sha256":"c4d84959c72c975b9aff6452b6b3043730a6678a42cb1f550e3d959879927593"},"schema_version":"1.0","source":{"id":"2310.06522","kind":"arxiv","version":2}},"canonical_sha256":"e61339c04d91596e35f5f4cda451e0bd16ce52f5313e2bb338687e7e02ebacd0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e61339c04d91596e35f5f4cda451e0bd16ce52f5313e2bb338687e7e02ebacd0","first_computed_at":"2026-07-05T09:07:44.047436Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:07:44.047436Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P18cSjLZ+mYLb+h7/q+bBsG0wYGgq8OExotzND3ptF1u44FKY8ctbDPRWx0pyRQkRTSUFrAtqPRiO4HMEn4aDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:07:44.047881Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.06522","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3df0529d4cbcbc82f3b8377e123116b528f46b552130c36992cef0d94ad821b6","sha256:63d5062a5dedf68cd4a47a18e8a822277b6203914da12e5bf118a558d45c7d88"],"state_sha256":"eeab48df47db7f050a6c5427f24f0048d6f359065ea3107750907debff0b4811"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kzU4dbeusxUD5km+MXJirLTPVsWshSzyMmN7BIzXGTs8Kiu3HK1VziCM1sNbp4urxXtHzvaA4Op7sUvNgsGNCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T02:41:48.668465Z","bundle_sha256":"a47617ad639db570a8c518b24b2c3430da414b6e516ae61d868388a0af58e90a"}}