{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IRTCY7OPG52YCSDFTKMLZGWSKT","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":"7e9070e4e6109afc5d0b417d0957b109de2bcea8ef4c09bd6c3700fa392ccab1","cross_cats_sorted":["cs.AI","cs.CV","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T08:55:23Z","title_canon_sha256":"5bf90227213f1324264565f06da2a99bb9c1ed3e4369117b0dae900a1ecdab1b"},"schema_version":"1.0","source":{"id":"2307.11434","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.11434","created_at":"2026-07-05T06:33:27Z"},{"alias_kind":"arxiv_version","alias_value":"2307.11434v1","created_at":"2026-07-05T06:33:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.11434","created_at":"2026-07-05T06:33:27Z"},{"alias_kind":"pith_short_12","alias_value":"IRTCY7OPG52Y","created_at":"2026-07-05T06:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"IRTCY7OPG52YCSDF","created_at":"2026-07-05T06:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"IRTCY7OP","created_at":"2026-07-05T06:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:2dd0cad7b71e0f308f1f23415ce09d698caeac07fdf5ce5f07197376f948d405","target":"graph","created_at":"2026-07-05T06:33:27Z","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/2307.11434/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The batch size is an essential parameter to tune during the development of new neural networks. Amongst other quality indicators, it has a large degree of influence on the model's accuracy, generalisability, training times and parallelisability. This fact is generally known and commonly studied. However, during the application phase of a deep learning model, when the model is utilised by an end-user for inference, we find that there is a disregard for the potential benefits of introducing a batch size. In this study, we examine the effect of input batching on the energy consumption and respons","authors_text":"Arie van Deursen, Daniel Feitosa, June Sallou, Lu\\'is Cruz, Tim Yarally","cross_cats":["cs.AI","cs.CV","cs.SE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T08:55:23Z","title":"Batching for Green AI -- An Exploratory Study on Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.11434","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:e9bfe16d50a9a56d7fd1b8eff5f4cf7c3196195d79accf0be7f2590bbc045ba6","target":"record","created_at":"2026-07-05T06:33:27Z","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":"7e9070e4e6109afc5d0b417d0957b109de2bcea8ef4c09bd6c3700fa392ccab1","cross_cats_sorted":["cs.AI","cs.CV","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T08:55:23Z","title_canon_sha256":"5bf90227213f1324264565f06da2a99bb9c1ed3e4369117b0dae900a1ecdab1b"},"schema_version":"1.0","source":{"id":"2307.11434","kind":"arxiv","version":1}},"canonical_sha256":"44662c7dcf37758148659a98bc9ad254ff55a3c7cff210e5dcd716e3f85f747c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"44662c7dcf37758148659a98bc9ad254ff55a3c7cff210e5dcd716e3f85f747c","first_computed_at":"2026-07-05T06:33:27.437826Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:33:27.437826Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kBgr5hsX0wSE2DOSUSwY2kQe8EuWo0XkibFzTMq3T9HzkH5qphBoBhhDznqPGIIosihdgDdTi9PJwGjTkgChCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:33:27.438275Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.11434","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9bfe16d50a9a56d7fd1b8eff5f4cf7c3196195d79accf0be7f2590bbc045ba6","sha256:2dd0cad7b71e0f308f1f23415ce09d698caeac07fdf5ce5f07197376f948d405"],"state_sha256":"cfee0d05c70c6d2bbb8f6f29c06d17c716c1eb77ef4b873e6064765418068876"}