{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LMMMN2XBF54QGIC5QLCREEB5HU","short_pith_number":"pith:LMMMN2XB","canonical_record":{"source":{"id":"2506.13838","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-16T12:53:02Z","cross_cats_sorted":["cs.AI","cs.SE"],"title_canon_sha256":"f6989d2c297596bf460e903a2d146317ef307437f5fc6f1e79e0bb74b3277e2c","abstract_canon_sha256":"e0748645e68c807f32e79674e4c4d67ed6fbe4b1d0b711dbd315fa140f573523"},"schema_version":"1.0"},"canonical_sha256":"5b18c6eae12f7903205d82c512103d3d250d172843cf7fdd07e289af69a87058","source":{"kind":"arxiv","id":"2506.13838","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.13838","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"arxiv_version","alias_value":"2506.13838v1","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.13838","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_12","alias_value":"LMMMN2XBF54Q","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_16","alias_value":"LMMMN2XBF54QGIC5","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_8","alias_value":"LMMMN2XB","created_at":"2026-07-05T11:22:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LMMMN2XBF54QGIC5QLCREEB5HU","target":"record","payload":{"canonical_record":{"source":{"id":"2506.13838","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-16T12:53:02Z","cross_cats_sorted":["cs.AI","cs.SE"],"title_canon_sha256":"f6989d2c297596bf460e903a2d146317ef307437f5fc6f1e79e0bb74b3277e2c","abstract_canon_sha256":"e0748645e68c807f32e79674e4c4d67ed6fbe4b1d0b711dbd315fa140f573523"},"schema_version":"1.0"},"canonical_sha256":"5b18c6eae12f7903205d82c512103d3d250d172843cf7fdd07e289af69a87058","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:44.659956Z","signature_b64":"PNfez5dOB6YXaakcTUO6nxm8oh7Iq6CPOhbGdNbIYvi87pRyXUSBFXXEwxm16zTjtCaxAf4U9nHHR+hdZl5fAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b18c6eae12f7903205d82c512103d3d250d172843cf7fdd07e289af69a87058","last_reissued_at":"2026-07-05T11:22:44.659449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:44.659449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.13838","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:22:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I5Uxyf1+STBwuknw0ZR0xXWJtT9YKEVJgqvu42K5UsY32g9gf1VGqD0KRzTOO2+ZTfq+CMPC0O1O8gL3cGnCCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:16:13.392547Z"},"content_sha256":"a2ee7c9cc6b5c151679cb506464eb0bc1e6b9edce7d1bad15fad24edfa29df04","schema_version":"1.0","event_id":"sha256:a2ee7c9cc6b5c151679cb506464eb0bc1e6b9edce7d1bad15fad24edfa29df04"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LMMMN2XBF54QGIC5QLCREEB5HU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SE"],"primary_cat":"cs.LG","authors_text":"Arie van Deursen, Jan Rellermeyer, June Sallou, Lorena Poenaru-Olaru, Luis Cruz","submitted_at":"2025-06-16T12:53:02Z","abstract_excerpt":"The reliability of machine learning (ML) software systems is heavily influenced by changes in data over time. For that reason, ML systems require regular maintenance, typically based on model retraining. However, retraining requires significant computational demand, which makes it energy-intensive and raises concerns about its environmental impact. To understand which retraining techniques should be considered when designing sustainable ML applications, in this work, we study the energy consumption of common retraining techniques. Since the accuracy of ML systems is also essential, we compare "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.13838","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/2506.13838/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":"2026-07-05T11:22:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GT/Kx9RKFaDQ9j7Nwj4MxXxCf4N/ZHJxq41BhxIys/HMpyjPV2jdvGy0WYYY9c2X9CWzJCAuEjXt5em8iugBAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T06:16:13.392919Z"},"content_sha256":"23769ac6e7bcc8fe3bd7b7f9e96ca3c5fa51246bc80159ef1007e90dfd65f386","schema_version":"1.0","event_id":"sha256:23769ac6e7bcc8fe3bd7b7f9e96ca3c5fa51246bc80159ef1007e90dfd65f386"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LMMMN2XBF54QGIC5QLCREEB5HU/bundle.json","state_url":"https://pith.science/pith/LMMMN2XBF54QGIC5QLCREEB5HU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LMMMN2XBF54QGIC5QLCREEB5HU/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":"2026-07-07T06:16:13Z","links":{"resolver":"https://pith.science/pith/LMMMN2XBF54QGIC5QLCREEB5HU","bundle":"https://pith.science/pith/LMMMN2XBF54QGIC5QLCREEB5HU/bundle.json","state":"https://pith.science/pith/LMMMN2XBF54QGIC5QLCREEB5HU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LMMMN2XBF54QGIC5QLCREEB5HU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LMMMN2XBF54QGIC5QLCREEB5HU","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":"e0748645e68c807f32e79674e4c4d67ed6fbe4b1d0b711dbd315fa140f573523","cross_cats_sorted":["cs.AI","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-16T12:53:02Z","title_canon_sha256":"f6989d2c297596bf460e903a2d146317ef307437f5fc6f1e79e0bb74b3277e2c"},"schema_version":"1.0","source":{"id":"2506.13838","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.13838","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"arxiv_version","alias_value":"2506.13838v1","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.13838","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_12","alias_value":"LMMMN2XBF54Q","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_16","alias_value":"LMMMN2XBF54QGIC5","created_at":"2026-07-05T11:22:44Z"},{"alias_kind":"pith_short_8","alias_value":"LMMMN2XB","created_at":"2026-07-05T11:22:44Z"}],"graph_snapshots":[{"event_id":"sha256:23769ac6e7bcc8fe3bd7b7f9e96ca3c5fa51246bc80159ef1007e90dfd65f386","target":"graph","created_at":"2026-07-05T11:22:44Z","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/2506.13838/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The reliability of machine learning (ML) software systems is heavily influenced by changes in data over time. For that reason, ML systems require regular maintenance, typically based on model retraining. However, retraining requires significant computational demand, which makes it energy-intensive and raises concerns about its environmental impact. To understand which retraining techniques should be considered when designing sustainable ML applications, in this work, we study the energy consumption of common retraining techniques. Since the accuracy of ML systems is also essential, we compare ","authors_text":"Arie van Deursen, Jan Rellermeyer, June Sallou, Lorena Poenaru-Olaru, Luis Cruz","cross_cats":["cs.AI","cs.SE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-16T12:53:02Z","title":"Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.13838","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:a2ee7c9cc6b5c151679cb506464eb0bc1e6b9edce7d1bad15fad24edfa29df04","target":"record","created_at":"2026-07-05T11:22:44Z","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":"e0748645e68c807f32e79674e4c4d67ed6fbe4b1d0b711dbd315fa140f573523","cross_cats_sorted":["cs.AI","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-16T12:53:02Z","title_canon_sha256":"f6989d2c297596bf460e903a2d146317ef307437f5fc6f1e79e0bb74b3277e2c"},"schema_version":"1.0","source":{"id":"2506.13838","kind":"arxiv","version":1}},"canonical_sha256":"5b18c6eae12f7903205d82c512103d3d250d172843cf7fdd07e289af69a87058","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b18c6eae12f7903205d82c512103d3d250d172843cf7fdd07e289af69a87058","first_computed_at":"2026-07-05T11:22:44.659449Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:44.659449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PNfez5dOB6YXaakcTUO6nxm8oh7Iq6CPOhbGdNbIYvi87pRyXUSBFXXEwxm16zTjtCaxAf4U9nHHR+hdZl5fAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:44.659956Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.13838","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2ee7c9cc6b5c151679cb506464eb0bc1e6b9edce7d1bad15fad24edfa29df04","sha256:23769ac6e7bcc8fe3bd7b7f9e96ca3c5fa51246bc80159ef1007e90dfd65f386"],"state_sha256":"d280c265eee3feb374dc83746ead29b51e970457b36c8b2c27c269c15303d979"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oGdm38sgw1rKOrV+MFfXt1i2kbBio5vbL8JIKYxfuJD8/b2hJyKnW89FW93kqT23UllUqUslz1/3WHAxCD6DBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T06:16:13.395182Z","bundle_sha256":"4863a88922b46c93c78ae2e7f8d7f7f9dd14ba5509690bc7fac4f89f9a263c82"}}