{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LLBKMI6JACZLJ3H4QGC4XPFXCY","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":"2ba540115e840014b2d46320f32f89622befa53ffd7861530cbc9722f923c12f","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-22T12:59:15Z","title_canon_sha256":"09c7b4146b0a238b4af7ce661ba15e829f81d2c4d9af73da5e50d2b3585b5006"},"schema_version":"1.0","source":{"id":"2506.18020","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.18020","created_at":"2026-07-07T01:15:55Z"},{"alias_kind":"arxiv_version","alias_value":"2506.18020v3","created_at":"2026-07-07T01:15:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.18020","created_at":"2026-07-07T01:15:55Z"},{"alias_kind":"pith_short_12","alias_value":"LLBKMI6JACZL","created_at":"2026-07-07T01:15:55Z"},{"alias_kind":"pith_short_16","alias_value":"LLBKMI6JACZLJ3H4","created_at":"2026-07-07T01:15:55Z"},{"alias_kind":"pith_short_8","alias_value":"LLBKMI6J","created_at":"2026-07-07T01:15:55Z"}],"graph_snapshots":[{"event_id":"sha256:0e8044ff11c07c6a42fd922eb0cf6d4ccf90b4225080b1dc4379a72b7a12ecef","target":"graph","created_at":"2026-07-07T01:15:55Z","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/2506.18020/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robust distributed learning algorithms aim to maintain reliable performance despite the presence of misbehaving workers. Such misbehaviors are commonly modeled as \\textit{Byzantine failures}, allowing arbitrarily corrupted communication, or as \\textit{data poisoning}, a weaker form of corruption restricted to local training data. While prior work shows similar optimization guarantees for both models, an important question remains: \\textit{How do these threat models impact generalization?} We show, for the first time, a fundamental gap in generalization guarantees between the two threat models:","authors_text":"Aur\\'elien Bellet, Batiste Le Bars, Nirupam Gupta, Thomas Boudou","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-22T12:59:15Z","title":"Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.18020","kind":"arxiv","version":3},"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:c05cbb6babbd0f87f670e6101f93acab07894e4c8c8cb2633b84a2fb9980bc32","target":"record","created_at":"2026-07-07T01:15:55Z","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":"2ba540115e840014b2d46320f32f89622befa53ffd7861530cbc9722f923c12f","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-22T12:59:15Z","title_canon_sha256":"09c7b4146b0a238b4af7ce661ba15e829f81d2c4d9af73da5e50d2b3585b5006"},"schema_version":"1.0","source":{"id":"2506.18020","kind":"arxiv","version":3}},"canonical_sha256":"5ac2a623c900b2b4ecfc8185cbbcb7160c9eabdaf1a9096169e229527bfe6fbe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ac2a623c900b2b4ecfc8185cbbcb7160c9eabdaf1a9096169e229527bfe6fbe","first_computed_at":"2026-07-07T01:15:55.376423Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T01:15:55.376423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PnZ2665HCoaIVxYnYHlsxLhqpShtp6IvhOM2B5jKP3fEfA+bTVrvX+tEwgtofimYTuLqs5qJGdEUs/QWVTZ7Bw==","signature_status":"signed_v1","signed_at":"2026-07-07T01:15:55.377207Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.18020","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c05cbb6babbd0f87f670e6101f93acab07894e4c8c8cb2633b84a2fb9980bc32","sha256:0e8044ff11c07c6a42fd922eb0cf6d4ccf90b4225080b1dc4379a72b7a12ecef"],"state_sha256":"148bb8da9a9b031ec0ce5bd78050929989dad6aa9bf7c872d81f72f38d8f7efc"}