{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:RH55XTCJKNSFOR7KYS5NCABFJ3","short_pith_number":"pith:RH55XTCJ","canonical_record":{"source":{"id":"1810.03264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-08T03:57:39Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"49b6ffd86c1a3c010e2e1d8575b76925a5dc77ebfaae75f197d43efc246bf375","abstract_canon_sha256":"28753e3877df49a7c93f15b1fda1af2a86652c05c01c544808adce1e121f1ad7"},"schema_version":"1.0"},"canonical_sha256":"89fbdbcc4953645747eac4bad100254efea3f75e19c83dc15e1cf2fdc8644353","source":{"kind":"arxiv","id":"1810.03264","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.03264","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"1810.03264v1","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.03264","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"RH55XTCJKNSF","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RH55XTCJKNSFOR7K","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RH55XTCJ","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:RH55XTCJKNSFOR7KYS5NCABFJ3","target":"record","payload":{"canonical_record":{"source":{"id":"1810.03264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-08T03:57:39Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"49b6ffd86c1a3c010e2e1d8575b76925a5dc77ebfaae75f197d43efc246bf375","abstract_canon_sha256":"28753e3877df49a7c93f15b1fda1af2a86652c05c01c544808adce1e121f1ad7"},"schema_version":"1.0"},"canonical_sha256":"89fbdbcc4953645747eac4bad100254efea3f75e19c83dc15e1cf2fdc8644353","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:53.973431Z","signature_b64":"bUaYVWcjN8cqVGGhsQeWQE7pebzGHFZwNXPH51tcMmLa/BnDNXBh4lL0POYA4ZGbTbBorUYEWtLf+2iGqdYeBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"89fbdbcc4953645747eac4bad100254efea3f75e19c83dc15e1cf2fdc8644353","last_reissued_at":"2026-05-18T00:03:53.972845Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:53.972845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.03264","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":"2026-05-18T00:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V8X7l75Znx6zUsvxaLBWV/EmAQouoqRQnIie5ZyEbDwnigpN2KMUAGs8cFhJXO496QHVTnKdO+txAB5QlDrUAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:54:40.597293Z"},"content_sha256":"c2df3e261ba04faf02ef3a564ad8143f5c5ac0d173c5ee56010e91b967687ded","schema_version":"1.0","event_id":"sha256:c2df3e261ba04faf02ef3a564ad8143f5c5ac0d173c5ee56010e91b967687ded"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:RH55XTCJKNSFOR7KYS5NCABFJ3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Toward Understanding the Impact of Staleness in Distributed Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Eric P. Xing, Hao Zhang, Nanqing Dong, Wei Dai, Yi Zhou","submitted_at":"2018-10-08T03:57:39Z","abstract_excerpt":"Many distributed machine learning (ML) systems adopt the non-synchronous execution in order to alleviate the network communication bottleneck, resulting in stale parameters that do not reflect the latest updates. Despite much development in large-scale ML, the effects of staleness on learning are inconclusive as it is challenging to directly monitor or control staleness in complex distributed environments. In this work, we study the convergence behaviors of a wide array of ML models and algorithms under delayed updates. Our extensive experiments reveal the rich diversity of the effects of stal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.03264","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":""},"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":"2026-05-18T00:03:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6SF4g+euZVeOliKj3dcpyPMM0dBNSAz30BAQoTYnsitA2ohv8AEuoYEjWlFoPw4onUgXx0nOiDOnO+8aRtA3CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T18:54:40.597909Z"},"content_sha256":"cdd4011ceef5eaee90934d8a424237fe6a28979abfc30a4b62b1083d69e351ea","schema_version":"1.0","event_id":"sha256:cdd4011ceef5eaee90934d8a424237fe6a28979abfc30a4b62b1083d69e351ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/bundle.json","state_url":"https://pith.science/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/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":"2026-05-26T18:54:40Z","links":{"resolver":"https://pith.science/pith/RH55XTCJKNSFOR7KYS5NCABFJ3","bundle":"https://pith.science/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/bundle.json","state":"https://pith.science/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RH55XTCJKNSFOR7KYS5NCABFJ3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:RH55XTCJKNSFOR7KYS5NCABFJ3","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":"28753e3877df49a7c93f15b1fda1af2a86652c05c01c544808adce1e121f1ad7","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-08T03:57:39Z","title_canon_sha256":"49b6ffd86c1a3c010e2e1d8575b76925a5dc77ebfaae75f197d43efc246bf375"},"schema_version":"1.0","source":{"id":"1810.03264","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.03264","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"arxiv_version","alias_value":"1810.03264v1","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.03264","created_at":"2026-05-18T00:03:53Z"},{"alias_kind":"pith_short_12","alias_value":"RH55XTCJKNSF","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RH55XTCJKNSFOR7K","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RH55XTCJ","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:cdd4011ceef5eaee90934d8a424237fe6a28979abfc30a4b62b1083d69e351ea","target":"graph","created_at":"2026-05-18T00:03:53Z","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"},"paper":{"abstract_excerpt":"Many distributed machine learning (ML) systems adopt the non-synchronous execution in order to alleviate the network communication bottleneck, resulting in stale parameters that do not reflect the latest updates. Despite much development in large-scale ML, the effects of staleness on learning are inconclusive as it is challenging to directly monitor or control staleness in complex distributed environments. In this work, we study the convergence behaviors of a wide array of ML models and algorithms under delayed updates. Our extensive experiments reveal the rich diversity of the effects of stal","authors_text":"Eric P. Xing, Hao Zhang, Nanqing Dong, Wei Dai, Yi Zhou","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-08T03:57:39Z","title":"Toward Understanding the Impact of Staleness in Distributed Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.03264","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:c2df3e261ba04faf02ef3a564ad8143f5c5ac0d173c5ee56010e91b967687ded","target":"record","created_at":"2026-05-18T00:03:53Z","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":"28753e3877df49a7c93f15b1fda1af2a86652c05c01c544808adce1e121f1ad7","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-10-08T03:57:39Z","title_canon_sha256":"49b6ffd86c1a3c010e2e1d8575b76925a5dc77ebfaae75f197d43efc246bf375"},"schema_version":"1.0","source":{"id":"1810.03264","kind":"arxiv","version":1}},"canonical_sha256":"89fbdbcc4953645747eac4bad100254efea3f75e19c83dc15e1cf2fdc8644353","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"89fbdbcc4953645747eac4bad100254efea3f75e19c83dc15e1cf2fdc8644353","first_computed_at":"2026-05-18T00:03:53.972845Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:53.972845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bUaYVWcjN8cqVGGhsQeWQE7pebzGHFZwNXPH51tcMmLa/BnDNXBh4lL0POYA4ZGbTbBorUYEWtLf+2iGqdYeBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:53.973431Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.03264","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2df3e261ba04faf02ef3a564ad8143f5c5ac0d173c5ee56010e91b967687ded","sha256:cdd4011ceef5eaee90934d8a424237fe6a28979abfc30a4b62b1083d69e351ea"],"state_sha256":"755e4bb956860c22bd299a42859b6ab2501236ca7df2563a4254a468a41652a3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xACNkVbc7TVlCQpWrLFmTsb1sYeu3nHsXydlS9ZGdoCMait14LLyqmqFGPe94eZJymRkREVJPCgkaWt/gNN7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T18:54:40.601262Z","bundle_sha256":"2a9570cc38af2e80f3f649916793ebbf7cd265a3211898019f60df5b6232c37e"}}