{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:M2MHJIQRGDSQF7B4ZU7VD6FBNY","short_pith_number":"pith:M2MHJIQR","canonical_record":{"source":{"id":"2503.07545","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T17:12:47Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"a1a76e73e9b563cb77fcc995316cc10931c48b91ee5ae05b2cf9b341166f8f54","abstract_canon_sha256":"4baba983b4ad58d7bc1671cfe384a7a1e3b78128f4cf023ea4cca11fd338b707"},"schema_version":"1.0"},"canonical_sha256":"669874a21130e502fc3ccd3f51f8a16e1b0ccc3fe7926dc9028ebd3cf28297bc","source":{"kind":"arxiv","id":"2503.07545","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.07545","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"arxiv_version","alias_value":"2503.07545v1","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.07545","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_12","alias_value":"M2MHJIQRGDSQ","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"M2MHJIQRGDSQF7B4","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"M2MHJIQR","created_at":"2026-07-05T10:28:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:M2MHJIQRGDSQF7B4ZU7VD6FBNY","target":"record","payload":{"canonical_record":{"source":{"id":"2503.07545","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T17:12:47Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"a1a76e73e9b563cb77fcc995316cc10931c48b91ee5ae05b2cf9b341166f8f54","abstract_canon_sha256":"4baba983b4ad58d7bc1671cfe384a7a1e3b78128f4cf023ea4cca11fd338b707"},"schema_version":"1.0"},"canonical_sha256":"669874a21130e502fc3ccd3f51f8a16e1b0ccc3fe7926dc9028ebd3cf28297bc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:28:06.767817Z","signature_b64":"obxa14soRPguiRJu1ZX07g4TbCQrPKCARM9HdJADW2F5kxyCQQIjW1PJU7qFTqa9nuaPjxFuQZOWMM/yXTWvBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"669874a21130e502fc3ccd3f51f8a16e1b0ccc3fe7926dc9028ebd3cf28297bc","last_reissued_at":"2026-07-05T10:28:06.766734Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:28:06.766734Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.07545","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":"2026-07-05T10:28:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"naPmTu0rE3AXYUvPsie7qcftgsJ1tGWE+bWx88vHddzfKsJov9OVEAK0nzLwic76oT8whCTd0FjB5bj9InqEBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T19:08:51.362662Z"},"content_sha256":"a2dba94528d1723f2ded869c47c937aed2fbe6f1fa438eac3a62a47b0b32ac04","schema_version":"1.0","event_id":"sha256:a2dba94528d1723f2ded869c47c937aed2fbe6f1fa438eac3a62a47b0b32ac04"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:M2MHJIQRGDSQF7B4ZU7VD6FBNY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Queueing, Predictions, and LLMs: Challenges and Open Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.AI","authors_text":"Michael Mitzenmacher, Rana Shahout","submitted_at":"2025-03-10T17:12:47Z","abstract_excerpt":"Queueing systems present many opportunities for applying machine-learning predictions, such as estimated service times, to improve system performance. This integration raises numerous open questions about how predictions can be effectively leveraged to improve scheduling decisions. Recent studies explore queues with predicted service times, typically aiming to minimize job time in the system. We review these works, highlight the effectiveness of predictions, and present open questions on queue performance. We then move to consider an important practical example of using predictions in scheduli"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.07545","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/2503.07545/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":"2026-07-05T10:28:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pkSbMRI9RvUrb2/712zrFoQqKqvdoTwe6pT3rgb/pIiVumZxZ6LwfxeRkPp1zCROlfWMqVKTtVeqKHvnSQ4rCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T19:08:51.363159Z"},"content_sha256":"526733429a9e5f6dd14547aed9709f15974936724424c192ab431b7b23f229d7","schema_version":"1.0","event_id":"sha256:526733429a9e5f6dd14547aed9709f15974936724424c192ab431b7b23f229d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/bundle.json","state_url":"https://pith.science/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/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":"2026-08-04T19:08:51Z","links":{"resolver":"https://pith.science/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY","bundle":"https://pith.science/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/bundle.json","state":"https://pith.science/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M2MHJIQRGDSQF7B4ZU7VD6FBNY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:M2MHJIQRGDSQF7B4ZU7VD6FBNY","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":"4baba983b4ad58d7bc1671cfe384a7a1e3b78128f4cf023ea4cca11fd338b707","cross_cats_sorted":["cs.DS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T17:12:47Z","title_canon_sha256":"a1a76e73e9b563cb77fcc995316cc10931c48b91ee5ae05b2cf9b341166f8f54"},"schema_version":"1.0","source":{"id":"2503.07545","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.07545","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"arxiv_version","alias_value":"2503.07545v1","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.07545","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_12","alias_value":"M2MHJIQRGDSQ","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_16","alias_value":"M2MHJIQRGDSQF7B4","created_at":"2026-07-05T10:28:06Z"},{"alias_kind":"pith_short_8","alias_value":"M2MHJIQR","created_at":"2026-07-05T10:28:06Z"}],"graph_snapshots":[{"event_id":"sha256:526733429a9e5f6dd14547aed9709f15974936724424c192ab431b7b23f229d7","target":"graph","created_at":"2026-07-05T10:28:06Z","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/2503.07545/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Queueing systems present many opportunities for applying machine-learning predictions, such as estimated service times, to improve system performance. This integration raises numerous open questions about how predictions can be effectively leveraged to improve scheduling decisions. Recent studies explore queues with predicted service times, typically aiming to minimize job time in the system. We review these works, highlight the effectiveness of predictions, and present open questions on queue performance. We then move to consider an important practical example of using predictions in scheduli","authors_text":"Michael Mitzenmacher, Rana Shahout","cross_cats":["cs.DS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T17:12:47Z","title":"Queueing, Predictions, and LLMs: Challenges and Open Problems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.07545","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:a2dba94528d1723f2ded869c47c937aed2fbe6f1fa438eac3a62a47b0b32ac04","target":"record","created_at":"2026-07-05T10:28:06Z","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":"4baba983b4ad58d7bc1671cfe384a7a1e3b78128f4cf023ea4cca11fd338b707","cross_cats_sorted":["cs.DS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T17:12:47Z","title_canon_sha256":"a1a76e73e9b563cb77fcc995316cc10931c48b91ee5ae05b2cf9b341166f8f54"},"schema_version":"1.0","source":{"id":"2503.07545","kind":"arxiv","version":1}},"canonical_sha256":"669874a21130e502fc3ccd3f51f8a16e1b0ccc3fe7926dc9028ebd3cf28297bc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"669874a21130e502fc3ccd3f51f8a16e1b0ccc3fe7926dc9028ebd3cf28297bc","first_computed_at":"2026-07-05T10:28:06.766734Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:28:06.766734Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"obxa14soRPguiRJu1ZX07g4TbCQrPKCARM9HdJADW2F5kxyCQQIjW1PJU7qFTqa9nuaPjxFuQZOWMM/yXTWvBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:28:06.767817Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.07545","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2dba94528d1723f2ded869c47c937aed2fbe6f1fa438eac3a62a47b0b32ac04","sha256:526733429a9e5f6dd14547aed9709f15974936724424c192ab431b7b23f229d7"],"state_sha256":"b1896879c75a15e06894fe430788a800600a9c7f071ed7ed9128540290d2bdd6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dJJvkQm5NGuwW5HUOgDduVGYHdxJP+gHAiNzh3boZXRLWB352AkN9xK2Do2NoK3Eb6bHu80bWHXS6ydfGh2DCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T19:08:51.366654Z","bundle_sha256":"b7e8702b6336c7d87dc1d363cff4bad6e7b6b6dd1303175f44b2da5033b4439c"}}