{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TWMD6CKTOH2CHVOE47C3SATDMM","short_pith_number":"pith:TWMD6CKT","canonical_record":{"source":{"id":"2406.07536","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-11T17:57:49Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"4c17bf82a264d4ef7d761f4248e884c204e34ed3c56e178b689a9debbda32f97","abstract_canon_sha256":"608e3cb5baeea4859b06f48ca2be0e0752bbf5e176f9156b4fc0d8c6fb4c5d89"},"schema_version":"1.0"},"canonical_sha256":"9d983f095371f423d5c4e7c5b90263631aaa3c75fdb025029832e800b592eaf4","source":{"kind":"arxiv","id":"2406.07536","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07536","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07536v1","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07536","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_12","alias_value":"TWMD6CKTOH2C","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_16","alias_value":"TWMD6CKTOH2CHVOE","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_8","alias_value":"TWMD6CKT","created_at":"2026-07-05T08:30:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TWMD6CKTOH2CHVOE47C3SATDMM","target":"record","payload":{"canonical_record":{"source":{"id":"2406.07536","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-11T17:57:49Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"4c17bf82a264d4ef7d761f4248e884c204e34ed3c56e178b689a9debbda32f97","abstract_canon_sha256":"608e3cb5baeea4859b06f48ca2be0e0752bbf5e176f9156b4fc0d8c6fb4c5d89"},"schema_version":"1.0"},"canonical_sha256":"9d983f095371f423d5c4e7c5b90263631aaa3c75fdb025029832e800b592eaf4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:30:26.720736Z","signature_b64":"+Md9Q8oiKy5gMYG0RCjGz9elflqV0XlI2xsP6HPWas3xjhHPkOyQVvM0MGrZA92xq9sBNNDL2HtSznGR97QTCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d983f095371f423d5c4e7c5b90263631aaa3c75fdb025029832e800b592eaf4","last_reissued_at":"2026-07-05T08:30:26.720194Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:30:26.720194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.07536","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":"2026-07-05T08:30:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W2yUAGXpPUJO/vNqzbYTKh1+zUo3iHEn85t1432Dm6jy0sQ3gfuZH/fDuAdwxUtI+IH0hJ7Z1UCnbonbCEKWCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T10:15:36.870736Z"},"content_sha256":"90d10ce569ea3a1780a37cc190c9922bf8250f68578cd8f6a1efac1f9f110918","schema_version":"1.0","event_id":"sha256:90d10ce569ea3a1780a37cc190c9922bf8250f68578cd8f6a1efac1f9f110918"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TWMD6CKTOH2CHVOE47C3SATDMM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Lingjuan Lyu, Weiming Zhuang, Wenxiao Wang","submitted_at":"2024-06-11T17:57:49Z","abstract_excerpt":"The advancement of deep learning technologies is bringing new models every day, motivating the study of scalable model selection. An ideal model selection scheme should minimally support two operations efficiently over a large pool of candidate models: update, which involves either adding a new candidate model or removing an existing candidate model, and selection, which involves locating highly performing models for a given task. However, previous solutions to model selection require high computational complexity for at least one of these two operations. In this work, we target fundamentally "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07536","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/2406.07536/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":"2026-07-05T08:30:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y61xNB7cRpPZvwy7u2LB0tUnaxbc/DXRXK8YXrKb4wcOkTNq8/szhIeJFv+5KOgR/9nECAuliah6Jb1OU7kIDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T10:15:36.871270Z"},"content_sha256":"d727a5fcf2d91f55a31c131bacf85ed1c6673cae775b2fa84fe5d8f56b4bdb04","schema_version":"1.0","event_id":"sha256:d727a5fcf2d91f55a31c131bacf85ed1c6673cae775b2fa84fe5d8f56b4bdb04"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TWMD6CKTOH2CHVOE47C3SATDMM/bundle.json","state_url":"https://pith.science/pith/TWMD6CKTOH2CHVOE47C3SATDMM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TWMD6CKTOH2CHVOE47C3SATDMM/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":"2026-08-14T10:15:36Z","links":{"resolver":"https://pith.science/pith/TWMD6CKTOH2CHVOE47C3SATDMM","bundle":"https://pith.science/pith/TWMD6CKTOH2CHVOE47C3SATDMM/bundle.json","state":"https://pith.science/pith/TWMD6CKTOH2CHVOE47C3SATDMM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TWMD6CKTOH2CHVOE47C3SATDMM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TWMD6CKTOH2CHVOE47C3SATDMM","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":"608e3cb5baeea4859b06f48ca2be0e0752bbf5e176f9156b4fc0d8c6fb4c5d89","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-11T17:57:49Z","title_canon_sha256":"4c17bf82a264d4ef7d761f4248e884c204e34ed3c56e178b689a9debbda32f97"},"schema_version":"1.0","source":{"id":"2406.07536","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07536","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07536v1","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07536","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_12","alias_value":"TWMD6CKTOH2C","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_16","alias_value":"TWMD6CKTOH2CHVOE","created_at":"2026-07-05T08:30:26Z"},{"alias_kind":"pith_short_8","alias_value":"TWMD6CKT","created_at":"2026-07-05T08:30:26Z"}],"graph_snapshots":[{"event_id":"sha256:d727a5fcf2d91f55a31c131bacf85ed1c6673cae775b2fa84fe5d8f56b4bdb04","target":"graph","created_at":"2026-07-05T08:30:26Z","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/2406.07536/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The advancement of deep learning technologies is bringing new models every day, motivating the study of scalable model selection. An ideal model selection scheme should minimally support two operations efficiently over a large pool of candidate models: update, which involves either adding a new candidate model or removing an existing candidate model, and selection, which involves locating highly performing models for a given task. However, previous solutions to model selection require high computational complexity for at least one of these two operations. In this work, we target fundamentally ","authors_text":"Lingjuan Lyu, Weiming Zhuang, Wenxiao Wang","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-11T17:57:49Z","title":"Towards Fundamentally Scalable Model Selection: Asymptotically Fast Update and Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07536","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":"sha256:90d10ce569ea3a1780a37cc190c9922bf8250f68578cd8f6a1efac1f9f110918","target":"record","created_at":"2026-07-05T08:30:26Z","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":"608e3cb5baeea4859b06f48ca2be0e0752bbf5e176f9156b4fc0d8c6fb4c5d89","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-06-11T17:57:49Z","title_canon_sha256":"4c17bf82a264d4ef7d761f4248e884c204e34ed3c56e178b689a9debbda32f97"},"schema_version":"1.0","source":{"id":"2406.07536","kind":"arxiv","version":1}},"canonical_sha256":"9d983f095371f423d5c4e7c5b90263631aaa3c75fdb025029832e800b592eaf4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d983f095371f423d5c4e7c5b90263631aaa3c75fdb025029832e800b592eaf4","first_computed_at":"2026-07-05T08:30:26.720194Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:30:26.720194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+Md9Q8oiKy5gMYG0RCjGz9elflqV0XlI2xsP6HPWas3xjhHPkOyQVvM0MGrZA92xq9sBNNDL2HtSznGR97QTCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:30:26.720736Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.07536","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90d10ce569ea3a1780a37cc190c9922bf8250f68578cd8f6a1efac1f9f110918","sha256:d727a5fcf2d91f55a31c131bacf85ed1c6673cae775b2fa84fe5d8f56b4bdb04"],"state_sha256":"8d83b2989008eab180c743de222d7e3c7728f97845dea9a2e178ba4e650089c7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qL57xuJ9AoQm54b81bkKEgmtChGJj7ZAiBUlIOf5bTUu0k84cyNwggDE5qR3TIYCPE4lfhCQoLVgGhJrRRoEAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T10:15:36.876678Z","bundle_sha256":"f008de4af505f543b2fa86304afda112f84fc499d8e7998195103f4c0a457008"}}