{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7KLSJRYOKSCTNEVDP7RZD65FNA","short_pith_number":"pith:7KLSJRYO","canonical_record":{"source":{"id":"2101.11684","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T20:56:19Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"188b680d7c214c910127b4e38bb2fe21a9eb867b2807002d07e1ac598d122bb3","abstract_canon_sha256":"990fe3e7ab4af2cb787375e98d98e03ec28f00470023e7b6f4f4519c224760d6"},"schema_version":"1.0"},"canonical_sha256":"fa9724c70e54853692a37fe391fba5680f376a8903efc9bc5a3ba1ed56c75ccd","source":{"kind":"arxiv","id":"2101.11684","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.11684","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"arxiv_version","alias_value":"2101.11684v2","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.11684","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_12","alias_value":"7KLSJRYOKSCT","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_16","alias_value":"7KLSJRYOKSCTNEVD","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_8","alias_value":"7KLSJRYO","created_at":"2026-07-05T02:14:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7KLSJRYOKSCTNEVDP7RZD65FNA","target":"record","payload":{"canonical_record":{"source":{"id":"2101.11684","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T20:56:19Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"188b680d7c214c910127b4e38bb2fe21a9eb867b2807002d07e1ac598d122bb3","abstract_canon_sha256":"990fe3e7ab4af2cb787375e98d98e03ec28f00470023e7b6f4f4519c224760d6"},"schema_version":"1.0"},"canonical_sha256":"fa9724c70e54853692a37fe391fba5680f376a8903efc9bc5a3ba1ed56c75ccd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:14:57.026821Z","signature_b64":"1kUvh8wP5bV7sYevsxgC+s713f2t2hBu8pB6+9klySnThrsA+IJGqrssT3HKx914ixPE2yykRk5TrZ2FG/LJAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa9724c70e54853692a37fe391fba5680f376a8903efc9bc5a3ba1ed56c75ccd","last_reissued_at":"2026-07-05T02:14:57.026434Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:14:57.026434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.11684","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:14:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kNF6kz6JGNWNtZeAKTWNKYd7K/pmBxxd4xtqrMMvyBIrJ1/rqmrkqReb2HTjersRfFG9JfFltt9mQVSZdvdZAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:17:41.461697Z"},"content_sha256":"1fbdde3e0763439a3172ee6eb3057002902a61c361d8e8e054ebe3ecb97ec288","schema_version":"1.0","event_id":"sha256:1fbdde3e0763439a3172ee6eb3057002902a61c361d8e8e054ebe3ecb97ec288"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7KLSJRYOKSCTNEVDP7RZD65FNA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Hybrid 2-stage Neural Optimization for Pareto Front Extraction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.LG","authors_text":"Clint Dawson, Gurpreet Singh, Matthew Lease, Soumyajit Gupta","submitted_at":"2021-01-27T20:56:19Z","abstract_excerpt":"Classification, recommendation, and ranking problems often involve competing goals with additional constraints (e.g., to satisfy fairness or diversity criteria). Such optimization problems are quite challenging, often involving non-convex functions along with considerations of user preferences in balancing trade-offs. Pareto solutions represent optimal frontiers for jointly optimizing multiple competing objectives. A major obstacle for frequently used linear-scalarization strategies is that the resulting optimization problem might not always converge to a global optimum. Furthermore, such meth"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.11684","kind":"arxiv","version":2},"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/2101.11684/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":"2026-07-05T02:14:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0usdrRzMhAlUuoGNwJ5HrnkZFXf79PfPNoSMzANy2J4NpPtpaSQsvY7wd6S0dXiMmMumIROrYiIBpunL9TvEBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:17:41.462220Z"},"content_sha256":"2115b90bea6ff8d614fcbd9bceb603d9c138b831a36add8aa0eb13322d344eb0","schema_version":"1.0","event_id":"sha256:2115b90bea6ff8d614fcbd9bceb603d9c138b831a36add8aa0eb13322d344eb0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/bundle.json","state_url":"https://pith.science/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/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":"2026-08-16T11:17:41Z","links":{"resolver":"https://pith.science/pith/7KLSJRYOKSCTNEVDP7RZD65FNA","bundle":"https://pith.science/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/bundle.json","state":"https://pith.science/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7KLSJRYOKSCTNEVDP7RZD65FNA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7KLSJRYOKSCTNEVDP7RZD65FNA","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":"990fe3e7ab4af2cb787375e98d98e03ec28f00470023e7b6f4f4519c224760d6","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T20:56:19Z","title_canon_sha256":"188b680d7c214c910127b4e38bb2fe21a9eb867b2807002d07e1ac598d122bb3"},"schema_version":"1.0","source":{"id":"2101.11684","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.11684","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"arxiv_version","alias_value":"2101.11684v2","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.11684","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_12","alias_value":"7KLSJRYOKSCT","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_16","alias_value":"7KLSJRYOKSCTNEVD","created_at":"2026-07-05T02:14:57Z"},{"alias_kind":"pith_short_8","alias_value":"7KLSJRYO","created_at":"2026-07-05T02:14:57Z"}],"graph_snapshots":[{"event_id":"sha256:2115b90bea6ff8d614fcbd9bceb603d9c138b831a36add8aa0eb13322d344eb0","target":"graph","created_at":"2026-07-05T02:14:57Z","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/2101.11684/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Classification, recommendation, and ranking problems often involve competing goals with additional constraints (e.g., to satisfy fairness or diversity criteria). Such optimization problems are quite challenging, often involving non-convex functions along with considerations of user preferences in balancing trade-offs. Pareto solutions represent optimal frontiers for jointly optimizing multiple competing objectives. A major obstacle for frequently used linear-scalarization strategies is that the resulting optimization problem might not always converge to a global optimum. Furthermore, such meth","authors_text":"Clint Dawson, Gurpreet Singh, Matthew Lease, Soumyajit Gupta","cross_cats":["math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T20:56:19Z","title":"A Hybrid 2-stage Neural Optimization for Pareto Front Extraction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.11684","kind":"arxiv","version":2},"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":"sha256:1fbdde3e0763439a3172ee6eb3057002902a61c361d8e8e054ebe3ecb97ec288","target":"record","created_at":"2026-07-05T02:14:57Z","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":"990fe3e7ab4af2cb787375e98d98e03ec28f00470023e7b6f4f4519c224760d6","cross_cats_sorted":["math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T20:56:19Z","title_canon_sha256":"188b680d7c214c910127b4e38bb2fe21a9eb867b2807002d07e1ac598d122bb3"},"schema_version":"1.0","source":{"id":"2101.11684","kind":"arxiv","version":2}},"canonical_sha256":"fa9724c70e54853692a37fe391fba5680f376a8903efc9bc5a3ba1ed56c75ccd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa9724c70e54853692a37fe391fba5680f376a8903efc9bc5a3ba1ed56c75ccd","first_computed_at":"2026-07-05T02:14:57.026434Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:14:57.026434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1kUvh8wP5bV7sYevsxgC+s713f2t2hBu8pB6+9klySnThrsA+IJGqrssT3HKx914ixPE2yykRk5TrZ2FG/LJAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:14:57.026821Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.11684","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fbdde3e0763439a3172ee6eb3057002902a61c361d8e8e054ebe3ecb97ec288","sha256:2115b90bea6ff8d614fcbd9bceb603d9c138b831a36add8aa0eb13322d344eb0"],"state_sha256":"2f11120a3c045bf7a7516c3bd9a8b8b267f21129811e05bb78ae709ee3b3d150"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sycjRECSDv81q52JcLZDuKfBqBhD11urNwb3l3RsSsCxp6qVubP5vlbfXBo+R3TmpZZVjUFsUICqwShOYIcIAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T11:17:41.466836Z","bundle_sha256":"09ca8693f5478f39fa4e36d4fd816abf66ea3552413176e62ed384672e4bf6c4"}}