{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:CAK5MI74FQUZMSPJWXGMP2K2UC","short_pith_number":"pith:CAK5MI74","canonical_record":{"source":{"id":"2311.01864","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-03T12:14:26Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"title_canon_sha256":"d65ddbcb6459d2a3a55dc5c036bde0212572258b3b98fd82cfbce0b77b9f3c0a","abstract_canon_sha256":"29e08025085d1afd5785981b29c1dea0af141043c2874316f605130c9742a9fb"},"schema_version":"1.0"},"canonical_sha256":"1015d623fc2c299649e9b5ccc7e95aa08b526e7a41dd2d893bd4c401df8caea5","source":{"kind":"arxiv","id":"2311.01864","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.01864","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"arxiv_version","alias_value":"2311.01864v1","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.01864","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_12","alias_value":"CAK5MI74FQUZ","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_16","alias_value":"CAK5MI74FQUZMSPJ","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_8","alias_value":"CAK5MI74","created_at":"2026-07-05T07:08:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:CAK5MI74FQUZMSPJWXGMP2K2UC","target":"record","payload":{"canonical_record":{"source":{"id":"2311.01864","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-03T12:14:26Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"title_canon_sha256":"d65ddbcb6459d2a3a55dc5c036bde0212572258b3b98fd82cfbce0b77b9f3c0a","abstract_canon_sha256":"29e08025085d1afd5785981b29c1dea0af141043c2874316f605130c9742a9fb"},"schema_version":"1.0"},"canonical_sha256":"1015d623fc2c299649e9b5ccc7e95aa08b526e7a41dd2d893bd4c401df8caea5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:08:46.399454Z","signature_b64":"r9bf1hAI0Kl0ln5+LvMQETNaCQuHC8hKoqxvur2fGHscxldpo4W6f5ROZMRwDMwpt6H1Bme71cB78IkiXLB8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1015d623fc2c299649e9b5ccc7e95aa08b526e7a41dd2d893bd4c401df8caea5","last_reissued_at":"2026-07-05T07:08:46.399046Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:08:46.399046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.01864","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":"2026-07-05T07:08:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UouXTtq3SHgy14QRD7YurWf4PNl5dMDfCkQoQqtCoWPBX01rztWSBF4Zw/tNmlDxz17aCIK07FhrVFBcAZbwAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:30:40.905591Z"},"content_sha256":"8f0f2df12c73ac68d965c8f19d8f025c141af7124c3a38f1b31b0b64b5d3242b","schema_version":"1.0","event_id":"sha256:8f0f2df12c73ac68d965c8f19d8f025c141af7124c3a38f1b31b0b64b5d3242b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:CAK5MI74FQUZMSPJWXGMP2K2UC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SortNet: Learning To Rank By a Neural-Based Sorting Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.IR"],"primary_cat":"cs.LG","authors_text":"Franco Scarselli, Leonardo Rigutini, Marco Maggini, Tiziano Papini","submitted_at":"2023-11-03T12:14:26Z","abstract_excerpt":"The problem of relevance ranking consists of sorting a set of objects with respect to a given criterion. Since users may prefer different relevance criteria, the ranking algorithms should be adaptable to the user needs. Two main approaches exist in literature for the task of learning to rank: 1) a score function, learned by examples, which evaluates the properties of each object yielding an absolute relevance value that can be used to order the objects or 2) a pairwise approach, where a \"preference function\" is learned using pairs of objects to define which one has to be ranked first. In this "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.01864","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/2311.01864/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":"2026-07-05T07:08:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x9KGb0vFVi563da637sxdTUQ69FTTSpBDD0mVeXIbuohZEfSQpE9SGAorb40Lfq/0NdsVaN4eRHHGLI87TBADg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:30:40.906178Z"},"content_sha256":"dbcb7b56729ecc376b7f895de3cdf08935170c0f87efced690e4db8ebf0e84ca","schema_version":"1.0","event_id":"sha256:dbcb7b56729ecc376b7f895de3cdf08935170c0f87efced690e4db8ebf0e84ca"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/bundle.json","state_url":"https://pith.science/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/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":"2026-07-31T18:30:40Z","links":{"resolver":"https://pith.science/pith/CAK5MI74FQUZMSPJWXGMP2K2UC","bundle":"https://pith.science/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/bundle.json","state":"https://pith.science/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CAK5MI74FQUZMSPJWXGMP2K2UC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CAK5MI74FQUZMSPJWXGMP2K2UC","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":"29e08025085d1afd5785981b29c1dea0af141043c2874316f605130c9742a9fb","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-03T12:14:26Z","title_canon_sha256":"d65ddbcb6459d2a3a55dc5c036bde0212572258b3b98fd82cfbce0b77b9f3c0a"},"schema_version":"1.0","source":{"id":"2311.01864","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.01864","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"arxiv_version","alias_value":"2311.01864v1","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.01864","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_12","alias_value":"CAK5MI74FQUZ","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_16","alias_value":"CAK5MI74FQUZMSPJ","created_at":"2026-07-05T07:08:46Z"},{"alias_kind":"pith_short_8","alias_value":"CAK5MI74","created_at":"2026-07-05T07:08:46Z"}],"graph_snapshots":[{"event_id":"sha256:dbcb7b56729ecc376b7f895de3cdf08935170c0f87efced690e4db8ebf0e84ca","target":"graph","created_at":"2026-07-05T07:08:46Z","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/2311.01864/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The problem of relevance ranking consists of sorting a set of objects with respect to a given criterion. Since users may prefer different relevance criteria, the ranking algorithms should be adaptable to the user needs. Two main approaches exist in literature for the task of learning to rank: 1) a score function, learned by examples, which evaluates the properties of each object yielding an absolute relevance value that can be used to order the objects or 2) a pairwise approach, where a \"preference function\" is learned using pairs of objects to define which one has to be ranked first. In this ","authors_text":"Franco Scarselli, Leonardo Rigutini, Marco Maggini, Tiziano Papini","cross_cats":["cs.AI","cs.CL","cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-03T12:14:26Z","title":"SortNet: Learning To Rank By a Neural-Based Sorting Algorithm"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.01864","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":"sha256:8f0f2df12c73ac68d965c8f19d8f025c141af7124c3a38f1b31b0b64b5d3242b","target":"record","created_at":"2026-07-05T07:08:46Z","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":"29e08025085d1afd5785981b29c1dea0af141043c2874316f605130c9742a9fb","cross_cats_sorted":["cs.AI","cs.CL","cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-03T12:14:26Z","title_canon_sha256":"d65ddbcb6459d2a3a55dc5c036bde0212572258b3b98fd82cfbce0b77b9f3c0a"},"schema_version":"1.0","source":{"id":"2311.01864","kind":"arxiv","version":1}},"canonical_sha256":"1015d623fc2c299649e9b5ccc7e95aa08b526e7a41dd2d893bd4c401df8caea5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1015d623fc2c299649e9b5ccc7e95aa08b526e7a41dd2d893bd4c401df8caea5","first_computed_at":"2026-07-05T07:08:46.399046Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:08:46.399046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r9bf1hAI0Kl0ln5+LvMQETNaCQuHC8hKoqxvur2fGHscxldpo4W6f5ROZMRwDMwpt6H1Bme71cB78IkiXLB8Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:08:46.399454Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.01864","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f0f2df12c73ac68d965c8f19d8f025c141af7124c3a38f1b31b0b64b5d3242b","sha256:dbcb7b56729ecc376b7f895de3cdf08935170c0f87efced690e4db8ebf0e84ca"],"state_sha256":"d8363b2b63e2877519ef984cbbba9f428111cf0901ee86f55b2f6551156b22c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m4H1xJ/KXBKT6UkAPc6cDKHh1Z67yICNUycvsuJHpQnMRgacXrg2nqBG3vryIihR5O9Tr5wF6tJymAzAdq9YAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T18:30:40.909137Z","bundle_sha256":"b84842ce3f11011df93773530bcbbdb09a24bbe8c51e5c5732d8dfb2878e6722"}}