{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:4XKU6PLWS237X4UIVUSWPWEGFV","short_pith_number":"pith:4XKU6PLW","schema_version":"1.0","canonical_sha256":"e5d54f3d7696b7fbf288ad2567d8862d6b8cb786be44ae674587af7a610a564e","source":{"kind":"arxiv","id":"2405.16460","version":1},"attestation_state":"computed","paper":{"title":"Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Bjoern Menze, Cheng Ouyang, Hongwei Bran Li, Juan Eugenio Iglesias, Matthew S. Rosen, Tamaz Amiranashvili","submitted_at":"2024-05-26T07:08:13Z","abstract_excerpt":"Self-supervised contrastive learning has predominantly adopted deterministic methods, which are not suited for environments characterized by uncertainty and noise. This paper introduces a new perspective on incorporating uncertainty into contrastive learning by embedding representations within a spherical space, inspired by the von Mises-Fisher distribution (vMF). We introduce an unnormalized form of vMF and leverage the concentration parameter, kappa, as a direct, interpretable measure to quantify uncertainty explicitly. This approach not only provides a probabilistic interpretation of the em"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.16460","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-26T07:08:13Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"5783c4824e9d6762e4a4f0be1404a496e01b883c5f55c483b9d1b075c6952db9","abstract_canon_sha256":"86835798ca2b21678a971c03a05923b1ed550c37c97bfdf1e2159f18680aabdb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:23:30.689672Z","signature_b64":"YGRP/OzIrBxyY9dzTJFosR7aNA8KBit8Qgg98cFA1MVzHAooIXMABWcPKsZISk8PDrX2DoAR7AcuxsmkjkNkAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5d54f3d7696b7fbf288ad2567d8862d6b8cb786be44ae674587af7a610a564e","last_reissued_at":"2026-07-05T08:23:30.689099Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:23:30.689099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Bjoern Menze, Cheng Ouyang, Hongwei Bran Li, Juan Eugenio Iglesias, Matthew S. Rosen, Tamaz Amiranashvili","submitted_at":"2024-05-26T07:08:13Z","abstract_excerpt":"Self-supervised contrastive learning has predominantly adopted deterministic methods, which are not suited for environments characterized by uncertainty and noise. This paper introduces a new perspective on incorporating uncertainty into contrastive learning by embedding representations within a spherical space, inspired by the von Mises-Fisher distribution (vMF). We introduce an unnormalized form of vMF and leverage the concentration parameter, kappa, as a direct, interpretable measure to quantify uncertainty explicitly. This approach not only provides a probabilistic interpretation of the em"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.16460","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/2405.16460/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.16460","created_at":"2026-07-05T08:23:30.689170+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.16460v1","created_at":"2026-07-05T08:23:30.689170+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.16460","created_at":"2026-07-05T08:23:30.689170+00:00"},{"alias_kind":"pith_short_12","alias_value":"4XKU6PLWS237","created_at":"2026-07-05T08:23:30.689170+00:00"},{"alias_kind":"pith_short_16","alias_value":"4XKU6PLWS237X4UI","created_at":"2026-07-05T08:23:30.689170+00:00"},{"alias_kind":"pith_short_8","alias_value":"4XKU6PLW","created_at":"2026-07-05T08:23:30.689170+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV","json":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV.json","graph_json":"https://pith.science/api/pith-number/4XKU6PLWS237X4UIVUSWPWEGFV/graph.json","events_json":"https://pith.science/api/pith-number/4XKU6PLWS237X4UIVUSWPWEGFV/events.json","paper":"https://pith.science/paper/4XKU6PLW"},"agent_actions":{"view_html":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV","download_json":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV.json","view_paper":"https://pith.science/paper/4XKU6PLW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.16460&json=true","fetch_graph":"https://pith.science/api/pith-number/4XKU6PLWS237X4UIVUSWPWEGFV/graph.json","fetch_events":"https://pith.science/api/pith-number/4XKU6PLWS237X4UIVUSWPWEGFV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV/action/storage_attestation","attest_author":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV/action/author_attestation","sign_citation":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV/action/citation_signature","submit_replication":"https://pith.science/pith/4XKU6PLWS237X4UIVUSWPWEGFV/action/replication_record"}},"created_at":"2026-07-05T08:23:30.689170+00:00","updated_at":"2026-07-05T08:23:30.689170+00:00"}