{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JN47YP2FBO52HYYJWJMIXNPXBF","short_pith_number":"pith:JN47YP2F","canonical_record":{"source":{"id":"2405.14574","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-05-23T13:49:37Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b403e954040122d5a09e8f329da77699286a491141bc13cbb3bf2c4da9f770db","abstract_canon_sha256":"39e95dbcbe75851279c25c6b04838d11b87efcda7df1c1355a0df2d026c49bbc"},"schema_version":"1.0"},"canonical_sha256":"4b79fc3f450bbba3e309b2588bb5f7095456a4f3591db35c41414db8273996c7","source":{"kind":"arxiv","id":"2405.14574","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14574","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14574v1","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14574","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_12","alias_value":"JN47YP2FBO52","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_16","alias_value":"JN47YP2FBO52HYYJ","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_8","alias_value":"JN47YP2F","created_at":"2026-07-05T08:22:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JN47YP2FBO52HYYJWJMIXNPXBF","target":"record","payload":{"canonical_record":{"source":{"id":"2405.14574","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-05-23T13:49:37Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b403e954040122d5a09e8f329da77699286a491141bc13cbb3bf2c4da9f770db","abstract_canon_sha256":"39e95dbcbe75851279c25c6b04838d11b87efcda7df1c1355a0df2d026c49bbc"},"schema_version":"1.0"},"canonical_sha256":"4b79fc3f450bbba3e309b2588bb5f7095456a4f3591db35c41414db8273996c7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:22:25.337672Z","signature_b64":"zKDmkV1Kpuim5+Fc5Bqv901y+tcdUWSbWsmITQtZ6J0zpMrIjZpcl/8Lv+jnbzPT2FdWSPMB8I/qlJZCFU/sCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b79fc3f450bbba3e309b2588bb5f7095456a4f3591db35c41414db8273996c7","last_reissued_at":"2026-07-05T08:22:25.337202Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:22:25.337202Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.14574","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":"2026-07-05T08:22:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6MQHzBUjLKtpdlWjbMkquT5BzuKKlhG38jSSOSSY5QN7CsIHSo0DZBCtFGzMYM7oBgYIker0pXrIeGuY63BmDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:42:46.438906Z"},"content_sha256":"41bdf4a308efdf79514ac5cbd2df17b08aa9c5cfe280ddd5b99dae4d8b9a231a","schema_version":"1.0","event_id":"sha256:41bdf4a308efdf79514ac5cbd2df17b08aa9c5cfe280ddd5b99dae4d8b9a231a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JN47YP2FBO52HYYJWJMIXNPXBF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning with Fitzpatrick Losses","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Jean-Philippe Chancelier, Mathieu Blondel, Michel De Lara, Seta Rakotomandimby","submitted_at":"2024-05-23T13:49:37Z","abstract_excerpt":"Fenchel-Young losses are a family of convex loss functions, encompassing the squared, logistic and sparsemax losses, among others. Each Fenchel-Young loss is implicitly associated with a link function, for mapping model outputs to predictions. For instance, the logistic loss is associated with the soft argmax link function. Can we build new loss functions associated with the same link function as Fenchel-Young losses? In this paper, we introduce Fitzpatrick losses, a new family of convex loss functions based on the Fitzpatrick function. A well-known theoretical tool in maximal monotone operato"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14574","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/2405.14574/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":"2026-07-05T08:22:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aCDVCbAwnnX/e7u2sU0dJmeT3bT8OIgjeeIwDu4W3iUExM/XavljKGp3K/sD+CwFerZRcJddUEbCnWKZrDqdCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:42:46.439483Z"},"content_sha256":"76f2e80aa0e69b1e3e6154591576efd2296dca6ce4634bfcd68204109e6f7d50","schema_version":"1.0","event_id":"sha256:76f2e80aa0e69b1e3e6154591576efd2296dca6ce4634bfcd68204109e6f7d50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JN47YP2FBO52HYYJWJMIXNPXBF/bundle.json","state_url":"https://pith.science/pith/JN47YP2FBO52HYYJWJMIXNPXBF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JN47YP2FBO52HYYJWJMIXNPXBF/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":"2026-08-19T16:42:46Z","links":{"resolver":"https://pith.science/pith/JN47YP2FBO52HYYJWJMIXNPXBF","bundle":"https://pith.science/pith/JN47YP2FBO52HYYJWJMIXNPXBF/bundle.json","state":"https://pith.science/pith/JN47YP2FBO52HYYJWJMIXNPXBF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JN47YP2FBO52HYYJWJMIXNPXBF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JN47YP2FBO52HYYJWJMIXNPXBF","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":"39e95dbcbe75851279c25c6b04838d11b87efcda7df1c1355a0df2d026c49bbc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-05-23T13:49:37Z","title_canon_sha256":"b403e954040122d5a09e8f329da77699286a491141bc13cbb3bf2c4da9f770db"},"schema_version":"1.0","source":{"id":"2405.14574","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14574","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14574v1","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14574","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_12","alias_value":"JN47YP2FBO52","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_16","alias_value":"JN47YP2FBO52HYYJ","created_at":"2026-07-05T08:22:25Z"},{"alias_kind":"pith_short_8","alias_value":"JN47YP2F","created_at":"2026-07-05T08:22:25Z"}],"graph_snapshots":[{"event_id":"sha256:76f2e80aa0e69b1e3e6154591576efd2296dca6ce4634bfcd68204109e6f7d50","target":"graph","created_at":"2026-07-05T08:22:25Z","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/2405.14574/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fenchel-Young losses are a family of convex loss functions, encompassing the squared, logistic and sparsemax losses, among others. Each Fenchel-Young loss is implicitly associated with a link function, for mapping model outputs to predictions. For instance, the logistic loss is associated with the soft argmax link function. Can we build new loss functions associated with the same link function as Fenchel-Young losses? In this paper, we introduce Fitzpatrick losses, a new family of convex loss functions based on the Fitzpatrick function. A well-known theoretical tool in maximal monotone operato","authors_text":"Jean-Philippe Chancelier, Mathieu Blondel, Michel De Lara, Seta Rakotomandimby","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-05-23T13:49:37Z","title":"Learning with Fitzpatrick Losses"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14574","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":"sha256:41bdf4a308efdf79514ac5cbd2df17b08aa9c5cfe280ddd5b99dae4d8b9a231a","target":"record","created_at":"2026-07-05T08:22:25Z","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":"39e95dbcbe75851279c25c6b04838d11b87efcda7df1c1355a0df2d026c49bbc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2024-05-23T13:49:37Z","title_canon_sha256":"b403e954040122d5a09e8f329da77699286a491141bc13cbb3bf2c4da9f770db"},"schema_version":"1.0","source":{"id":"2405.14574","kind":"arxiv","version":1}},"canonical_sha256":"4b79fc3f450bbba3e309b2588bb5f7095456a4f3591db35c41414db8273996c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b79fc3f450bbba3e309b2588bb5f7095456a4f3591db35c41414db8273996c7","first_computed_at":"2026-07-05T08:22:25.337202Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:22:25.337202Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zKDmkV1Kpuim5+Fc5Bqv901y+tcdUWSbWsmITQtZ6J0zpMrIjZpcl/8Lv+jnbzPT2FdWSPMB8I/qlJZCFU/sCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:22:25.337672Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.14574","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:41bdf4a308efdf79514ac5cbd2df17b08aa9c5cfe280ddd5b99dae4d8b9a231a","sha256:76f2e80aa0e69b1e3e6154591576efd2296dca6ce4634bfcd68204109e6f7d50"],"state_sha256":"efb8a9b36b5c238d32f54d99bcd8400df53ef9dc467c5934e6ecdaef7497cc33"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dcJYT+0wx+E8Lln4td+j8SgQAC8OjIMRD0VuMSQmE7WwBUuyUGqgeImZHuh6ysL66uXC6NIWQqvZn0VEKv7kAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T16:42:46.444965Z","bundle_sha256":"9eb37d8a698bcdf77cf31efb7c018abb3e046da68b144cb4b81bce57f6a8e73e"}}