{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W6COKIDPGPH53HALNSFBTMNT4B","short_pith_number":"pith:W6COKIDP","canonical_record":{"source":{"id":"2407.16058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-22T21:26:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"09ee9bdd271595369ffeb45c53143581406b38583df339374c50a0c5dcbd9c62","abstract_canon_sha256":"40633ddc902c933e4df26ceee29b4e8d5a1c93cafe8539bd0983da837ccec91c"},"schema_version":"1.0"},"canonical_sha256":"b784e5206f33cfdd9c0b6c8a19b1b3e07fed1fc07a163d60a22791d5c7bfff6c","source":{"kind":"arxiv","id":"2407.16058","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.16058","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2407.16058v2","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.16058","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"W6COKIDPGPH5","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"W6COKIDPGPH53HAL","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"W6COKIDP","created_at":"2026-07-05T08:56:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W6COKIDPGPH53HALNSFBTMNT4B","target":"record","payload":{"canonical_record":{"source":{"id":"2407.16058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-22T21:26:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"09ee9bdd271595369ffeb45c53143581406b38583df339374c50a0c5dcbd9c62","abstract_canon_sha256":"40633ddc902c933e4df26ceee29b4e8d5a1c93cafe8539bd0983da837ccec91c"},"schema_version":"1.0"},"canonical_sha256":"b784e5206f33cfdd9c0b6c8a19b1b3e07fed1fc07a163d60a22791d5c7bfff6c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:56:05.620554Z","signature_b64":"JiO76aZN+U72jYZ3KVPO0n9lr2mcU8KtpG7oc75NAX11elTWRSieG5HRTuXxjkI1uaV4R+et/hjhRu81/Y9PDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b784e5206f33cfdd9c0b6c8a19b1b3e07fed1fc07a163d60a22791d5c7bfff6c","last_reissued_at":"2026-07-05T08:56:05.619988Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:56:05.619988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.16058","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":"2026-07-05T08:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pZc1M78uAjq3/rmmeMrIMZF0C31a4lJDwGG/lUlPgiOpR7llyd4zTyOxUm3DXaH6yo0otyhXdNt5ucI5O/rvAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:51:15.254084Z"},"content_sha256":"0ef5abdcf7fde09b7e6e3cd5f179d0d84e11f1bd484b488cc49d772a9fcf6696","schema_version":"1.0","event_id":"sha256:0ef5abdcf7fde09b7e6e3cd5f179d0d84e11f1bd484b488cc49d772a9fcf6696"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W6COKIDPGPH53HALNSFBTMNT4B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Score Function Estimators for $k$-Subset Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Hossein Azizpour, Klas Wijk, Ricardo Vinuesa","submitted_at":"2024-07-22T21:26:39Z","abstract_excerpt":"Are score function estimators an underestimated approach to learning with $k$-subset sampling? Sampling $k$-subsets is a fundamental operation in many machine learning tasks that is not amenable to differentiable parametrization, impeding gradient-based optimization. Prior work has focused on relaxed sampling or pathwise gradient estimators. Inspired by the success of score function estimators in variational inference and reinforcement learning, we revisit them within the context of $k$-subset sampling. Specifically, we demonstrate how to efficiently compute the $k$-subset distribution's score"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.16058","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/2407.16058/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":"2026-07-05T08:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bYJTglH905ry/ASm3XK/xiEAroVAp4dtOBSP4BAeVc66bSLKhbSq05k/zjK5My+67UYodPTADrri5tJDq5oqAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:51:15.256477Z"},"content_sha256":"ee3232340932a197b9b213d95b146c537588ee315fc3221d49c6b8fd20e0da0d","schema_version":"1.0","event_id":"sha256:ee3232340932a197b9b213d95b146c537588ee315fc3221d49c6b8fd20e0da0d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W6COKIDPGPH53HALNSFBTMNT4B/bundle.json","state_url":"https://pith.science/pith/W6COKIDPGPH53HALNSFBTMNT4B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W6COKIDPGPH53HALNSFBTMNT4B/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":"2026-08-13T05:51:15Z","links":{"resolver":"https://pith.science/pith/W6COKIDPGPH53HALNSFBTMNT4B","bundle":"https://pith.science/pith/W6COKIDPGPH53HALNSFBTMNT4B/bundle.json","state":"https://pith.science/pith/W6COKIDPGPH53HALNSFBTMNT4B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W6COKIDPGPH53HALNSFBTMNT4B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W6COKIDPGPH53HALNSFBTMNT4B","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":"40633ddc902c933e4df26ceee29b4e8d5a1c93cafe8539bd0983da837ccec91c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-22T21:26:39Z","title_canon_sha256":"09ee9bdd271595369ffeb45c53143581406b38583df339374c50a0c5dcbd9c62"},"schema_version":"1.0","source":{"id":"2407.16058","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.16058","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2407.16058v2","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.16058","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"W6COKIDPGPH5","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"W6COKIDPGPH53HAL","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"W6COKIDP","created_at":"2026-07-05T08:56:05Z"}],"graph_snapshots":[{"event_id":"sha256:ee3232340932a197b9b213d95b146c537588ee315fc3221d49c6b8fd20e0da0d","target":"graph","created_at":"2026-07-05T08:56:05Z","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/2407.16058/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Are score function estimators an underestimated approach to learning with $k$-subset sampling? Sampling $k$-subsets is a fundamental operation in many machine learning tasks that is not amenable to differentiable parametrization, impeding gradient-based optimization. Prior work has focused on relaxed sampling or pathwise gradient estimators. Inspired by the success of score function estimators in variational inference and reinforcement learning, we revisit them within the context of $k$-subset sampling. Specifically, we demonstrate how to efficiently compute the $k$-subset distribution's score","authors_text":"Hossein Azizpour, Klas Wijk, Ricardo Vinuesa","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-22T21:26:39Z","title":"Revisiting Score Function Estimators for $k$-Subset Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.16058","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":"sha256:0ef5abdcf7fde09b7e6e3cd5f179d0d84e11f1bd484b488cc49d772a9fcf6696","target":"record","created_at":"2026-07-05T08:56:05Z","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":"40633ddc902c933e4df26ceee29b4e8d5a1c93cafe8539bd0983da837ccec91c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-22T21:26:39Z","title_canon_sha256":"09ee9bdd271595369ffeb45c53143581406b38583df339374c50a0c5dcbd9c62"},"schema_version":"1.0","source":{"id":"2407.16058","kind":"arxiv","version":2}},"canonical_sha256":"b784e5206f33cfdd9c0b6c8a19b1b3e07fed1fc07a163d60a22791d5c7bfff6c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b784e5206f33cfdd9c0b6c8a19b1b3e07fed1fc07a163d60a22791d5c7bfff6c","first_computed_at":"2026-07-05T08:56:05.619988Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:56:05.619988Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JiO76aZN+U72jYZ3KVPO0n9lr2mcU8KtpG7oc75NAX11elTWRSieG5HRTuXxjkI1uaV4R+et/hjhRu81/Y9PDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:56:05.620554Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.16058","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ef5abdcf7fde09b7e6e3cd5f179d0d84e11f1bd484b488cc49d772a9fcf6696","sha256:ee3232340932a197b9b213d95b146c537588ee315fc3221d49c6b8fd20e0da0d"],"state_sha256":"2498f2c388fe88fe62f345705460b798d0605427c49eb5065ffe2894e761b674"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DVk0uXDSmzFZIWwOyqWbexd5o7RJJeTOVdvNkfvfZUfmvnP4KAsS84UcriUi2M3bHYUecwXqTnJYXEeRLeYuDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T05:51:15.317399Z","bundle_sha256":"de489f66f5d6fb2b9cbb27f946c5f6ed02fce13dedf448bd0485712b11994358"}}