{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:APRZWLF365VMAJD7IIWVTBXJXT","short_pith_number":"pith:APRZWLF3","canonical_record":{"source":{"id":"2607.00275","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T23:51:44Z","cross_cats_sorted":["cs.AI","cs.DC","stat.ML"],"title_canon_sha256":"27c7c17c0466f42a82b5226f0e180a45cea3293d1df41a6203c3b29fa1772de5","abstract_canon_sha256":"4ddf8dbd6138e6d116651b3ccb2f11b461fd442cbd345510e158285aeb3c9cbb"},"schema_version":"1.0"},"canonical_sha256":"03e39b2cbbf76ac0247f422d5986e9bce4ca29b74aef67d94a2a7a3c9514371c","source":{"kind":"arxiv","id":"2607.00275","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00275","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00275v1","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00275","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_12","alias_value":"APRZWLF365VM","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_16","alias_value":"APRZWLF365VMAJD7","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_8","alias_value":"APRZWLF3","created_at":"2026-07-02T00:18:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:APRZWLF365VMAJD7IIWVTBXJXT","target":"record","payload":{"canonical_record":{"source":{"id":"2607.00275","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T23:51:44Z","cross_cats_sorted":["cs.AI","cs.DC","stat.ML"],"title_canon_sha256":"27c7c17c0466f42a82b5226f0e180a45cea3293d1df41a6203c3b29fa1772de5","abstract_canon_sha256":"4ddf8dbd6138e6d116651b3ccb2f11b461fd442cbd345510e158285aeb3c9cbb"},"schema_version":"1.0"},"canonical_sha256":"03e39b2cbbf76ac0247f422d5986e9bce4ca29b74aef67d94a2a7a3c9514371c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T00:18:42.461111Z","signature_b64":"X6ufWQPoGU1vtSfncDhAMrfL3v5sCRugrmdESFaZ/W4oV4on4Cp//mWn7Ffhp3c5arr36T3/q2FmeGeMdHR0Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"03e39b2cbbf76ac0247f422d5986e9bce4ca29b74aef67d94a2a7a3c9514371c","last_reissued_at":"2026-07-02T00:18:42.460301Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T00:18:42.460301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.00275","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":"2026-07-02T00:18:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jYcZx9kpzavWFM6soJPKad0hW6Qc3A65ZoJB5x3hmsCPWz4FfIxtZNBoTeyxmWj/zzA/ViyW4xm3rMj0U7PdDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:39:42.355090Z"},"content_sha256":"5b5f66ea1cf6932e14f1f77aa8f2fe967544fccc8505b8f94c9d25452b30cfd4","schema_version":"1.0","event_id":"sha256:5b5f66ea1cf6932e14f1f77aa8f2fe967544fccc8505b8f94c9d25452b30cfd4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:APRZWLF365VMAJD7IIWVTBXJXT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alireza Olama, Andreas Lundell, Krishna Harsha Kovelakuntla Huthasana","submitted_at":"2026-06-30T23:51:44Z","abstract_excerpt":"Federated Learning (FL) is a distributed machine learning (ML) paradigm with collaboration among multiple clients without sharing data. FL is challenging under data heterogeneity and partial client participation. Learning sparse models is useful for communication and computational efficiency in FL, but it is especially difficult in the small-sample high-dimensional regime (d >> N) where optimization can yield parameter configurations that fail to generalize to unseen test data. While magnitude-based pruning doesn't account for uncertainty exploration in the parameter space, a formulation with "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00275","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/2607.00275/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":"2026-07-02T00:18:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7VeYQQgBTFTaarTHeSo9kGN/ko0iUb/XY+FWxilAaalSIO3nNncmep7qPDJ9lXoLZEE6zO2Tv8PQiL2txqsHDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:39:42.355484Z"},"content_sha256":"384953084c1d18f90d0f26fe2ca6c71b85f0924f2af95f76cfe405bf544afd87","schema_version":"1.0","event_id":"sha256:384953084c1d18f90d0f26fe2ca6c71b85f0924f2af95f76cfe405bf544afd87"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/APRZWLF365VMAJD7IIWVTBXJXT/bundle.json","state_url":"https://pith.science/pith/APRZWLF365VMAJD7IIWVTBXJXT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/APRZWLF365VMAJD7IIWVTBXJXT/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":"2026-07-05T14:39:42Z","links":{"resolver":"https://pith.science/pith/APRZWLF365VMAJD7IIWVTBXJXT","bundle":"https://pith.science/pith/APRZWLF365VMAJD7IIWVTBXJXT/bundle.json","state":"https://pith.science/pith/APRZWLF365VMAJD7IIWVTBXJXT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/APRZWLF365VMAJD7IIWVTBXJXT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:APRZWLF365VMAJD7IIWVTBXJXT","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":"4ddf8dbd6138e6d116651b3ccb2f11b461fd442cbd345510e158285aeb3c9cbb","cross_cats_sorted":["cs.AI","cs.DC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T23:51:44Z","title_canon_sha256":"27c7c17c0466f42a82b5226f0e180a45cea3293d1df41a6203c3b29fa1772de5"},"schema_version":"1.0","source":{"id":"2607.00275","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00275","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00275v1","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00275","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_12","alias_value":"APRZWLF365VM","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_16","alias_value":"APRZWLF365VMAJD7","created_at":"2026-07-02T00:18:42Z"},{"alias_kind":"pith_short_8","alias_value":"APRZWLF3","created_at":"2026-07-02T00:18:42Z"}],"graph_snapshots":[{"event_id":"sha256:384953084c1d18f90d0f26fe2ca6c71b85f0924f2af95f76cfe405bf544afd87","target":"graph","created_at":"2026-07-02T00:18:42Z","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/2607.00275/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated Learning (FL) is a distributed machine learning (ML) paradigm with collaboration among multiple clients without sharing data. FL is challenging under data heterogeneity and partial client participation. Learning sparse models is useful for communication and computational efficiency in FL, but it is especially difficult in the small-sample high-dimensional regime (d >> N) where optimization can yield parameter configurations that fail to generalize to unseen test data. While magnitude-based pruning doesn't account for uncertainty exploration in the parameter space, a formulation with ","authors_text":"Alireza Olama, Andreas Lundell, Krishna Harsha Kovelakuntla Huthasana","cross_cats":["cs.AI","cs.DC","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T23:51:44Z","title":"Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00275","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":"sha256:5b5f66ea1cf6932e14f1f77aa8f2fe967544fccc8505b8f94c9d25452b30cfd4","target":"record","created_at":"2026-07-02T00:18:42Z","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":"4ddf8dbd6138e6d116651b3ccb2f11b461fd442cbd345510e158285aeb3c9cbb","cross_cats_sorted":["cs.AI","cs.DC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T23:51:44Z","title_canon_sha256":"27c7c17c0466f42a82b5226f0e180a45cea3293d1df41a6203c3b29fa1772de5"},"schema_version":"1.0","source":{"id":"2607.00275","kind":"arxiv","version":1}},"canonical_sha256":"03e39b2cbbf76ac0247f422d5986e9bce4ca29b74aef67d94a2a7a3c9514371c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03e39b2cbbf76ac0247f422d5986e9bce4ca29b74aef67d94a2a7a3c9514371c","first_computed_at":"2026-07-02T00:18:42.460301Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T00:18:42.460301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X6ufWQPoGU1vtSfncDhAMrfL3v5sCRugrmdESFaZ/W4oV4on4Cp//mWn7Ffhp3c5arr36T3/q2FmeGeMdHR0Cw==","signature_status":"signed_v1","signed_at":"2026-07-02T00:18:42.461111Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00275","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b5f66ea1cf6932e14f1f77aa8f2fe967544fccc8505b8f94c9d25452b30cfd4","sha256:384953084c1d18f90d0f26fe2ca6c71b85f0924f2af95f76cfe405bf544afd87"],"state_sha256":"0d26cbf588c68862696b436ad4db373a80e25c262ad85ebdab6fe2e586fb28a0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lz0ztXXesNO2leWhPYb3XtmbreIsCjXVInc+AkdK5Iw3P4StwWnzHpET54y9VVhDD7lM+S1Nq1tm2gJn1/NqDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T14:39:42.358052Z","bundle_sha256":"65e2d16da3d5707088b56ee7877ce9cd644d48aef6858f546ff0e83c3fc8a551"}}