{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DL6WGVJEWPQA37ZCKVISMBGNBF","short_pith_number":"pith:DL6WGVJE","canonical_record":{"source":{"id":"2605.18035","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T08:24:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aeea752e6243baf20fd5c6a38f518a5bceb18cb9ec78d6570ff4200ee2a1314c","abstract_canon_sha256":"1ab5984850f2535c3b170e9bc2a953f59874f202033411f9b0704583745bd1b2"},"schema_version":"1.0"},"canonical_sha256":"1afd635524b3e00dff2255512604cd094f1679ee0e4d75da56cf40ba07ac7d31","source":{"kind":"arxiv","id":"2605.18035","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18035","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18035v1","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18035","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_12","alias_value":"DL6WGVJEWPQA","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_16","alias_value":"DL6WGVJEWPQA37ZC","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_8","alias_value":"DL6WGVJE","created_at":"2026-05-20T00:05:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DL6WGVJEWPQA37ZCKVISMBGNBF","target":"record","payload":{"canonical_record":{"source":{"id":"2605.18035","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T08:24:18Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aeea752e6243baf20fd5c6a38f518a5bceb18cb9ec78d6570ff4200ee2a1314c","abstract_canon_sha256":"1ab5984850f2535c3b170e9bc2a953f59874f202033411f9b0704583745bd1b2"},"schema_version":"1.0"},"canonical_sha256":"1afd635524b3e00dff2255512604cd094f1679ee0e4d75da56cf40ba07ac7d31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:12.468487Z","signature_b64":"UjDkSC6R0GNxfKnDIwhLPAaVTc2Hp4IEHIE99esnYb5nXdxyQuS17hClOzsv8Euy3FDLjWBYKM1bTVCLFQgYBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1afd635524b3e00dff2255512604cd094f1679ee0e4d75da56cf40ba07ac7d31","last_reissued_at":"2026-05-20T00:05:12.467674Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:12.467674Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.18035","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":"2026-05-20T00:05:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b7KwZ4wxXbJF7pGl7Y9ZEPIuxj14AgHcr2egUJgFrH5d+Pqs8NTbah/a2RxCHXrlaCVWnvuvxwN0ChdIsbmwCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:59:34.471890Z"},"content_sha256":"5647c723b4c90291da3045d35b07b5cdcf301ad1c8cabc065528765863deb201","schema_version":"1.0","event_id":"sha256:5647c723b4c90291da3045d35b07b5cdcf301ad1c8cabc065528765863deb201"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DL6WGVJEWPQA37ZCKVISMBGNBF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"2) ((1) Harbin Institute of Technology, (2) Mohamed bin Zayed University of Artificial Intelligence, 3), (3) Jilin University), Bin Gu (2, Huan Xiong (1, William de Vazelhes (2), Xinzhe Yuan (1)","submitted_at":"2026-05-18T08:24:18Z","abstract_excerpt":"Hard-thresholding is an important type of algorithm in machine learning that is used to solve $\\ell_0$ constrained optimization problems. However, the true gradient of the objective function can be difficult to access in certain scenarios, which normally can be approximated by zeroth-order (ZO) methods. The SZOHT algorithm is the only algorithm tackling $\\ell_0$ sparsity constraints with ZO gradients so far. Unfortunately, SZOHT has a notable limitation on the number of random directions % in ZO gradients due to the inherent conflict between the deviation of ZO gradients and the expansivity of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18035","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/2605.18035/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.503761Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"02a6a3c80a4017df4a86165f4ee909601f018d7ccf3c360dfce6a97a63adead0"},"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":"2026-05-20T00:05:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cbBPHYfduOeH5CUAX7IttSADdFBZ1D8QwHq2eCAWY71L8DjzgWBt2ASZdJX40BM8ADkrhl1X1JVWQpiojyqCAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:59:34.472727Z"},"content_sha256":"f4877babac4965a76f5f457e7e791a248ae1d662dd2c30b7f1405847ad8bc046","schema_version":"1.0","event_id":"sha256:f4877babac4965a76f5f457e7e791a248ae1d662dd2c30b7f1405847ad8bc046"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/bundle.json","state_url":"https://pith.science/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/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":"2026-05-25T17:59:34Z","links":{"resolver":"https://pith.science/pith/DL6WGVJEWPQA37ZCKVISMBGNBF","bundle":"https://pith.science/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/bundle.json","state":"https://pith.science/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DL6WGVJEWPQA37ZCKVISMBGNBF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DL6WGVJEWPQA37ZCKVISMBGNBF","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":"1ab5984850f2535c3b170e9bc2a953f59874f202033411f9b0704583745bd1b2","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T08:24:18Z","title_canon_sha256":"aeea752e6243baf20fd5c6a38f518a5bceb18cb9ec78d6570ff4200ee2a1314c"},"schema_version":"1.0","source":{"id":"2605.18035","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18035","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18035v1","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18035","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_12","alias_value":"DL6WGVJEWPQA","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_16","alias_value":"DL6WGVJEWPQA37ZC","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_8","alias_value":"DL6WGVJE","created_at":"2026-05-20T00:05:12Z"}],"graph_snapshots":[{"event_id":"sha256:f4877babac4965a76f5f457e7e791a248ae1d662dd2c30b7f1405847ad8bc046","target":"graph","created_at":"2026-05-20T00:05:12Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.503761Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.18035/integrity.json","findings":[],"snapshot_sha256":"02a6a3c80a4017df4a86165f4ee909601f018d7ccf3c360dfce6a97a63adead0","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Hard-thresholding is an important type of algorithm in machine learning that is used to solve $\\ell_0$ constrained optimization problems. However, the true gradient of the objective function can be difficult to access in certain scenarios, which normally can be approximated by zeroth-order (ZO) methods. The SZOHT algorithm is the only algorithm tackling $\\ell_0$ sparsity constraints with ZO gradients so far. Unfortunately, SZOHT has a notable limitation on the number of random directions % in ZO gradients due to the inherent conflict between the deviation of ZO gradients and the expansivity of","authors_text":"2) ((1) Harbin Institute of Technology, (2) Mohamed bin Zayed University of Artificial Intelligence, 3), (3) Jilin University), Bin Gu (2, Huan Xiong (1, William de Vazelhes (2), Xinzhe Yuan (1)","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T08:24:18Z","title":"New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18035","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":"sha256:5647c723b4c90291da3045d35b07b5cdcf301ad1c8cabc065528765863deb201","target":"record","created_at":"2026-05-20T00:05:12Z","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":"1ab5984850f2535c3b170e9bc2a953f59874f202033411f9b0704583745bd1b2","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T08:24:18Z","title_canon_sha256":"aeea752e6243baf20fd5c6a38f518a5bceb18cb9ec78d6570ff4200ee2a1314c"},"schema_version":"1.0","source":{"id":"2605.18035","kind":"arxiv","version":1}},"canonical_sha256":"1afd635524b3e00dff2255512604cd094f1679ee0e4d75da56cf40ba07ac7d31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1afd635524b3e00dff2255512604cd094f1679ee0e4d75da56cf40ba07ac7d31","first_computed_at":"2026-05-20T00:05:12.467674Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:12.467674Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UjDkSC6R0GNxfKnDIwhLPAaVTc2Hp4IEHIE99esnYb5nXdxyQuS17hClOzsv8Euy3FDLjWBYKM1bTVCLFQgYBw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:12.468487Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.18035","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5647c723b4c90291da3045d35b07b5cdcf301ad1c8cabc065528765863deb201","sha256:f4877babac4965a76f5f457e7e791a248ae1d662dd2c30b7f1405847ad8bc046"],"state_sha256":"5d97233bcd1c65fc038a599487e9a3593665097894ca8a700c06f23d46eaa765"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W+4m6rcodEb8YzAOgL207JkTuNHC2ygkDPuuPNwMzXqQT0ZHThx+A6piPg04zwZzxYyyC30ZNgWq8lNCPxA8CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T17:59:34.476832Z","bundle_sha256":"6405ba3c99b407981ba8cc3ab342dfcb4d18d319ce75241ee706016d2af8b29e"}}