{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:BCINDD3KPWNMO2SPSI4LPCDTVO","short_pith_number":"pith:BCINDD3K","canonical_record":{"source":{"id":"2606.10445","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-09T05:48:31Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"c74fbd709f631e52fef0a099f6cd80e684b5683b383c582c39e6386c636ded6c","abstract_canon_sha256":"2160b6b29dbb4f9765ebc75ae115f439d4eeef88beb63f3fdc870c79ace263cf"},"schema_version":"1.0"},"canonical_sha256":"0890d18f6a7d9ac76a4f9238b78873ab8b178f0323d21ebecd172ad94e8fed4b","source":{"kind":"arxiv","id":"2606.10445","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.10445","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"arxiv_version","alias_value":"2606.10445v1","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10445","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_12","alias_value":"BCINDD3KPWNM","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_16","alias_value":"BCINDD3KPWNMO2SP","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_8","alias_value":"BCINDD3K","created_at":"2026-06-10T01:10:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:BCINDD3KPWNMO2SPSI4LPCDTVO","target":"record","payload":{"canonical_record":{"source":{"id":"2606.10445","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-09T05:48:31Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"c74fbd709f631e52fef0a099f6cd80e684b5683b383c582c39e6386c636ded6c","abstract_canon_sha256":"2160b6b29dbb4f9765ebc75ae115f439d4eeef88beb63f3fdc870c79ace263cf"},"schema_version":"1.0"},"canonical_sha256":"0890d18f6a7d9ac76a4f9238b78873ab8b178f0323d21ebecd172ad94e8fed4b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:10:19.466575Z","signature_b64":"XykgRbXWsYG7dNSRv6kSff8HqcuHKwHV+44uHYP9Iz0Ka4WIPCC6rm3tsngA4HW9gdwvjTd5vUsaD2jF2h8gDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0890d18f6a7d9ac76a4f9238b78873ab8b178f0323d21ebecd172ad94e8fed4b","last_reissued_at":"2026-06-10T01:10:19.466128Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:10:19.466128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.10445","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":"2026-06-10T01:10:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mq8AaYKCGmNe26gOwgBWJx0wFHybC6YhRLSSUbV7yUs4BnJGRmMepP7alFXameYcjgxIYMYX0xC5Aj5HVk/vCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T17:24:05.923003Z"},"content_sha256":"593d6eee3ef263e0972f34cc9039106c75f206b9600c318a09eba89f57ab0aa4","schema_version":"1.0","event_id":"sha256:593d6eee3ef263e0972f34cc9039106c75f206b9600c318a09eba89f57ab0aa4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:BCINDD3KPWNMO2SPSI4LPCDTVO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SpenseGPT: Practical One-shot Pruning Enabling Sparse and Dense GEMMs for LLM Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Jaeseong Lee, Samyam Rajbhandari, Seung-won Hwang","submitted_at":"2026-06-09T05:48:31Z","abstract_excerpt":"Semi-structured 2:4 sparsity is widely supported by modern accelerators, providing up to a 2x theoretical speedup. However, its strict 50% sparsity constraint often causes non-negligible accuracy degradation under post-training pruning. Meanwhile, existing relaxed sparsity formats either require specialized compiler support or introduce runtime overheads that limit end-to-end speedup. We propose Spense, a practical hybrid sparse-dense format that splits each weight matrix into a 2:4 sparse region and a dense region. This design relaxes the effective sparsity constraint while remaining compatib"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10445","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/2606.10445/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":"2026-06-10T01:10:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L2wzJdKKMo7qjXLaX+SgtgugwicT6/KC0QMkMjDxaaIbbnwaXzH9mJ1mLhQhsTlOIHTGwa89PxC1FTNeFtAbCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T17:24:05.923385Z"},"content_sha256":"c2f70b3172a94929bea797449418e5dd71c88bda12b3478e3e152b2ded7a0516","schema_version":"1.0","event_id":"sha256:c2f70b3172a94929bea797449418e5dd71c88bda12b3478e3e152b2ded7a0516"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/bundle.json","state_url":"https://pith.science/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/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":"2026-06-28T17:24:05Z","links":{"resolver":"https://pith.science/pith/BCINDD3KPWNMO2SPSI4LPCDTVO","bundle":"https://pith.science/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/bundle.json","state":"https://pith.science/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BCINDD3KPWNMO2SPSI4LPCDTVO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BCINDD3KPWNMO2SPSI4LPCDTVO","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":"2160b6b29dbb4f9765ebc75ae115f439d4eeef88beb63f3fdc870c79ace263cf","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-09T05:48:31Z","title_canon_sha256":"c74fbd709f631e52fef0a099f6cd80e684b5683b383c582c39e6386c636ded6c"},"schema_version":"1.0","source":{"id":"2606.10445","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.10445","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"arxiv_version","alias_value":"2606.10445v1","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10445","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_12","alias_value":"BCINDD3KPWNM","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_16","alias_value":"BCINDD3KPWNMO2SP","created_at":"2026-06-10T01:10:19Z"},{"alias_kind":"pith_short_8","alias_value":"BCINDD3K","created_at":"2026-06-10T01:10:19Z"}],"graph_snapshots":[{"event_id":"sha256:c2f70b3172a94929bea797449418e5dd71c88bda12b3478e3e152b2ded7a0516","target":"graph","created_at":"2026-06-10T01:10:19Z","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/2606.10445/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semi-structured 2:4 sparsity is widely supported by modern accelerators, providing up to a 2x theoretical speedup. However, its strict 50% sparsity constraint often causes non-negligible accuracy degradation under post-training pruning. Meanwhile, existing relaxed sparsity formats either require specialized compiler support or introduce runtime overheads that limit end-to-end speedup. We propose Spense, a practical hybrid sparse-dense format that splits each weight matrix into a 2:4 sparse region and a dense region. This design relaxes the effective sparsity constraint while remaining compatib","authors_text":"Jaeseong Lee, Samyam Rajbhandari, Seung-won Hwang","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-09T05:48:31Z","title":"SpenseGPT: Practical One-shot Pruning Enabling Sparse and Dense GEMMs for LLM Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10445","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":"sha256:593d6eee3ef263e0972f34cc9039106c75f206b9600c318a09eba89f57ab0aa4","target":"record","created_at":"2026-06-10T01:10:19Z","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":"2160b6b29dbb4f9765ebc75ae115f439d4eeef88beb63f3fdc870c79ace263cf","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-09T05:48:31Z","title_canon_sha256":"c74fbd709f631e52fef0a099f6cd80e684b5683b383c582c39e6386c636ded6c"},"schema_version":"1.0","source":{"id":"2606.10445","kind":"arxiv","version":1}},"canonical_sha256":"0890d18f6a7d9ac76a4f9238b78873ab8b178f0323d21ebecd172ad94e8fed4b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0890d18f6a7d9ac76a4f9238b78873ab8b178f0323d21ebecd172ad94e8fed4b","first_computed_at":"2026-06-10T01:10:19.466128Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T01:10:19.466128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XykgRbXWsYG7dNSRv6kSff8HqcuHKwHV+44uHYP9Iz0Ka4WIPCC6rm3tsngA4HW9gdwvjTd5vUsaD2jF2h8gDw==","signature_status":"signed_v1","signed_at":"2026-06-10T01:10:19.466575Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.10445","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:593d6eee3ef263e0972f34cc9039106c75f206b9600c318a09eba89f57ab0aa4","sha256:c2f70b3172a94929bea797449418e5dd71c88bda12b3478e3e152b2ded7a0516"],"state_sha256":"97312cb1db6b9aedfa62be723e8686a7f2f426c3757d9a318468cbeca692d660"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nHXLThitDafZAjq1hXhkn+PvHgnQSty/JraOGTnpv531d2WbD9aDMRapDWvx5ngnCTkFaQQTQo0LO5j6oyeUDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T17:24:05.925247Z","bundle_sha256":"d7c73fdbe5def3845fc8685b9f4121678fbb49531ba322fd5e312c82bf2a203c"}}