{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DNWM5HCD7QIQQ75242NMXEOBOS","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":"2662a8425cb49ffd9f328bcaa4942df2d874fd63bdd27176392e142e9e417328","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2023-04-10T05:52:38Z","title_canon_sha256":"e25164235e73829ab6260d54ef64dc4cd1d70ff5f0905a6d5175a298677fecd3"},"schema_version":"1.0","source":{"id":"2304.04397","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04397","created_at":"2026-07-05T05:59:25Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04397v1","created_at":"2026-07-05T05:59:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04397","created_at":"2026-07-05T05:59:25Z"},{"alias_kind":"pith_short_12","alias_value":"DNWM5HCD7QIQ","created_at":"2026-07-05T05:59:25Z"},{"alias_kind":"pith_short_16","alias_value":"DNWM5HCD7QIQQ752","created_at":"2026-07-05T05:59:25Z"},{"alias_kind":"pith_short_8","alias_value":"DNWM5HCD","created_at":"2026-07-05T05:59:25Z"}],"graph_snapshots":[{"event_id":"sha256:8580eec878b705a193f4fa82a87ab7cc2f704c5a6f1e39cd354a8dd68afca038","target":"graph","created_at":"2026-07-05T05:59:25Z","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/2304.04397/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have shown their power in different areas. Attention computation, as an important subroutine of LLMs, has also attracted interests in theory. Recently the static computation and dynamic maintenance of attention matrix has been studied by [Alman and Song 2023] and [Brand, Song and Zhou 2023] from both algorithmic perspective and hardness perspective. In this work, we consider the sparsification of the attention problem. We make one simplification which is the logit matrix is symmetric. Let $n$ denote the length of sentence, let $d$ denote the embedding dimension. Gi","authors_text":"Sridhar Mahadevan, Yichuan Deng, Zhao Song","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2023-04-10T05:52:38Z","title":"Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04397","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:b12d3d9068253ecf3441977a2bddd9d5ca2eb2f0ca11b7df39cc85c0fb46a38d","target":"record","created_at":"2026-07-05T05:59:25Z","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":"2662a8425cb49ffd9f328bcaa4942df2d874fd63bdd27176392e142e9e417328","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.DS","submitted_at":"2023-04-10T05:52:38Z","title_canon_sha256":"e25164235e73829ab6260d54ef64dc4cd1d70ff5f0905a6d5175a298677fecd3"},"schema_version":"1.0","source":{"id":"2304.04397","kind":"arxiv","version":1}},"canonical_sha256":"1b6cce9c43fc11087fbae69acb91c1748f44758916e3b02874bbb93aa5646ff0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b6cce9c43fc11087fbae69acb91c1748f44758916e3b02874bbb93aa5646ff0","first_computed_at":"2026-07-05T05:59:25.783248Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:25.783248Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5fVt6j0Az/wcA5RMlTPRxuMGOzhDctKcE8fPPeePhlKmuGgICs9/KV3VqwLMKysfNTlh0SY5NuKO8iw421n2Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:25.783668Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.04397","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b12d3d9068253ecf3441977a2bddd9d5ca2eb2f0ca11b7df39cc85c0fb46a38d","sha256:8580eec878b705a193f4fa82a87ab7cc2f704c5a6f1e39cd354a8dd68afca038"],"state_sha256":"d9173d4fb60b63e191d9f31b4e615140c93d62818a29d17a949123642e343157"}