{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LTYDHCQP44HDTJGTYZGXF2CPQ4","short_pith_number":"pith:LTYDHCQP","canonical_record":{"source":{"id":"2509.10406","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T16:58:17Z","cross_cats_sorted":[],"title_canon_sha256":"bcafed616852da6d7360fdb40c8078f40f0c7e9d484be5c03dc00a6fc807c977","abstract_canon_sha256":"f2d3063b0a5f329b6a8917d936528b4bca2066cb195dbcdcd9c3acbd502bb5ac"},"schema_version":"1.0"},"canonical_sha256":"5cf0338a0fe70e39a4d3c64d72e84f872c2e58d1cfcbd12f12662095bea7568a","source":{"kind":"arxiv","id":"2509.10406","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.10406","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"arxiv_version","alias_value":"2509.10406v4","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.10406","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_12","alias_value":"LTYDHCQP44HD","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_16","alias_value":"LTYDHCQP44HDTJGT","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_8","alias_value":"LTYDHCQP","created_at":"2026-07-01T01:17:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LTYDHCQP44HDTJGTYZGXF2CPQ4","target":"record","payload":{"canonical_record":{"source":{"id":"2509.10406","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T16:58:17Z","cross_cats_sorted":[],"title_canon_sha256":"bcafed616852da6d7360fdb40c8078f40f0c7e9d484be5c03dc00a6fc807c977","abstract_canon_sha256":"f2d3063b0a5f329b6a8917d936528b4bca2066cb195dbcdcd9c3acbd502bb5ac"},"schema_version":"1.0"},"canonical_sha256":"5cf0338a0fe70e39a4d3c64d72e84f872c2e58d1cfcbd12f12662095bea7568a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-01T01:17:41.358954Z","signature_b64":"lACleOOKqzTwOC+3h1sIN8zC2pEKgzciKr+vRj0Paj7rzizjtoutNq33LvoekjKfutsd523wW2PrVqfm/I69Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5cf0338a0fe70e39a4d3c64d72e84f872c2e58d1cfcbd12f12662095bea7568a","last_reissued_at":"2026-07-01T01:17:41.358451Z","signature_status":"signed_v1","first_computed_at":"2026-07-01T01:17:41.358451Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.10406","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-01T01:17:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/sSJn0RpfLjxwZBfOtbwZOuCyDt3P0xMA9rLjTqVArZAbZ64egE91We1bP07EfDlR1lxNnoZf2wcQSsRQKmaAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T21:11:48.616734Z"},"content_sha256":"c14d5e00ce9917f16b7f43f6651ef15ffab6abd26c8b87df368ef945257803b4","schema_version":"1.0","event_id":"sha256:c14d5e00ce9917f16b7f43f6651ef15ffab6abd26c8b87df368ef945257803b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LTYDHCQP44HDTJGTYZGXF2CPQ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kristian Kersting, Rupert Mitchell","submitted_at":"2025-09-12T16:58:17Z","abstract_excerpt":"Pretraining transformers on long sequences (entire code repositories, collections of related documents) is bottlenecked by quadratic attention costs. We present Multipole Semantic Attention (MuSe), which accelerates 64k-context pretraining by 36% while matching baseline loss, requiring no architectural changes. MuSe clusters queries and keys separately in representation space. This yields query-specific summaries that substantially outperform spatial blocking at matched sparsity, while also enabling drop-in compatibility with existing pretrained models; we validate on Llama 3.1-8B and 3.2-1B w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.10406","kind":"arxiv","version":4},"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/2509.10406/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":"2026-07-01T01:17:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vnvjq7YNasmDAmnFfPVMOT/dPfnaZw+C73xrDtl9cidoeI2Xf3p5uJde1gud1233iu5JdkAFGU4WsSUAqw9ODQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T21:11:48.617257Z"},"content_sha256":"778b2ecbf733f0f64050b655a88903f300803bb0900b36f6355bd4a0713e834c","schema_version":"1.0","event_id":"sha256:778b2ecbf733f0f64050b655a88903f300803bb0900b36f6355bd4a0713e834c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/bundle.json","state_url":"https://pith.science/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/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":"2026-08-18T21:11:48Z","links":{"resolver":"https://pith.science/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4","bundle":"https://pith.science/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/bundle.json","state":"https://pith.science/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LTYDHCQP44HDTJGTYZGXF2CPQ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LTYDHCQP44HDTJGTYZGXF2CPQ4","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":"f2d3063b0a5f329b6a8917d936528b4bca2066cb195dbcdcd9c3acbd502bb5ac","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T16:58:17Z","title_canon_sha256":"bcafed616852da6d7360fdb40c8078f40f0c7e9d484be5c03dc00a6fc807c977"},"schema_version":"1.0","source":{"id":"2509.10406","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.10406","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"arxiv_version","alias_value":"2509.10406v4","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.10406","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_12","alias_value":"LTYDHCQP44HD","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_16","alias_value":"LTYDHCQP44HDTJGT","created_at":"2026-07-01T01:17:41Z"},{"alias_kind":"pith_short_8","alias_value":"LTYDHCQP","created_at":"2026-07-01T01:17:41Z"}],"graph_snapshots":[{"event_id":"sha256:778b2ecbf733f0f64050b655a88903f300803bb0900b36f6355bd4a0713e834c","target":"graph","created_at":"2026-07-01T01:17:41Z","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/2509.10406/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Pretraining transformers on long sequences (entire code repositories, collections of related documents) is bottlenecked by quadratic attention costs. We present Multipole Semantic Attention (MuSe), which accelerates 64k-context pretraining by 36% while matching baseline loss, requiring no architectural changes. MuSe clusters queries and keys separately in representation space. This yields query-specific summaries that substantially outperform spatial blocking at matched sparsity, while also enabling drop-in compatibility with existing pretrained models; we validate on Llama 3.1-8B and 3.2-1B w","authors_text":"Kristian Kersting, Rupert Mitchell","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T16:58:17Z","title":"Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.10406","kind":"arxiv","version":4},"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:c14d5e00ce9917f16b7f43f6651ef15ffab6abd26c8b87df368ef945257803b4","target":"record","created_at":"2026-07-01T01:17:41Z","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":"f2d3063b0a5f329b6a8917d936528b4bca2066cb195dbcdcd9c3acbd502bb5ac","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-12T16:58:17Z","title_canon_sha256":"bcafed616852da6d7360fdb40c8078f40f0c7e9d484be5c03dc00a6fc807c977"},"schema_version":"1.0","source":{"id":"2509.10406","kind":"arxiv","version":4}},"canonical_sha256":"5cf0338a0fe70e39a4d3c64d72e84f872c2e58d1cfcbd12f12662095bea7568a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5cf0338a0fe70e39a4d3c64d72e84f872c2e58d1cfcbd12f12662095bea7568a","first_computed_at":"2026-07-01T01:17:41.358451Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-01T01:17:41.358451Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lACleOOKqzTwOC+3h1sIN8zC2pEKgzciKr+vRj0Paj7rzizjtoutNq33LvoekjKfutsd523wW2PrVqfm/I69Bg==","signature_status":"signed_v1","signed_at":"2026-07-01T01:17:41.358954Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.10406","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c14d5e00ce9917f16b7f43f6651ef15ffab6abd26c8b87df368ef945257803b4","sha256:778b2ecbf733f0f64050b655a88903f300803bb0900b36f6355bd4a0713e834c"],"state_sha256":"7b5e87c812e83881619bf2fde043c13499882d2f9abca0beb0f935db42719f8e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"69DQ109z+7WXPIA5dmfCaiWSi5n8ImKzN9rnx9CubU5jmBaTJTd/GWwe1ik6RQt6K3nHyaTo3oy57ZhlKG2cAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T21:11:48.623233Z","bundle_sha256":"c7def1792d4375ea5d76aae87a6cc6ad89c95a0c6b8310ba218a3bde47aedff9"}}