{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5CB7ZRWRC44TCXDYSJ7NJMJPKH","short_pith_number":"pith:5CB7ZRWR","canonical_record":{"source":{"id":"2505.24179","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-30T03:40:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5a0b00a30cb5bd7d089faecd1b81c0ea93cf9cb91cfc8de022baf45f68e197d5","abstract_canon_sha256":"a3688c1b4372ff19d2dca2d990d60ba181dfeba22ab558d1ea64d4d26fcc5304"},"schema_version":"1.0"},"canonical_sha256":"e883fcc6d11739315c78927ed4b12f51c975ec34129102766ae8f67cb3d28807","source":{"kind":"arxiv","id":"2505.24179","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.24179","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"arxiv_version","alias_value":"2505.24179v1","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.24179","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_12","alias_value":"5CB7ZRWRC44T","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_16","alias_value":"5CB7ZRWRC44TCXDY","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_8","alias_value":"5CB7ZRWR","created_at":"2026-07-05T11:12:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5CB7ZRWRC44TCXDYSJ7NJMJPKH","target":"record","payload":{"canonical_record":{"source":{"id":"2505.24179","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-30T03:40:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5a0b00a30cb5bd7d089faecd1b81c0ea93cf9cb91cfc8de022baf45f68e197d5","abstract_canon_sha256":"a3688c1b4372ff19d2dca2d990d60ba181dfeba22ab558d1ea64d4d26fcc5304"},"schema_version":"1.0"},"canonical_sha256":"e883fcc6d11739315c78927ed4b12f51c975ec34129102766ae8f67cb3d28807","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:12:43.568433Z","signature_b64":"TCAjxzDYR5pA0HrgXBp4ZmxkKno2hMMUWhYnfIuQzlgzs0dw35zdgMu1P/6jVg7zzAOqLC3jHwJ0Fawp03ulDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e883fcc6d11739315c78927ed4b12f51c975ec34129102766ae8f67cb3d28807","last_reissued_at":"2026-07-05T11:12:43.567866Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:12:43.567866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.24179","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":"2026-07-05T11:12:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wYJclHiv5g45JdevoZ/l+bW6KSm6oTs87bNHdqRNzjlHrjipacIkvHnjoXOh1oZ82EstczKGNyeJu1at6YApAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:54:31.171148Z"},"content_sha256":"ca16e0db75d3b83047a2016d24a666a40a9d68e07be966dae43032222e8b8d0f","schema_version":"1.0","event_id":"sha256:ca16e0db75d3b83047a2016d24a666a40a9d68e07be966dae43032222e8b8d0f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5CB7ZRWRC44TCXDYSJ7NJMJPKH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Bin Cui, Fangcheng Fu, Hailin Zhang, Xiaodong Ji","submitted_at":"2025-05-30T03:40:24Z","abstract_excerpt":"Many advanced Large Language Model (LLM) applications require long-context processing, but the self-attention module becomes a bottleneck during the prefilling stage of inference due to its quadratic time complexity with respect to sequence length. Existing sparse attention methods accelerate attention computation by skipping less significant regions of the attention map. However, these approaches typically perform coarse-grained inspection of the attention map, rendering considerable loss in model accuracy. In this paper, we propose SALE, a fine-grained sparse attention method that accelerate"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.24179","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/2505.24179/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":"2026-07-05T11:12:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xIn5psVli5o5O5hwS8rSK4+P2I1Igk3n2v8zFHbLaqzGNMp8+CAjMGp392bFzdH0eZBrbQvCaSD+nepEnLopBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:54:31.171833Z"},"content_sha256":"75bb0d9788bdacc79aaaa4298300a6ae8512d28c50b3cb4fa255057af5022f6d","schema_version":"1.0","event_id":"sha256:75bb0d9788bdacc79aaaa4298300a6ae8512d28c50b3cb4fa255057af5022f6d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/bundle.json","state_url":"https://pith.science/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/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":"2026-08-07T19:54:31Z","links":{"resolver":"https://pith.science/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH","bundle":"https://pith.science/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/bundle.json","state":"https://pith.science/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5CB7ZRWRC44TCXDYSJ7NJMJPKH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5CB7ZRWRC44TCXDYSJ7NJMJPKH","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":"a3688c1b4372ff19d2dca2d990d60ba181dfeba22ab558d1ea64d4d26fcc5304","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-30T03:40:24Z","title_canon_sha256":"5a0b00a30cb5bd7d089faecd1b81c0ea93cf9cb91cfc8de022baf45f68e197d5"},"schema_version":"1.0","source":{"id":"2505.24179","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.24179","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"arxiv_version","alias_value":"2505.24179v1","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.24179","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_12","alias_value":"5CB7ZRWRC44T","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_16","alias_value":"5CB7ZRWRC44TCXDY","created_at":"2026-07-05T11:12:43Z"},{"alias_kind":"pith_short_8","alias_value":"5CB7ZRWR","created_at":"2026-07-05T11:12:43Z"}],"graph_snapshots":[{"event_id":"sha256:75bb0d9788bdacc79aaaa4298300a6ae8512d28c50b3cb4fa255057af5022f6d","target":"graph","created_at":"2026-07-05T11:12:43Z","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/2505.24179/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many advanced Large Language Model (LLM) applications require long-context processing, but the self-attention module becomes a bottleneck during the prefilling stage of inference due to its quadratic time complexity with respect to sequence length. Existing sparse attention methods accelerate attention computation by skipping less significant regions of the attention map. However, these approaches typically perform coarse-grained inspection of the attention map, rendering considerable loss in model accuracy. In this paper, we propose SALE, a fine-grained sparse attention method that accelerate","authors_text":"Bin Cui, Fangcheng Fu, Hailin Zhang, Xiaodong Ji","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-30T03:40:24Z","title":"SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.24179","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:ca16e0db75d3b83047a2016d24a666a40a9d68e07be966dae43032222e8b8d0f","target":"record","created_at":"2026-07-05T11:12:43Z","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":"a3688c1b4372ff19d2dca2d990d60ba181dfeba22ab558d1ea64d4d26fcc5304","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-30T03:40:24Z","title_canon_sha256":"5a0b00a30cb5bd7d089faecd1b81c0ea93cf9cb91cfc8de022baf45f68e197d5"},"schema_version":"1.0","source":{"id":"2505.24179","kind":"arxiv","version":1}},"canonical_sha256":"e883fcc6d11739315c78927ed4b12f51c975ec34129102766ae8f67cb3d28807","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e883fcc6d11739315c78927ed4b12f51c975ec34129102766ae8f67cb3d28807","first_computed_at":"2026-07-05T11:12:43.567866Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:12:43.567866Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TCAjxzDYR5pA0HrgXBp4ZmxkKno2hMMUWhYnfIuQzlgzs0dw35zdgMu1P/6jVg7zzAOqLC3jHwJ0Fawp03ulDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:12:43.568433Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.24179","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca16e0db75d3b83047a2016d24a666a40a9d68e07be966dae43032222e8b8d0f","sha256:75bb0d9788bdacc79aaaa4298300a6ae8512d28c50b3cb4fa255057af5022f6d"],"state_sha256":"fbca5591653bc36a2a55a751d9c6479b0e318f89cdea5a33f37b87fa79ea4f46"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ENfh+yPdORmvZUwx72xpCtmM59iKVDljKMyqV/JK8J88ckjC70YSWZhd4BZJxQTbR+3FzhX7ezQ4kTCpWFqACg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T19:54:31.177479Z","bundle_sha256":"07459a6ae57f0db1efbf2dd189358e0ada6d88ef0d702cbede0dc5c82f917b97"}}