{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3FNF7K5WGPMHI7IHQI5I6RFJED","short_pith_number":"pith:3FNF7K5W","canonical_record":{"source":{"id":"2506.11498","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:49:53Z","cross_cats_sorted":[],"title_canon_sha256":"422f5444e66a974701515018ade4e92acc548d6708ca30fbe1d12b47223e2e93","abstract_canon_sha256":"eca0785c2d76c2fb76e93d0556ea14e4b6f386a9bd2ab553bd3be998542bf6d3"},"schema_version":"1.0"},"canonical_sha256":"d95a5fabb633d8747d07823a8f44a920ecc9454e9832dba083e6546994f3b386","source":{"kind":"arxiv","id":"2506.11498","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.11498","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"arxiv_version","alias_value":"2506.11498v1","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11498","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_12","alias_value":"3FNF7K5WGPMH","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_16","alias_value":"3FNF7K5WGPMHI7IH","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_8","alias_value":"3FNF7K5W","created_at":"2026-07-05T11:21:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3FNF7K5WGPMHI7IHQI5I6RFJED","target":"record","payload":{"canonical_record":{"source":{"id":"2506.11498","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:49:53Z","cross_cats_sorted":[],"title_canon_sha256":"422f5444e66a974701515018ade4e92acc548d6708ca30fbe1d12b47223e2e93","abstract_canon_sha256":"eca0785c2d76c2fb76e93d0556ea14e4b6f386a9bd2ab553bd3be998542bf6d3"},"schema_version":"1.0"},"canonical_sha256":"d95a5fabb633d8747d07823a8f44a920ecc9454e9832dba083e6546994f3b386","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:21:05.650082Z","signature_b64":"Z/RD+udzzZapMvzCFixqmbUdwVhKjwCDoEcsKpALU1UpTihh8N2gNiyIkEHYla+szDJITwC5+67aNGIgsFlwAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d95a5fabb633d8747d07823a8f44a920ecc9454e9832dba083e6546994f3b386","last_reissued_at":"2026-07-05T11:21:05.649611Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:21:05.649611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.11498","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":"2026-07-05T11:21:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OJxMFX7dFHXvEVwYw6K6W+QIm2FZGGdH9CparrPzi8mwY5Zs68LS4hyHVb/zWvCYEmlCa0MhAO1KTyr2QV6bAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:45:32.569362Z"},"content_sha256":"59ed68ebced95c5de682c0b0323e4440f5f145587b48d4fa2e024bc1fc56d925","schema_version":"1.0","event_id":"sha256:59ed68ebced95c5de682c0b0323e4440f5f145587b48d4fa2e024bc1fc56d925"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3FNF7K5WGPMHI7IHQI5I6RFJED","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lag-Relative Sparse Attention In Long Context Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Huaijun Li, Jinlong Li, Mandi Liu, Manlai Liang, Wanyi Huang","submitted_at":"2025-06-13T06:49:53Z","abstract_excerpt":"Large Language Models (LLMs) have made significant strides in natural language processing and generation, yet their ability to handle long-context input remains constrained by the quadratic complexity of attention computation and linear-increasing key-value memory footprint. To reduce computational costs and memory, key-value cache compression techniques are commonly applied at inference time, but this often leads to severe performance degradation, as models are not trained to handle compressed context. Although there are more sophisticated compression methods, they are typically unsuitable fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11498","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/2506.11498/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":"2026-07-05T11:21:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"acWgXQ7MEkRrn5jbMMA25FDLZXl/ylTA4kjkUszxgOIxpcsXkF578m1jFO8fMk+he565Sepzt2rpWZc6iMGxCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:45:32.569994Z"},"content_sha256":"5e4094ce64d9acf30fe1be3b61b7fdc01e79f2ce45875a401562511c3b3a7e9e","schema_version":"1.0","event_id":"sha256:5e4094ce64d9acf30fe1be3b61b7fdc01e79f2ce45875a401562511c3b3a7e9e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/bundle.json","state_url":"https://pith.science/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/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":"2026-08-10T08:45:32Z","links":{"resolver":"https://pith.science/pith/3FNF7K5WGPMHI7IHQI5I6RFJED","bundle":"https://pith.science/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/bundle.json","state":"https://pith.science/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3FNF7K5WGPMHI7IHQI5I6RFJED/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3FNF7K5WGPMHI7IHQI5I6RFJED","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":"eca0785c2d76c2fb76e93d0556ea14e4b6f386a9bd2ab553bd3be998542bf6d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:49:53Z","title_canon_sha256":"422f5444e66a974701515018ade4e92acc548d6708ca30fbe1d12b47223e2e93"},"schema_version":"1.0","source":{"id":"2506.11498","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.11498","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"arxiv_version","alias_value":"2506.11498v1","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11498","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_12","alias_value":"3FNF7K5WGPMH","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_16","alias_value":"3FNF7K5WGPMHI7IH","created_at":"2026-07-05T11:21:05Z"},{"alias_kind":"pith_short_8","alias_value":"3FNF7K5W","created_at":"2026-07-05T11:21:05Z"}],"graph_snapshots":[{"event_id":"sha256:5e4094ce64d9acf30fe1be3b61b7fdc01e79f2ce45875a401562511c3b3a7e9e","target":"graph","created_at":"2026-07-05T11:21:05Z","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/2506.11498/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have made significant strides in natural language processing and generation, yet their ability to handle long-context input remains constrained by the quadratic complexity of attention computation and linear-increasing key-value memory footprint. To reduce computational costs and memory, key-value cache compression techniques are commonly applied at inference time, but this often leads to severe performance degradation, as models are not trained to handle compressed context. Although there are more sophisticated compression methods, they are typically unsuitable fo","authors_text":"Huaijun Li, Jinlong Li, Mandi Liu, Manlai Liang, Wanyi Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:49:53Z","title":"Lag-Relative Sparse Attention In Long Context Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11498","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":"sha256:59ed68ebced95c5de682c0b0323e4440f5f145587b48d4fa2e024bc1fc56d925","target":"record","created_at":"2026-07-05T11:21:05Z","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":"eca0785c2d76c2fb76e93d0556ea14e4b6f386a9bd2ab553bd3be998542bf6d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:49:53Z","title_canon_sha256":"422f5444e66a974701515018ade4e92acc548d6708ca30fbe1d12b47223e2e93"},"schema_version":"1.0","source":{"id":"2506.11498","kind":"arxiv","version":1}},"canonical_sha256":"d95a5fabb633d8747d07823a8f44a920ecc9454e9832dba083e6546994f3b386","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d95a5fabb633d8747d07823a8f44a920ecc9454e9832dba083e6546994f3b386","first_computed_at":"2026-07-05T11:21:05.649611Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:05.649611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z/RD+udzzZapMvzCFixqmbUdwVhKjwCDoEcsKpALU1UpTihh8N2gNiyIkEHYla+szDJITwC5+67aNGIgsFlwAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:05.650082Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.11498","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59ed68ebced95c5de682c0b0323e4440f5f145587b48d4fa2e024bc1fc56d925","sha256:5e4094ce64d9acf30fe1be3b61b7fdc01e79f2ce45875a401562511c3b3a7e9e"],"state_sha256":"640954eb3e398da3557ec42156ed5f2e6379a6ce636b64115d0ee419bf0108e7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5oPQ1MCLul5Z6g+SIDoNSEc5cADkWmPb6ueIupBmcJiMEWY+unKenI6b7dR4j+RcOnRCaX2Xjon7zsdX1JySBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T08:45:32.583743Z","bundle_sha256":"93b3fe64bbdf2e128697be694915accce86b469ddbccd6cbd349ec24e5a6a44f"}}