{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5SUGOE43MTTYBBGS5EQXGH73JL","short_pith_number":"pith:5SUGOE43","canonical_record":{"source":{"id":"2510.24606","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-28T16:34:18Z","cross_cats_sorted":[],"title_canon_sha256":"644cb592616be24871b262237c3d7ec1ea99ad1f52efdf82645f0531f1f66d23","abstract_canon_sha256":"0bfc70e870811e15f5135cd5992f44920a55ad1d2e02ff70df2e7567798656c8"},"schema_version":"1.0"},"canonical_sha256":"eca867139b64e78084d2e921731ffb4af31058bca1f674d3164da7264cfa142d","source":{"kind":"arxiv","id":"2510.24606","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.24606","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"arxiv_version","alias_value":"2510.24606v2","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.24606","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_12","alias_value":"5SUGOE43MTTY","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_16","alias_value":"5SUGOE43MTTYBBGS","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_8","alias_value":"5SUGOE43","created_at":"2026-05-29T01:04:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5SUGOE43MTTYBBGS5EQXGH73JL","target":"record","payload":{"canonical_record":{"source":{"id":"2510.24606","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-28T16:34:18Z","cross_cats_sorted":[],"title_canon_sha256":"644cb592616be24871b262237c3d7ec1ea99ad1f52efdf82645f0531f1f66d23","abstract_canon_sha256":"0bfc70e870811e15f5135cd5992f44920a55ad1d2e02ff70df2e7567798656c8"},"schema_version":"1.0"},"canonical_sha256":"eca867139b64e78084d2e921731ffb4af31058bca1f674d3164da7264cfa142d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:04:57.468014Z","signature_b64":"Au6sUpbHcCJzWPS5lYBHEjMGR0fZYuuOz5teTuLOuefuyQcjgFN5GboP8nZ0pbACmUNYHwUwpdqYSVP4FBl2Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eca867139b64e78084d2e921731ffb4af31058bca1f674d3164da7264cfa142d","last_reissued_at":"2026-05-29T01:04:57.467473Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:04:57.467473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2510.24606","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-29T01:04:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BbXj2o4TJj/oq8Fiqd5xv/BgxkNyQDD0rS1rfFkdZiQUL3OG782NnqhJgb57fBs8SA73DAZDrCRAXVg47+NCAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T04:42:43.470367Z"},"content_sha256":"d7f0fc531c6f65ec9b40d45c65ab35527bcad6fe1304d065fdaca0f52f455d2b","schema_version":"1.0","event_id":"sha256:d7f0fc531c6f65ec9b40d45c65ab35527bcad6fe1304d065fdaca0f52f455d2b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5SUGOE43MTTYBBGS5EQXGH73JL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Faramarz Fekri, Joe Zou, Siheng Xiong, Yae Jee Cho","submitted_at":"2025-10-28T16:34:18Z","abstract_excerpt":"The quadratic cost of attention limits the scalability of long-context LLMs, especially under limited hardware memory budgets. While attention is often sparse, existing static sparse methods cannot adapt to task- or input-dependent variations, and recent dynamic approaches rely on predefined templates or heuristics that may sacrifice generality. We propose Dynamic Hierarchical Sparse Attention (DHSA), a data-driven framework that predicts attention sparsity online while keeping the LLM backbone frozen. DHSA performs hierarchical routing by estimating importance at the chunk level and propagati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.24606","kind":"arxiv","version":2},"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/2510.24606/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":"2026-05-29T01:04:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gtrvMPfpzEYPVzVkP8GdP0A0jyrbmdtUkVMCkv1IfK7q0HfFP1zgx3suSC2wW3vqpgp5XvDyrF4zN+NYdJTFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T04:42:43.470763Z"},"content_sha256":"fae40be290b6f50188c49b7b9c4112c2d916cccc291653997635e34fe39c7320","schema_version":"1.0","event_id":"sha256:fae40be290b6f50188c49b7b9c4112c2d916cccc291653997635e34fe39c7320"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5SUGOE43MTTYBBGS5EQXGH73JL/bundle.json","state_url":"https://pith.science/pith/5SUGOE43MTTYBBGS5EQXGH73JL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5SUGOE43MTTYBBGS5EQXGH73JL/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":"2026-05-31T04:42:43Z","links":{"resolver":"https://pith.science/pith/5SUGOE43MTTYBBGS5EQXGH73JL","bundle":"https://pith.science/pith/5SUGOE43MTTYBBGS5EQXGH73JL/bundle.json","state":"https://pith.science/pith/5SUGOE43MTTYBBGS5EQXGH73JL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5SUGOE43MTTYBBGS5EQXGH73JL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5SUGOE43MTTYBBGS5EQXGH73JL","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":"0bfc70e870811e15f5135cd5992f44920a55ad1d2e02ff70df2e7567798656c8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-28T16:34:18Z","title_canon_sha256":"644cb592616be24871b262237c3d7ec1ea99ad1f52efdf82645f0531f1f66d23"},"schema_version":"1.0","source":{"id":"2510.24606","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2510.24606","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"arxiv_version","alias_value":"2510.24606v2","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2510.24606","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_12","alias_value":"5SUGOE43MTTY","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_16","alias_value":"5SUGOE43MTTYBBGS","created_at":"2026-05-29T01:04:57Z"},{"alias_kind":"pith_short_8","alias_value":"5SUGOE43","created_at":"2026-05-29T01:04:57Z"}],"graph_snapshots":[{"event_id":"sha256:fae40be290b6f50188c49b7b9c4112c2d916cccc291653997635e34fe39c7320","target":"graph","created_at":"2026-05-29T01:04:57Z","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/2510.24606/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The quadratic cost of attention limits the scalability of long-context LLMs, especially under limited hardware memory budgets. While attention is often sparse, existing static sparse methods cannot adapt to task- or input-dependent variations, and recent dynamic approaches rely on predefined templates or heuristics that may sacrifice generality. We propose Dynamic Hierarchical Sparse Attention (DHSA), a data-driven framework that predicts attention sparsity online while keeping the LLM backbone frozen. DHSA performs hierarchical routing by estimating importance at the chunk level and propagati","authors_text":"Faramarz Fekri, Joe Zou, Siheng Xiong, Yae Jee Cho","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-28T16:34:18Z","title":"Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2510.24606","kind":"arxiv","version":2},"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:d7f0fc531c6f65ec9b40d45c65ab35527bcad6fe1304d065fdaca0f52f455d2b","target":"record","created_at":"2026-05-29T01:04:57Z","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":"0bfc70e870811e15f5135cd5992f44920a55ad1d2e02ff70df2e7567798656c8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-10-28T16:34:18Z","title_canon_sha256":"644cb592616be24871b262237c3d7ec1ea99ad1f52efdf82645f0531f1f66d23"},"schema_version":"1.0","source":{"id":"2510.24606","kind":"arxiv","version":2}},"canonical_sha256":"eca867139b64e78084d2e921731ffb4af31058bca1f674d3164da7264cfa142d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eca867139b64e78084d2e921731ffb4af31058bca1f674d3164da7264cfa142d","first_computed_at":"2026-05-29T01:04:57.467473Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:04:57.467473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Au6sUpbHcCJzWPS5lYBHEjMGR0fZYuuOz5teTuLOuefuyQcjgFN5GboP8nZ0pbACmUNYHwUwpdqYSVP4FBl2Dg==","signature_status":"signed_v1","signed_at":"2026-05-29T01:04:57.468014Z","signed_message":"canonical_sha256_bytes"},"source_id":"2510.24606","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7f0fc531c6f65ec9b40d45c65ab35527bcad6fe1304d065fdaca0f52f455d2b","sha256:fae40be290b6f50188c49b7b9c4112c2d916cccc291653997635e34fe39c7320"],"state_sha256":"d6537188b90297f5b9aefec09bac5add807635e91248490757724f4037e8c6f1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HrcnTvpryJEXP2pjMCOCvn1iIAaKYy5pgGMxqDepX0VRxredKUKrxit5iooX8tNPkXrGPqtBku2OaMHfweymDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T04:42:43.473475Z","bundle_sha256":"68a67f23962dec516e9a8b22f8953bbb34e845ecdbd57876dc529fb0b05e396a"}}