{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MN2EQJXQG54WQ4L7IWMEGMWGWK","short_pith_number":"pith:MN2EQJXQ","canonical_record":{"source":{"id":"2502.03805","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-06T06:31:47Z","cross_cats_sorted":[],"title_canon_sha256":"fe576bcc2b56dad45d962889287c4e0eede3801a3d1abb489fc3b709145c35c2","abstract_canon_sha256":"7ca7d3bb9be2858a7ec7e49d0a648e7ce60ce8377b0dc377188c8a3396c2b64f"},"schema_version":"1.0"},"canonical_sha256":"63744826f0377968717f45984332c6b298819ba5d74ad8597e990b25ff4f2a92","source":{"kind":"arxiv","id":"2502.03805","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.03805","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"2502.03805v2","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03805","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"MN2EQJXQG54W","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_16","alias_value":"MN2EQJXQG54WQ4L7","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_8","alias_value":"MN2EQJXQ","created_at":"2026-05-29T01:04:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MN2EQJXQG54WQ4L7IWMEGMWGWK","target":"record","payload":{"canonical_record":{"source":{"id":"2502.03805","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-06T06:31:47Z","cross_cats_sorted":[],"title_canon_sha256":"fe576bcc2b56dad45d962889287c4e0eede3801a3d1abb489fc3b709145c35c2","abstract_canon_sha256":"7ca7d3bb9be2858a7ec7e49d0a648e7ce60ce8377b0dc377188c8a3396c2b64f"},"schema_version":"1.0"},"canonical_sha256":"63744826f0377968717f45984332c6b298819ba5d74ad8597e990b25ff4f2a92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:04:51.892844Z","signature_b64":"dcXGTLnWEBhMZdes4FU24bz6f1DYq8wX3hsvnG3XHLo9LKuNllfJ9OLQ9aX2l/eEb9VN/cImku0clbqXXeB3AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63744826f0377968717f45984332c6b298819ba5d74ad8597e990b25ff4f2a92","last_reissued_at":"2026-05-29T01:04:51.892373Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:04:51.892373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.03805","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":"2026-05-29T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nN89m1F93r/EUhO6ZICYuCNQUJzpmwVtJFZPkwim9ucbNstzeKmFwQnwptouXtMZJ+9Epo3oDyqiyIO8smRQAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:34:44.759151Z"},"content_sha256":"f49929d30f66725e68b75da29d6654ef5efd05233dddf591039ee764940f7985","schema_version":"1.0","event_id":"sha256:f49929d30f66725e68b75da29d6654ef5efd05233dddf591039ee764940f7985"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MN2EQJXQG54WQ4L7IWMEGMWGWK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Haoyu Guo, Junlin Lv, S Kevin Zhou, Xike Xie, Yuan Feng, Yukun Cao","submitted_at":"2025-02-06T06:31:47Z","abstract_excerpt":"Large language models have revolutionized natural language processing but face significant challenges of high storage and runtime costs, due to the transformer architecture's reliance on self-attention, particularly the large KV cache for long-sequence inference. Recent efforts to reduce KV cache size by pruning less critical entries based on attention weights remain empirical and lack formal grounding. This paper presents a formal study on identifying critical KV cache entries by analyzing attention output perturbation. Our analysis reveals that, beyond attention weights, the value states wit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03805","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/2502.03805/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":"2026-05-29T01:04:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dH8Sx0rDJOream64a6Lc62e2dW/3HtLfQskOQg+qQEctbSupu8SjLVO6MdcBmhyzu+FeIL9iDx8tJa+lGKIYCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:34:44.759535Z"},"content_sha256":"cbf200cbe9a646753147b6535d2ac429f48b0bfd8453a3323fa3cd7911447d50","schema_version":"1.0","event_id":"sha256:cbf200cbe9a646753147b6535d2ac429f48b0bfd8453a3323fa3cd7911447d50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/bundle.json","state_url":"https://pith.science/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/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":"2026-06-02T14:34:44Z","links":{"resolver":"https://pith.science/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK","bundle":"https://pith.science/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/bundle.json","state":"https://pith.science/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MN2EQJXQG54WQ4L7IWMEGMWGWK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MN2EQJXQG54WQ4L7IWMEGMWGWK","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":"7ca7d3bb9be2858a7ec7e49d0a648e7ce60ce8377b0dc377188c8a3396c2b64f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-06T06:31:47Z","title_canon_sha256":"fe576bcc2b56dad45d962889287c4e0eede3801a3d1abb489fc3b709145c35c2"},"schema_version":"1.0","source":{"id":"2502.03805","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.03805","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"arxiv_version","alias_value":"2502.03805v2","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03805","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_12","alias_value":"MN2EQJXQG54W","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_16","alias_value":"MN2EQJXQG54WQ4L7","created_at":"2026-05-29T01:04:51Z"},{"alias_kind":"pith_short_8","alias_value":"MN2EQJXQ","created_at":"2026-05-29T01:04:51Z"}],"graph_snapshots":[{"event_id":"sha256:cbf200cbe9a646753147b6535d2ac429f48b0bfd8453a3323fa3cd7911447d50","target":"graph","created_at":"2026-05-29T01:04:51Z","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/2502.03805/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models have revolutionized natural language processing but face significant challenges of high storage and runtime costs, due to the transformer architecture's reliance on self-attention, particularly the large KV cache for long-sequence inference. Recent efforts to reduce KV cache size by pruning less critical entries based on attention weights remain empirical and lack formal grounding. This paper presents a formal study on identifying critical KV cache entries by analyzing attention output perturbation. Our analysis reveals that, beyond attention weights, the value states wit","authors_text":"Haoyu Guo, Junlin Lv, S Kevin Zhou, Xike Xie, Yuan Feng, Yukun Cao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-06T06:31:47Z","title":"CriticalKV: Optimizing KV Cache Eviction from an Output Perturbation Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03805","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:f49929d30f66725e68b75da29d6654ef5efd05233dddf591039ee764940f7985","target":"record","created_at":"2026-05-29T01:04:51Z","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":"7ca7d3bb9be2858a7ec7e49d0a648e7ce60ce8377b0dc377188c8a3396c2b64f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-06T06:31:47Z","title_canon_sha256":"fe576bcc2b56dad45d962889287c4e0eede3801a3d1abb489fc3b709145c35c2"},"schema_version":"1.0","source":{"id":"2502.03805","kind":"arxiv","version":2}},"canonical_sha256":"63744826f0377968717f45984332c6b298819ba5d74ad8597e990b25ff4f2a92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"63744826f0377968717f45984332c6b298819ba5d74ad8597e990b25ff4f2a92","first_computed_at":"2026-05-29T01:04:51.892373Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:04:51.892373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dcXGTLnWEBhMZdes4FU24bz6f1DYq8wX3hsvnG3XHLo9LKuNllfJ9OLQ9aX2l/eEb9VN/cImku0clbqXXeB3AQ==","signature_status":"signed_v1","signed_at":"2026-05-29T01:04:51.892844Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.03805","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f49929d30f66725e68b75da29d6654ef5efd05233dddf591039ee764940f7985","sha256:cbf200cbe9a646753147b6535d2ac429f48b0bfd8453a3323fa3cd7911447d50"],"state_sha256":"72d0ffd4118df94072c8c68651474809507e2998dfd89956cb37078db7b9d7dc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mS4984jGRJPH1VzT5u50GRzAJ0fQ+Avb8EwHNcFvXGJV8xJrqKYIlVHfqdCV9SwAh22tsF4cEjUKqQxOvJq6Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T14:34:44.761429Z","bundle_sha256":"e65b102ade2800e4f3b19b88a090761b9939deec47ffba9dc84ed8ac0b23c8e4"}}