{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SLN7ING4TPN56ATXAEJOZ2E4MW","short_pith_number":"pith:SLN7ING4","canonical_record":{"source":{"id":"2502.17599","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-24T19:34:52Z","cross_cats_sorted":[],"title_canon_sha256":"c2298a308cd04c5b7e145ccece93f549b1cb5b6f3a64fb1e1718b352bb521b27","abstract_canon_sha256":"9c8127512994b7b6228dacf06d19a40d79d46425aa9e5a87b47cc74cacd2fba3"},"schema_version":"1.0"},"canonical_sha256":"92dbf434dc9bdbdf02770112ece89c658e63e6a0197552a4bc2a9660807861af","source":{"kind":"arxiv","id":"2502.17599","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.17599","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.17599v2","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.17599","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_12","alias_value":"SLN7ING4TPN5","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_16","alias_value":"SLN7ING4TPN56ATX","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_8","alias_value":"SLN7ING4","created_at":"2026-07-05T10:30:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SLN7ING4TPN56ATXAEJOZ2E4MW","target":"record","payload":{"canonical_record":{"source":{"id":"2502.17599","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-24T19:34:52Z","cross_cats_sorted":[],"title_canon_sha256":"c2298a308cd04c5b7e145ccece93f549b1cb5b6f3a64fb1e1718b352bb521b27","abstract_canon_sha256":"9c8127512994b7b6228dacf06d19a40d79d46425aa9e5a87b47cc74cacd2fba3"},"schema_version":"1.0"},"canonical_sha256":"92dbf434dc9bdbdf02770112ece89c658e63e6a0197552a4bc2a9660807861af","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:30:31.377829Z","signature_b64":"L0RoImGLm/cSor+Oqs8FOrpOqLPQT0bpc9/FnCQfY2Mi5UnMMsDrkkbb9CyVzqNHwEQ3L0jTBwL1TfqrN5KtAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92dbf434dc9bdbdf02770112ece89c658e63e6a0197552a4bc2a9660807861af","last_reissued_at":"2026-07-05T10:30:31.377302Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:30:31.377302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.17599","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":"2026-07-05T10:30:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"awaf9BtmvitXkSM23hGhr44vfaPN3bNZvrZW46eVePELnPAU3g+S7a/zyGey2g/qtwyWLxirS7UyL5wNMuisDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T13:18:23.661375Z"},"content_sha256":"1a1c97640cdf03bad5979f8a78aaf43c1f7d1f6da7cc68e7940c444f29825300","schema_version":"1.0","event_id":"sha256:1a1c97640cdf03bad5979f8a78aaf43c1f7d1f6da7cc68e7940c444f29825300"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SLN7ING4TPN56ATXAEJOZ2E4MW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Che Liu, Hui Shen, Mi Zhang, Xin Wang, Zheda Mai, Zhongwei Wan","submitted_at":"2025-02-24T19:34:52Z","abstract_excerpt":"Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-video modalities, demand substantial resources as their multimodal Key-Value (KV) caches grow with increasing input lengths, challenging inference efficiency. Existing methods for KV cache compression, in both text-only and multimodal LLMs, have neglected attention density variations across layers, thus often adopting uniform or progressive reduction strategies for layer-wise cache allocation. In this work, we propose MEDA, a dynamic layer-wise KV cache allocation method for efficient multimodal lon"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.17599","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/2502.17599/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":"2026-07-05T10:30:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bf3U6vPtIarDy9/ZUP3ReMSGBPqavmYfGT7BNujWsH34/OFG9Vur/QEFc9B5tBKVpMemSBQgdUfwWPdoDfOTDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T13:18:23.661758Z"},"content_sha256":"8fa7481562479315ea0ccae409d60fea6a1474f8cabec2bcf8b5823867ce78b8","schema_version":"1.0","event_id":"sha256:8fa7481562479315ea0ccae409d60fea6a1474f8cabec2bcf8b5823867ce78b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/bundle.json","state_url":"https://pith.science/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/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":"2026-08-03T13:18:23Z","links":{"resolver":"https://pith.science/pith/SLN7ING4TPN56ATXAEJOZ2E4MW","bundle":"https://pith.science/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/bundle.json","state":"https://pith.science/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SLN7ING4TPN56ATXAEJOZ2E4MW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SLN7ING4TPN56ATXAEJOZ2E4MW","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":"9c8127512994b7b6228dacf06d19a40d79d46425aa9e5a87b47cc74cacd2fba3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-24T19:34:52Z","title_canon_sha256":"c2298a308cd04c5b7e145ccece93f549b1cb5b6f3a64fb1e1718b352bb521b27"},"schema_version":"1.0","source":{"id":"2502.17599","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.17599","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.17599v2","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.17599","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_12","alias_value":"SLN7ING4TPN5","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_16","alias_value":"SLN7ING4TPN56ATX","created_at":"2026-07-05T10:30:31Z"},{"alias_kind":"pith_short_8","alias_value":"SLN7ING4","created_at":"2026-07-05T10:30:31Z"}],"graph_snapshots":[{"event_id":"sha256:8fa7481562479315ea0ccae409d60fea6a1474f8cabec2bcf8b5823867ce78b8","target":"graph","created_at":"2026-07-05T10:30:31Z","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/2502.17599/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-video modalities, demand substantial resources as their multimodal Key-Value (KV) caches grow with increasing input lengths, challenging inference efficiency. Existing methods for KV cache compression, in both text-only and multimodal LLMs, have neglected attention density variations across layers, thus often adopting uniform or progressive reduction strategies for layer-wise cache allocation. In this work, we propose MEDA, a dynamic layer-wise KV cache allocation method for efficient multimodal lon","authors_text":"Che Liu, Hui Shen, Mi Zhang, Xin Wang, Zheda Mai, Zhongwei Wan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-24T19:34:52Z","title":"MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.17599","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":"sha256:1a1c97640cdf03bad5979f8a78aaf43c1f7d1f6da7cc68e7940c444f29825300","target":"record","created_at":"2026-07-05T10:30:31Z","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":"9c8127512994b7b6228dacf06d19a40d79d46425aa9e5a87b47cc74cacd2fba3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-24T19:34:52Z","title_canon_sha256":"c2298a308cd04c5b7e145ccece93f549b1cb5b6f3a64fb1e1718b352bb521b27"},"schema_version":"1.0","source":{"id":"2502.17599","kind":"arxiv","version":2}},"canonical_sha256":"92dbf434dc9bdbdf02770112ece89c658e63e6a0197552a4bc2a9660807861af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92dbf434dc9bdbdf02770112ece89c658e63e6a0197552a4bc2a9660807861af","first_computed_at":"2026-07-05T10:30:31.377302Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:30:31.377302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L0RoImGLm/cSor+Oqs8FOrpOqLPQT0bpc9/FnCQfY2Mi5UnMMsDrkkbb9CyVzqNHwEQ3L0jTBwL1TfqrN5KtAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:30:31.377829Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.17599","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1a1c97640cdf03bad5979f8a78aaf43c1f7d1f6da7cc68e7940c444f29825300","sha256:8fa7481562479315ea0ccae409d60fea6a1474f8cabec2bcf8b5823867ce78b8"],"state_sha256":"e781a30311fbd5b0200343336188884b6b169204f5a35f9c8485b55b984585fe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xnFH6M/jLHAqZtKx9OQT6aV+jtbloKoiK7crQUSeNO9FazOadgTM0NbVBLf9ujTHXTuEYfQHHDaswPzLnFaMDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T13:18:23.664513Z","bundle_sha256":"0ae443f6809dcd5c402384151ea28459e2c53f49e25affb441155874056ad4c1"}}