{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TPLPIKCZSSCXR4IOQ3DXDE5EBA","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":"ecb11adedc1c4c5940749e95206607ad0aea9b271f187a3c8a677fbecb012124","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-18T08:33:52Z","title_canon_sha256":"4736c73e70475f1c6f1f2ee0be81f1c1f53ddb3ab6d15c23b2b2a658a5f205cc"},"schema_version":"1.0","source":{"id":"2605.18041","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18041","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18041v1","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18041","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_12","alias_value":"TPLPIKCZSSCX","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_16","alias_value":"TPLPIKCZSSCXR4IO","created_at":"2026-05-20T00:05:12Z"},{"alias_kind":"pith_short_8","alias_value":"TPLPIKCZ","created_at":"2026-05-20T00:05:12Z"}],"graph_snapshots":[{"event_id":"sha256:4890957c1ea96df630b1f0b101001b88a5b8cbb1577b2fad43671def05a7ac2a","target":"graph","created_at":"2026-05-20T00:05:12Z","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":[{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T23:41:59.306205Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.496766Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.18041/integrity.json","findings":[],"snapshot_sha256":"5f4d131fc7135cdbf757f8562acee7afb759c2fab172e5eeb8de66c9bb5e0814","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Omnimodal large language models (OmniLLMs) have recently gained increasing attention for unified audio-video understanding. However, processing long multimodal token sequences introduces substantial computational overhead, making efficient token compression crucial. Existing methods typically rely on fixed, modality-specific guidance, which fails to account for the varying importance of modalities across different queries. To address this limitation, we propose $\\textbf{OmniSelect}$, a training-free, modality-adaptive token pruning framework that dynamically selects appropriate compression str","authors_text":"Jianxin Zhang, Juntao Li, Le Li, Morunliu Yang, Peifeng Li, Ruotao Xu, Siwei Feng, Yihang Lou, Yue Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-18T08:33:52Z","title":"OmniSelect: Dynamic Modality-Aware Token Compression for Efficient Omni-modal Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18041","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:d8a8d38651e30e9ca4640db00cff6c964afa502e665f5e9b847bb93851ce5eea","target":"record","created_at":"2026-05-20T00:05:12Z","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":"ecb11adedc1c4c5940749e95206607ad0aea9b271f187a3c8a677fbecb012124","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-18T08:33:52Z","title_canon_sha256":"4736c73e70475f1c6f1f2ee0be81f1c1f53ddb3ab6d15c23b2b2a658a5f205cc"},"schema_version":"1.0","source":{"id":"2605.18041","kind":"arxiv","version":1}},"canonical_sha256":"9bd6f42859948578f10e86c77193a4080f85796e4ae22c26a20d00ef185b30ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9bd6f42859948578f10e86c77193a4080f85796e4ae22c26a20d00ef185b30ec","first_computed_at":"2026-05-20T00:05:12.815564Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:12.815564Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D/SZaZcNetZQ/FeWBJBX0ptpC50yRgiWWjAG408VG3o9M0CISmsqmsVD0UtSYiorNd6v3STtFYgxC8uV3Wu5CA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:12.816670Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.18041","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8a8d38651e30e9ca4640db00cff6c964afa502e665f5e9b847bb93851ce5eea","sha256:4890957c1ea96df630b1f0b101001b88a5b8cbb1577b2fad43671def05a7ac2a"],"state_sha256":"50c0119755138754c7c78097e4969a3a98f75ad03b32f536cd8065df8a082ace"}