{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Y7TEUVAOJVEVNZBAKYYGXMCVAO","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":"3580ce5b0e9ad43ba0c88f68ed9a36f59c5b6709231c34f2206cf1b27b7487e8","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-04T00:43:20Z","title_canon_sha256":"2656815c3c98e1795f32dec3dacc4723a40ab9523d4124f4f5a9c9f71e93484b"},"schema_version":"1.0","source":{"id":"2606.05538","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05538","created_at":"2026-06-05T01:14:54Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05538v1","created_at":"2026-06-05T01:14:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05538","created_at":"2026-06-05T01:14:54Z"},{"alias_kind":"pith_short_12","alias_value":"Y7TEUVAOJVEV","created_at":"2026-06-05T01:14:54Z"},{"alias_kind":"pith_short_16","alias_value":"Y7TEUVAOJVEVNZBA","created_at":"2026-06-05T01:14:54Z"},{"alias_kind":"pith_short_8","alias_value":"Y7TEUVAO","created_at":"2026-06-05T01:14:54Z"}],"graph_snapshots":[{"event_id":"sha256:5bd78a20f5ffe91b074684cb5721f2ae9f9ebbfbbd004d0801e3cd02bbb36068","target":"graph","created_at":"2026-06-05T01:14:54Z","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/2606.05538/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mixture-of-Experts (MoE) models achieve strong performance through conditional computation, but their large parameter footprint poses deployment challenges. Prior MoE compression approaches catastrophically fail when evaluated on general-purpose benchmarks beyond commonsense reasoning. We trace this failure to the granularity of compression: important capabilities are distributed across experts but concentrated in FFN sparse intermediate dimensions. To identify these dimensions, we use Fisher importance which outperforms activation-, router-score-, and magnitude-based alternatives, and identif","authors_text":"Ao Qu, Haoze He, Heather Miller, Juncheng Billy Li, Xingyuan Ding, Xinkai Zou, Xuan Jiang","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-04T00:43:20Z","title":"Less is MoE: Trimming Experts in Domain-Specialist Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05538","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":"sha256:17a7e5bd41897c2736872d6712971c97b600d00e1266d15282e82d6908899be0","target":"record","created_at":"2026-06-05T01:14:54Z","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":"3580ce5b0e9ad43ba0c88f68ed9a36f59c5b6709231c34f2206cf1b27b7487e8","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-04T00:43:20Z","title_canon_sha256":"2656815c3c98e1795f32dec3dacc4723a40ab9523d4124f4f5a9c9f71e93484b"},"schema_version":"1.0","source":{"id":"2606.05538","kind":"arxiv","version":1}},"canonical_sha256":"c7e64a540e4d4956e42056306bb0550389c6ce06379a42be2e67d091bac9bf57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7e64a540e4d4956e42056306bb0550389c6ce06379a42be2e67d091bac9bf57","first_computed_at":"2026-06-05T01:14:54.188174Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:14:54.188174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uYQ1KRJhyqqpZrtv7dEZca6pCn5zh8lHkWJtCtvyyH281TtZbYiNvpnOvRTJqz0mPBCW37I6tAqMk1wDgGNTBw==","signature_status":"signed_v1","signed_at":"2026-06-05T01:14:54.188597Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05538","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17a7e5bd41897c2736872d6712971c97b600d00e1266d15282e82d6908899be0","sha256:5bd78a20f5ffe91b074684cb5721f2ae9f9ebbfbbd004d0801e3cd02bbb36068"],"state_sha256":"7690fc7e811c5e2661b938df3feae5cfbafe8b654678903825636262edf3c7e4"}