{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6NSCPLZ62MU5B466CVSKAU3DON","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":"a7029efe750eeb876638d5a268d7777349815d96a60388864da78921e6064621","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T06:02:56Z","title_canon_sha256":"771b5b4457f5edc95a508f3b65304197b3270264bb362d1a8800a4d8a0dc8346"},"schema_version":"1.0","source":{"id":"2410.10181","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.10181","created_at":"2026-07-05T09:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"2410.10181v2","created_at":"2026-07-05T09:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.10181","created_at":"2026-07-05T09:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"6NSCPLZ62MU5","created_at":"2026-07-05T09:25:02Z"},{"alias_kind":"pith_short_16","alias_value":"6NSCPLZ62MU5B466","created_at":"2026-07-05T09:25:02Z"},{"alias_kind":"pith_short_8","alias_value":"6NSCPLZ6","created_at":"2026-07-05T09:25:02Z"}],"graph_snapshots":[{"event_id":"sha256:ddff2bf8095cc45941186552ad021cd762542052c07a9eba5bb37cbbd328a5ee","target":"graph","created_at":"2026-07-05T09:25:02Z","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/2410.10181/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Domain-specific adaptation is critical to maximizing the performance of pre-trained language models (PLMs) on one or multiple targeted tasks, especially under resource-constrained use cases, such as edge devices. However, existing methods often struggle to balance domain-specific performance, retention of general knowledge, and efficiency for training and inference. To address these challenges, we propose Modular Domain Experts (MoDE). MoDE is a mixture-of-experts architecture that augments a general PLMs with modular, domain-specialized experts. These experts are trained independently and com","authors_text":"Arun Kandoor, Chih-Kuan Yeh, James Laudon, Peter Schafhalter, Shun Liao, Yanqi Zhou","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T06:02:56Z","title":"Scalable Multi-Domain Adaptation of Language Models using Modular Experts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.10181","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:e229b779c70a8ac50c14704a3f59c72f1c1ca67cc2f04e7595838a966a4f3187","target":"record","created_at":"2026-07-05T09:25:02Z","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":"a7029efe750eeb876638d5a268d7777349815d96a60388864da78921e6064621","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T06:02:56Z","title_canon_sha256":"771b5b4457f5edc95a508f3b65304197b3270264bb362d1a8800a4d8a0dc8346"},"schema_version":"1.0","source":{"id":"2410.10181","kind":"arxiv","version":2}},"canonical_sha256":"f36427af3ed329d0f3de1564a053637372d2b9f9dcd944ead543645955787db4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f36427af3ed329d0f3de1564a053637372d2b9f9dcd944ead543645955787db4","first_computed_at":"2026-07-05T09:25:02.203220Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:25:02.203220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZG3Lk+dOEGgN/l1gkHkuzkwVh+aI3CILw6rcUQ72Kg7bxrWr9UKDNc3iDhD94Qknzs8vcERXv9Zgd4SCrPkbDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:25:02.203660Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.10181","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e229b779c70a8ac50c14704a3f59c72f1c1ca67cc2f04e7595838a966a4f3187","sha256:ddff2bf8095cc45941186552ad021cd762542052c07a9eba5bb37cbbd328a5ee"],"state_sha256":"46f66686eff368df7eb23421263f6ae2ce2c62f9ba1dac2fd8aba535f518de69"}