{"paper":{"title":"Language Acquisition Device in Large Language Models","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"Pre-pretraining LLMs on MP-STRUCT achieves token efficiency on par with strong baselines while adding resistance to implausible languages.","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Masato Mita, Ryo Yoshida, Taiga Someya, Yohei Oseki","submitted_at":"2026-05-16T02:13:32Z","abstract_excerpt":"Large Language Models (LLMs) remain substantially less data-efficient than humans. Pre-pretraining (PPT) on synthetic languages has been proposed to close this gap, with prior work emphasizing highly expressive formal languages such as $k$-Shuffle Dyck. Inspired by the Language Acquisition Device (LAD) hypothesis, which posits that innate constraints preemptively restrict the learner's hypothesis space to natural-language-like structure, we propose LAD-inspired PPT: pre-pretraining on MP-STRUCT, a formal language whose strings encode hierarchical composition, feature-based dependencies, and lo"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"A brief 500-step PPT with MP-STRUCT matches strong formal-language baselines in token efficiency while additionally imparting a human-like resistance to structurally implausible languages (e.g., REVERSE).","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the structural properties encoded in MP-STRUCT (hierarchical composition, feature-based dependencies, long-distance displacement) successfully instantiate the innate constraints of the LAD hypothesis and transfer to improved natural-language behavior in LLMs.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Pre-pretraining on MP-STRUCT matches k-Shuffle Dyck baselines in efficiency while adding human-like resistance to implausible languages and challenges the need for C-RASP definability in effective PPT languages.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Pre-pretraining LLMs on MP-STRUCT achieves token efficiency on par with strong baselines while adding resistance to implausible languages.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"bb954bf25e6c819612c47d71ed52ee6a6cd38206696eadec10a1a93bb711bc7d"},"source":{"id":"2605.16758","kind":"arxiv","version":1},"verdict":{"id":"4f9f21e2-b5f9-4540-9feb-a7053aff5f25","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T21:41:19.236203Z","strongest_claim":"A brief 500-step PPT with MP-STRUCT matches strong formal-language baselines in token efficiency while additionally imparting a human-like resistance to structurally implausible languages (e.g., REVERSE).","one_line_summary":"Pre-pretraining on MP-STRUCT matches k-Shuffle Dyck baselines in efficiency while adding human-like resistance to implausible languages and challenges the need for C-RASP definability in effective PPT languages.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the structural properties encoded in MP-STRUCT (hierarchical composition, feature-based dependencies, long-distance displacement) successfully instantiate the innate constraints of the LAD hypothesis and transfer to improved natural-language behavior in LLMs.","pith_extraction_headline":"Pre-pretraining LLMs on MP-STRUCT achieves token efficiency on par with strong baselines while adding resistance to implausible languages."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.16758/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T22:01:19.776145Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T21:51:05.042862Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T19:01:56.321161Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.452872Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"c59784603001e5845ad14611bfd48d19b12910ad2786b2f33677060487c7f6d0"},"references":{"count":109,"sample":[{"doi":"10.1016/s0019-9958(59)90362-6","year":1959,"title":"Noam Chomsky , abstract =. 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