{"paper":{"title":"Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appear","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"Language models can instantiate formal generative linguistic theories in addition to usage-based ones.","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"R. Thomas McCoy","submitted_at":"2026-05-11T06:38:40Z","abstract_excerpt":"Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in the generative tradition. This argument expands the space of theories that can be tested with LMs, potentially enabling reconciliations between usage-based and generative accounts."},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in the generative tradition.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the observed success and behavior of LMs can be interpreted as instantiating formal generative theories without additional evidence or specific mechanisms provided.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Language models can support formal generative linguistic theories, expanding testable theories and potentially reconciling them with usage-based accounts.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Language models can instantiate formal generative linguistic theories in addition to usage-based ones.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"0f08869c93aa817aa387a7f3805c61df33db42847744b289ab40cc475bb25df9"},"source":{"id":"2605.10061","kind":"arxiv","version":1},"verdict":{"id":"9e686e6e-575a-4371-9b40-8851d417127b","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-12T02:10:48.890450Z","strongest_claim":"I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in the generative tradition.","one_line_summary":"Language models can support formal generative linguistic theories, expanding testable theories and potentially reconciling them with usage-based accounts.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the observed success and behavior of LMs can be interpreted as instantiating formal generative theories without additional evidence or specific mechanisms provided.","pith_extraction_headline":"Language models can instantiate formal generative linguistic theories in addition to usage-based ones."},"references":{"count":12,"sample":[{"doi":"","year":2025,"title":"Boleda, G. (2025). LLMs as a synthesis between symbolic and distributed approaches to language. In Findings of the Association for Computational Linguistics: EMNLP 2025, pages 9365–9379, Suzhou, China","work_id":"61fe8f61-5b7c-4107-aadd-d6d57fbfb241","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2001,"title":"Bybee, J. L. and Hopper, P. J. (2001).Frequency and the emergence of linguistic structure. John Benjamins Publishing Company","work_id":"514ef8e7-394a-4b12-bf4d-d6fc1ae203d1","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1993,"title":"Chomsky, N. (1993). A minimalist program for linguistic theory. InThe View from Building 20, pages 1–52. MIT Press","work_id":"c12690cf-ef61-4c54-ad35-5eab93cb7060","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2025,"title":"Futrell, R. and Mahowald, K. (2025). How linguistics learned to stop worrying and love the language models.Behavioral and Brain Sciences, pages 1–98","work_id":"17881b4b-086f-4958-bcde-7b73fcd553be","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2024,"title":"Kim, N., Schuster, S., and Toshniwal, S. (2024). Code pretraining improves entity tracking abilities of language models.arXiv preprint arXiv:2405.21068","work_id":"38bff4b3-9a1f-4c77-99d2-a6667f4bccbd","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":12,"snapshot_sha256":"8923fee80d2db7dd9cdca13b8f61f9d6c77f81d774e94614688da46d3515f876","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"}