{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:4TPHQWJ5NXY4FCXIC644Z4QWW7","short_pith_number":"pith:4TPHQWJ5","schema_version":"1.0","canonical_sha256":"e4de78593d6df1c28ae817b9ccf216b7e95372f61125a64bd1966a95977310ec","source":{"kind":"arxiv","id":"2605.10061","version":1},"attestation_state":"computed","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."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":true,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.10061","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-05-11T06:38:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"061c49fb7b52b80356013514ae9d135b5276ca8b86660aeee627b13ee39708f0","abstract_canon_sha256":"80721926dbdb497aa17a53ac02d0da34b6257f8d5d55263f15c4af9b67a28ed0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T15:59:25.052806Z","signature_b64":"kttMIOsotMjjZAhFTqLOm+jC+aqjIqxZ6CoTkfX0XIe3mO0pp8k1T9Ls+X1EatALB+dzBMUyL4uaH4hrLe26CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e4de78593d6df1c28ae817b9ccf216b7e95372f61125a64bd1966a95977310ec","last_reissued_at":"2026-05-18T15:59:25.051778Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T15:59:25.051778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.10061","created_at":"2026-05-18T15:59:25.051906+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.10061v1","created_at":"2026-05-18T15:59:25.051906+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.10061","created_at":"2026-05-18T15:59:25.051906+00:00"},{"alias_kind":"pith_short_12","alias_value":"4TPHQWJ5NXY4","created_at":"2026-05-18T15:59:25.051906+00:00"},{"alias_kind":"pith_short_16","alias_value":"4TPHQWJ5NXY4FCXI","created_at":"2026-05-18T15:59:25.051906+00:00"},{"alias_kind":"pith_short_8","alias_value":"4TPHQWJ5","created_at":"2026-05-18T15:59:25.051906+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7","json":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7.json","graph_json":"https://pith.science/api/pith-number/4TPHQWJ5NXY4FCXIC644Z4QWW7/graph.json","events_json":"https://pith.science/api/pith-number/4TPHQWJ5NXY4FCXIC644Z4QWW7/events.json","paper":"https://pith.science/paper/4TPHQWJ5"},"agent_actions":{"view_html":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7","download_json":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7.json","view_paper":"https://pith.science/paper/4TPHQWJ5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.10061&json=true","fetch_graph":"https://pith.science/api/pith-number/4TPHQWJ5NXY4FCXIC644Z4QWW7/graph.json","fetch_events":"https://pith.science/api/pith-number/4TPHQWJ5NXY4FCXIC644Z4QWW7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7/action/storage_attestation","attest_author":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7/action/author_attestation","sign_citation":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7/action/citation_signature","submit_replication":"https://pith.science/pith/4TPHQWJ5NXY4FCXIC644Z4QWW7/action/replication_record"}},"created_at":"2026-05-18T15:59:25.051906+00:00","updated_at":"2026-05-18T15:59:25.051906+00:00"}