Paper

Large Language Models as Modal Models in Linguistics

Unreadunread

AI summary

arXiv:2606. 10467v1 Announce Type: new Abstract: The rapid advancement of large language models (LLMs) has intensified debates about their significance for linguistic theory.

Reading status

Priority

About this paper

Authors: Haruto Suzuki, Saku Sugawara
Released: 2026-06-10 (29d ago)
Topic: Related to current project
Relation to my work: Read next because Large Language Models as Modal Models in Linguistics overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "Only continuous soft prefixes hit both EM axes at once on Qwen-2.5-7B-Instruct: discrete prompt searches split between the alignment objective and the distributional objective, and both discretizations of the soft prefix collapse (MODERATE confidence)", experiment "Add C2 control arm (donor sees marker_B without marker_A) to disambiguate paired-marker binding from marker_B leaking alone". Matching terms: under, eval, without, position, test, language, model. Source: arxiv cs.CL (NLP).
arXiv: 2606.10467

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to Large Language Models as Modal Models in Linguistics. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.