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A retrospective analysis on the use of LLMs to study infant syntax learning

Paper recorded by Signals 4 on 2026-09-22 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-22 on arXiv · recorded by Signals 4 on 2026-09-23

Category: cs.CL · 自然语言处理 · first seen 2026-09-23

Abstract

Large language models (LLMs) have increasingly been used to investigate how children acquire syntax at an early stage of development. This is notably the central scientific goal of the BabyLM challenge, a community-wide effort to develop models that achieve human-level syntactic performance while being trained on developmentally realistic corpora. In this paper, we reflect on the use of LLMs in th

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#9 most recent of 227 cs.CL papers we have recorded · ↑ newer: Receptiveness, Not Sycophancy: Distinguishing Engagement from Deferenc · ↓ older: Transcribe, Translate, and Optimize: Joint Reward Learning for Speech
Cite this page: A retrospective analysis on the use of LLMs to study infant syntax learning: the #9 most recent of 227 cs.CL papers we have recorded (as of 2026-09-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-retrospective-analysis-on-the-use-of-llms-to-study-infant-syntax-learning.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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