Language Acquisition
68 papers with code • 1 benchmarks • 6 datasets
Language acquisition refers to tasks related to the learning of a second language.
Benchmarks
These leaderboards are used to track progress in Language Acquisition
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Libraries
Use these libraries to find Language Acquisition models and implementationsDatasets
BLiMP
Duolingo SLAM Shared Task
Duolingo Spaced Repetition Data
New Brown Corpus
BabySLM
Latest papers
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling
EvLab-MIT/LexiContrastiveGrd
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Today's most accurate language models are trained on orders of magnitude more language data than human language learners receive - but with no supervision from other sensory modalities that play a crucial role in human learning.
Opening the black box of language acquisition
However, it is unclear whether or how these models represent grammatical information from the learned languages.
Multilingual Mathematical Autoformalization
In this work, we create $\texttt{MMA}$, a large, flexible, multilingual, and multi-domain dataset of informal-formal pairs, by using a language model to translate in the reverse direction, that is, from formal mathematical statements into corresponding informal ones.
Mini Minds: Exploring Bebeshka and Zlata Baby Models
In this paper, we describe the University of Lyon 2 submission to the Strict-Small track of the BabyLM competition.
Ling-CL: Understanding NLP Models through Linguistic Curricula
We employ a characterization of linguistic complexity from psycholinguistic and language acquisition research to develop data-driven curricula to understand the underlying linguistic knowledge that models learn to address NLP tasks.
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes
EvLab-MIT/LexiContrastiveGrd
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But to achieve these results, LMs must be trained in distinctly un-human-like ways - requiring orders of magnitude more language data than children receive during development, and without perceptual or social context.
CiwaGAN: Articulatory information exchange
This paper introduces CiwaGAN, a model of human spoken language acquisition that combines unsupervised articulatory modeling with an unsupervised model of information exchange through the auditory modality.
Spoken Language Intelligence of Large Language Models for Language Learning
Our focus is centered on evaluating the efficacy of LLMs in the realm of education, specifically in the areas of spoken language learning which encompass phonetics, phonology, and second language acquisition.
Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition
sled-group/comparative-learning
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Human language acquisition is an efficient, supervised, and continual process.
Second Language Acquisition of Neural Language Models
With the success of neural language models (LMs), their language acquisition has gained much attention.
