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It's been said that "Language Models are Unsupervised Multitask Learners." Indeed, self-supervised language models trained on "positive" examples of English text generalize in desirable ways to many natural language tasks. But if such…

Computation and Language · Computer Science 2020-10-23 Michael L. Wick , Kate Silverstein , Jean-Baptiste Tristan , Adam Pocock , Mark Johnson

Recent approaches to human concept learning have successfully combined the power of symbolic, infinitely productive rule systems and statistical learning to explain our ability to learn new concepts from just a few examples. The aim of most…

Artificial Intelligence · Computer Science 2020-04-29 Pablo Tano , Sergio Romano , Mariano Sigman , Alejo Salles , Santiago Figueira

Juba recently proposed a formulation of learning abductive reasoning from examples, in which both the relative plausibility of various explanations, as well as which explanations are valid, are learned directly from data. The main…

Artificial Intelligence · Computer Science 2017-11-28 Brendan Juba , Zongyi Li , Evan Miller

In the first year of life, infants' speech perception becomes attuned to the sounds of their native language. Many accounts of this early phonetic learning exist, but computational models predicting the attunement patterns observed in…

Computation and Language · Computer Science 2020-08-10 Yevgen Matusevych , Thomas Schatz , Herman Kamper , Naomi H. Feldman , Sharon Goldwater

How do children learn correspondences between the language and the world from noisy, ambiguous, naturalistic input? One hypothesis is via cross-situational learning: tracking words and their possible referents across multiple situations…

Computation and Language · Computer Science 2020-03-13 Wai Keen Vong , Brenden M. Lake

This survey provides an overview of the evolution of visually grounded models of spoken language over the last 20 years. Such models are inspired by the observation that when children pick up a language, they rely on a wide range of…

Artificial Intelligence · Computer Science 2022-02-22 Grzegorz Chrupała

The performance of sentence encoders can be significantly improved through the simple practice of fine-tuning using contrastive loss. A natural question arises: what characteristics do models acquire during contrastive learning? This paper…

Computation and Language · Computer Science 2023-10-25 Hiroto Kurita , Goro Kobayashi , Sho Yokoi , Kentaro Inui

The probing methodology allows one to obtain a partial representation of linguistic phenomena stored in the inner layers of the neural network, using external classifiers and statistical analysis. Pre-trained transformer-based language…

Computation and Language · Computer Science 2022-07-04 Ekaterina Voloshina , Oleg Serikov , Tatiana Shavrina

We argue that language-only models don't learn the physical manifestation of language. We present an empirical investigation of visual-auditory properties of language through a series of tasks, termed H-Test. These tasks highlight a…

Computation and Language · Computer Science 2024-06-07 Bruce W. Lee , JaeHyuk Lim

Petroni et al. (2019) demonstrated that it is possible to retrieve world facts from a pre-trained language model by expressing them as cloze-style prompts and interpret the model's prediction accuracy as a lower bound on the amount of…

Computation and Language · Computer Science 2021-12-15 Zexuan Zhong , Dan Friedman , Danqi Chen

Semantic parsing has emerged as a significant and powerful paradigm for natural language interface and question answering systems. Traditional methods of building a semantic parser rely on high-quality lexicons, hand-crafted grammars and…

Computation and Language · Computer Science 2017-05-10 Liang Li , Pengyu Li , Yifan Liu , Tao Wan , Zengchang Qin

One of the common ways children learn is by mimicking adults. Imitation learning focuses on learning policies with suitable performance from demonstrations generated by an expert, with an unspecified performance measure, and unobserved…

Machine Learning · Computer Science 2022-08-15 Junzhe Zhang , Daniel Kumor , Elias Bareinboim

Most positive and unlabeled data is subject to selection biases. The labeled examples can, for example, be selected from the positive set because they are easier to obtain or more obviously positive. This paper investigates how learning can…

Machine Learning · Computer Science 2019-07-01 Jessa Bekker , Pieter Robberechts , Jesse Davis

We propose a learning system in which language is grounded in visual percepts without specific pre-defined categories of terms. We present a unified generative method to acquire a shared semantic/visual embedding that enables the learning…

Computation and Language · Computer Science 2021-08-02 Nisha Pillai , Cynthia Matuszek , Francis Ferraro

This paper proposes an incremental method that can be used by an intelligent system to learn better descriptions of a thematic context. The method starts with a small number of terms selected from a simple description of the topic under…

Information Retrieval · Computer Science 2010-04-28 Carlos M. Lorenzetti , Ana G. Maguitman

This study explores an LLM's ability to learn new languages using explanations found in a grammar book, a process we term "explicit learning." To rigorously assess this ability, we design controlled translation experiments between English…

Computation and Language · Computer Science 2025-09-05 Malik Marmonier , Rachel Bawden , Benoît Sagot

Predicting the words that a child is going to learn next can be useful for boosting language acquisition, and such predictions have been shown to be possible with both neural network techniques (looking at changes in the vocabulary state…

Computation and Language · Computer Science 2025-03-24 Andrew Roxburgh , Floriana Grasso , Terry R. Payne

This paper reviews the main perspectives of language acquisition and language comprehension. In language acquisition, we have reviewed the different types of language acquisitions like first language acquisition, second language…

Neurons and Cognition · Quantitative Biology 2020-05-13 Kailsah Nath Tripathi , Anand Bihari , Sudhakar Tripathi , R. B. Mishra

This paper explores the impact of variable pragmatic competence on communicative success through simulating language learning and conversing between speakers and listeners with different levels of reasoning abilities. Through studying this…

Computation and Language · Computer Science 2024-10-10 Kata Naszadi , Frans A. Oliehoek , Christof Monz

Language change is a cultural evolutionary process in which variants of linguistic variables change in frequency through processes analogous to mutation, selection and genetic drift. In this work, we apply a recently-introduced method to…

Computation and Language · Computer Science 2023-08-22 Juan Guerrero Montero , Andres Karjus , Kenny Smith , Richard A. Blythe