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A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations…

Machine Learning · Computer Science 2021-05-20 Jacob Russin , Roland Fernandez , Hamid Palangi , Eric Rosen , Nebojsa Jojic , Paul Smolensky , Jianfeng Gao

Human beings possess the most sophisticated computational machinery in the known universe. We can understand language of rich descriptive power, and communicate in the same environment with astonishing clarity. Two of the many contributors…

Computation and Language · Computer Science 2021-01-01 Karthikeya Ramesh Kaushik , Andrea E. Martin

How can a learner systematically prepare for reading a book they are interested in? In this paper,we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise generation can be…

Computation and Language · Computer Science 2020-11-24 Haemanth Santhi Ponnusamy , Detmar Meurers

We present a compositional semantics for various types of polar questions and wh-questions within the framework of Combinatory Categorial Grammar (CCG). To assess the explanatory power of our proposed analysis, we introduce a…

Computation and Language · Computer Science 2023-12-25 Hayate Funakura , Koji Mineshima

This paper measures the impact of increased exposure on whether learned construction grammars converge onto shared representations when trained on data from different registers. Register influences the frequency of constructions, with some…

Computation and Language · Computer Science 2021-10-13 Jonathan Dunn , Harish Tayyar Madabushi

We probe large language models' ability to learn deep form-meaning mappings as defined by construction grammars. We introduce the ConTest-NLI benchmark of 80k sentences covering eight English constructions from highly lexicalized to highly…

Computation and Language · Computer Science 2025-09-23 Tom Mackintosh , Harish Tayyar Madabushi , Claire Bonial

Despite interest in using cross-lingual knowledge to learn word embeddings for various tasks, a systematic comparison of the possible approaches is lacking in the literature. We perform an extensive evaluation of four popular approaches of…

Computation and Language · Computer Science 2016-06-09 Shyam Upadhyay , Manaal Faruqui , Chris Dyer , Dan Roth

Though generative dialogue modeling is widely seen as a language modeling task, the task demands an agent to have a complex natural language understanding of its input text to carry a meaningful interaction with an user. The automatic…

Computation and Language · Computer Science 2020-08-25 Prasanna Parthasarathi , Joelle Pineau , Sarath Chandar

Natural Language Parsing has been the most prominent research area since the genesis of Natural Language Processing. Probabilistic Parsers are being developed to make the process of parser development much easier, accurate and fast. In…

Computation and Language · Computer Science 2012-09-07 Nisheeth Joshi , Iti Mathur

This paper describes a computational framework for a grammar architecture in which different linguistic domains such as morphology, syntax, and semantics are treated not as separate components but compositional domains. Word and phrase…

cmp-lg · Computer Science 2008-02-03 Cem Bozsahin , Elvan Gocmen

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal…

Computation and Language · Computer Science 2017-03-28 Ivan Habernal , Iryna Gurevych

Current generative knowledge graph construction approaches usually fail to capture structural knowledge by simply flattening natural language into serialized texts or a specification language. However, large generative language model…

Computation and Language · Computer Science 2024-01-19 Zhen Bi , Jing Chen , Yinuo Jiang , Feiyu Xiong , Wei Guo , Huajun Chen , Ningyu Zhang

We study the problem of building generative models of natural source code (NSC); that is, source code written and understood by humans. Our primary contribution is to describe a family of generative models for NSC that have three key…

Programming Languages · Computer Science 2014-06-23 Chris J. Maddison , Daniel Tarlow

We introduce the first automated models for classifying natural language descriptions provided in cost documents called "Bills of Quantities" (BoQs) popular in the infrastructure construction industry, into the International Construction…

Computation and Language · Computer Science 2022-11-16 J. Ignacio Deza , Hisham Ihshaish , Lamine Mahdjoubi

We provide a comparative study between neural word representations and traditional vector spaces based on co-occurrence counts, in a number of compositional tasks. We use three different semantic spaces and implement seven tensor-based…

Computation and Language · Computer Science 2014-08-27 Dmitrijs Milajevs , Dimitri Kartsaklis , Mehrnoosh Sadrzadeh , Matthew Purver

Language models have demonstrated the ability to generate highly fluent text; however, it remains unclear whether their output retains coherent high-level structure (e.g., story progression). Here, we propose to apply a statistical tool,…

Computation and Language · Computer Science 2022-10-18 Yuntian Deng , Volodymyr Kuleshov , Alexander M. Rush

The syntactic structures of sentences can be readily read-out from the activations of large language models (LLMs). However, the ``structural probes'' that have been developed to reveal this phenomenon are typically evaluated on an…

Computation and Language · Computer Science 2025-08-12 Pablo J. Diego-Simón , Emmanuel Chemla , Jean-Rémi King , Yair Lakretz

A usage-based Construction Grammar (CxG) posits that slot-constraints generalize from common exemplar constructions. But what is the best model of constraint generalization? This paper evaluates competing frequency-based and…

Computation and Language · Computer Science 2019-04-12 Jonathan Dunn

There is much debate over the degree to which language learning is governed by innate language-specific biases, or acquired through cognition-general principles. Here we examine the probabilistic language acquisition hypothesis on three…

Computation and Language · Computer Science 2010-06-17 Anne S. Hsu , Nick Chater , Paul M. B. Vitanyi

Population protocols are a model of distributed computation intended for the study of networks of independent computing agents with dynamic communication structure. Each agent has a finite number of states, and communication opportunities…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-19 Mikhail Raskin