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Related papers: A Study on Learnability for Rigid Lambek Grammars

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In this paper we propose a learning paradigm for the problem of understanding spoken language. The basis of the work is in a formalization of the understanding problem as a communication problem. This results in the definition of a…

cmp-lg · Computer Science 2008-02-03 Roberto Pieraccini , Esther Levin

Machine Reading Comprehension (MRC) is the task of answering a question over a paragraph of text. While neural MRC systems gain popularity and achieve noticeable performance, issues are being raised with the methodology used to establish…

Computation and Language · Computer Science 2020-03-11 Viktor Schlegel , Marco Valentino , André Freitas , Goran Nenadic , Riza Batista-Navarro

Polymodal provability logic GLP is incomplete w.r.t. Kripke frames. It is known to be complete w.r.t. topological semantics, where the diamond modalities correspond to topological derivative operations. However, the topologies needed for…

Logic · Mathematics 2024-07-16 Lev D. Beklemishev , Yunsong Wang

An important result from psycholinguistics (Griffiths & Kalish, 2005) states that no language can be learned iteratively by rational agents in a self-sustaining manner. We show how to modify the learning process slightly in order to achieve…

Optimization and Control · Mathematics 2016-09-14 Bernard Chazelle , Chu Wang

Recurrent neural network grammars (RNNG) are a recently proposed probabilistic generative modeling family for natural language. They show state-of-the-art language modeling and parsing performance. We investigate what information they…

Computation and Language · Computer Science 2017-01-12 Adhiguna Kuncoro , Miguel Ballesteros , Lingpeng Kong , Chris Dyer , Graham Neubig , Noah A. Smith

With the advent of large language models (LLMs), the trend in NLP has been to train LLMs on vast amounts of data to solve diverse language understanding and generation tasks. The list of LLM successes is long and varied. Nevertheless,…

Computation and Language · Computer Science 2023-06-22 Nicholas Asher , Swarnadeep Bhar , Akshay Chaturvedi , Julie Hunter , Soumya Paul

What counts as evidence for syntactic structure? In traditional generative grammar, systematic contrasts in grammaticality such as subject-auxiliary inversion and the licensing of parasitic gaps are taken as evidence for an internal,…

Computation and Language · Computer Science 2025-12-12 Lars G. B. Johnsen

We introduce the logical grammar emdebbing (LGE), a model inspired by pregroup grammars and categorial grammars to enable unsupervised inference of lexical categories and syntactic rules from a corpus of text. LGE produces comprehensible…

Computation and Language · Computer Science 2023-06-07 Sean Deyo , Veit Elser

A well-known approach to treating syntactic island constraints in the setting of Lambek grammars consists in adding specific bracket modalities to the logic. We adapt this approach to abstract categorial grammars (ACG). Thus we define…

Logic · Mathematics 2020-05-21 Sergey Slavnov

One of the challenges in language teaching is how best to organize rules regarding syntax, semantics, or phonology in a meaningful manner. This not only requires content creators to have pedagogical skills, but also have that language's…

Computation and Language · Computer Science 2023-10-31 Aditi Chaudhary , Arun Sampath , Ashwin Sheshadri , Antonios Anastasopoulos , Graham Neubig

Grammatical features across human languages show intriguing correlations often attributed to learning biases in humans. However, empirical evidence has been limited to experiments with highly simplified artificial languages, and whether…

Computation and Language · Computer Science 2025-02-19 Tianyang Xu , Tatsuki Kuribayashi , Yohei Oseki , Ryan Cotterell , Alex Warstadt

Despite the superior performance of large language models to generate natural language texts, it is hard to generate texts with correct logic according to a given task, due to the difficulties for neural models to capture implied rules from…

Computation and Language · Computer Science 2024-07-08 Fan Zhang , Kebing Jin , Hankz Hankui Zhuo

Word Embeddings are used widely in multiple Natural Language Processing (NLP) applications. They are coordinates associated with each word in a dictionary, inferred from statistical properties of these words in a large corpus. In this paper…

Computation and Language · Computer Science 2020-06-18 Adam Sutton , Nello Cristianini

We present a proof-theoretic analysis of the logic NL$\lambda$ (Barker \& Shan 2014, Barker 2019). We notably introduce a novel calculus of proof nets and prove it is sound and complete with respect to the sequent calculus for the logic. We…

Computation and Language · Computer Science 2020-10-26 Richard Moot

Controlled natural languages (CNL) with a direct mapping to formal logic have been proposed to improve the usability of knowledge representation systems, query interfaces, and formal specifications. Predictive editors are a popular approach…

Computation and Language · Computer Science 2013-03-12 Tobias Kuhn

One of the challenges of language teaching is how to organize the rules regarding syntax, semantics, or phonology of the language in a meaningful manner. This not only requires pedagogical skills, but also requires a deep understanding of…

Computation and Language · Computer Science 2022-06-13 Aditi Chaudhary , Arun Sampath , Ashwin Sheshadri , Antonios Anastasopoulos , Graham Neubig

In this article we show that hybrid type-logical grammars are a fragment of first-order linear logic. This embedding result has several important consequences: it not only provides a simple new proof theory for the calculus, thereby…

Logic in Computer Science · Computer Science 2014-05-27 Richard Moot

The ability to produce and understand an unlimited number of different sentences is a hallmark of human language. Linguists have sought to define the essence of this generative capacity using formal grammars that describe the syntactic…

Computation and Language · Computer Science 2022-09-22 Carlos Gómez-Rodríguez , Morten H. Christiansen , Ramon Ferrer-i-Cancho

A major target of linguistics and cognitive science has been to understand what class of learning systems can acquire the key structures of natural language. Until recently, the computational requirements of language have been used to argue…

Artificial Intelligence · Computer Science 2022-01-27 Yuan Yang

Curriculum learning is a widely adopted training strategy in natural language processing (NLP), where models are exposed to examples organized by increasing difficulty to enhance learning efficiency and performance. However, most existing…

Computation and Language · Computer Science 2025-07-15 Qi Feng , Yihong Liu , Hinrich Schütze