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Related papers: Learning Lambek grammars from proof frames

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The Random Language Model (De Giuli 2019) is an ensemble of stochastic context-free grammars, quantifying the syntax of human and computer languages. The model suggests a simple picture of first language learning as a type of annealing in…

Disordered Systems and Neural Networks · Physics 2024-12-10 Fatemeh Lalegani , Eric De Giuli

In the last years there has been a growing interest in the study of learning problems associated with algebraic structures. The framework we use models the scenario in which a learner is given larger and larger fragments of a structure from…

Many applications require categorization of text documents using predefined categories. The main approach to performing text categorization is learning from labeled examples. For many tasks, it may be difficult to find examples in one…

Computation and Language · Computer Science 2018-02-13 Sarai Duek , Shaul Markovitch

We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most $\ell.$ The goal is to learn a cover context-free…

Formal Languages and Automata Theory · Computer Science 2014-04-10 Mircea Marin , Gabriel Istrate

We propose a scalable framework for deciding, proving, and explaining (in-)equivalence of context-free grammars. We present an implementation of the framework and evaluate it on large data sets collected within educational support systems.…

Formal Languages and Automata Theory · Computer Science 2026-04-09 Marko Schmellenkamp , Thomas Zeume , Sven Argo , Sandra Kiefer , Cedric Siems , Fynn Stebel

This paper solves an open problem concerning the generative power of nonerasing context-free rewriting systems using a simple mechanism for checking for context dependencies, in the literature known as semi-conditional grammars of degree…

Formal Languages and Automata Theory · Computer Science 2010-04-22 Tomas Masopust

This article addresses Second Language (L2) writing development through an investigation of new grammatical and structural complexity metrics. We explore the paradigmatic production in learner English by linking language functions to…

Computation and Language · Computer Science 2025-03-17 Cyriel Mallart , Andrew Simpkin , Nicolas Ballier , Paula Lissón , Rémi Venant , Jen-Yu Li , Bernardo Stearns , Thomas Gaillat

This paper presents Arvada, an algorithm for learning context-free grammars from a set of positive examples and a Boolean-valued oracle. Arvada learns a context-free grammar by building parse trees from the positive examples. Starting from…

Software Engineering · Computer Science 2021-08-31 Neil Kulkarni , Caroline Lemieux , Koushik Sen

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

We classify essential algebras whose irredundant non-refinable covers consist of primal algebras. The proof is obtained by constructing one to one correspondence between such algebras and partial orders on finite sets. Further, we prove…

Logic · Mathematics 2014-06-26 Shohei Izawa

Zero-shot Learners are models capable of predicting unseen classes. In this work, we propose a Zero-shot Learning approach for text categorization. Our method involves training model on a large corpus of sentences to learn the relationship…

Computation and Language · Computer Science 2017-12-27 Pushpankar Kumar Pushp , Muktabh Mayank Srivastava

We propose a segmental neural language model that combines the generalization power of neural networks with the ability to discover word-like units that are latent in unsegmented character sequences. In contrast to previous segmentation…

Computation and Language · Computer Science 2019-06-19 Kazuya Kawakami , Chris Dyer , Phil Blunsom

Concept Bottleneck Models (CBMs) are regarded as inherently interpretable because they first predict a set of human-defined concepts which are used to predict a task label. For inherent interpretability to be fully realised, and ensure…

Machine Learning · Computer Science 2024-07-31 Jack Furby , Daniel Cunnington , Dave Braines , Alun Preece

Motivated by problems in online advertising, we address the task of Learning from Label Proportions (LLP). We introduce a novel and versatile low-variance debiasing methodology to learn from aggregate label information, significantly…

Machine Learning · Computer Science 2026-02-02 Lorne Applebaum , Travis Dick , Claudio Gentile , Haim Kaplan , Tomer Koren

Grounded language models use external sources of information, such as knowledge graphs, to meet some of the general challenges associated with pre-training. By extending previous work on compositional generalization in semantic parsing, we…

Computation and Language · Computer Science 2024-06-10 Sondre Wold , Étienne Simon , Lucas Georges Gabriel Charpentier , Egor V. Kostylev , Erik Velldal , Lilja Øvrelid

A natural next step in the evolution of constraint-based grammar formalisms from rewriting formalisms is to abstract fully away from the details of the grammar mechanism---to express syntactic theories purely in terms of the properties of…

cmp-lg · Computer Science 2008-02-03 James Rogers

We introduce and elaborate a novel formalism for the manipulation and analysis of proofs as objects in a global manner. In this first approach the formalism is restricted to first-order problems characterized by condensed detachment. It is…

Logic in Computer Science · Computer Science 2024-10-31 Christoph Wernhard , Wolfgang Bibel

The paper presents a solution to the long-standing question about the decidability of the two-variable fragment of the superintuitionistic predicate logic $\mathbf{QLC}$ defined by the class of linear Kripke frames, which is also the…

Logic · Mathematics 2025-10-06 Mikhail Rybakov

The grammatical knowledge of language models (LMs) is often measured using a benchmark of linguistic minimal pairs, where the LMs are presented with a pair of acceptable and unacceptable sentences and required to judge which is more…

Computation and Language · Computer Science 2025-02-10 Yusuke Ide , Yuto Nishida , Justin Vasselli , Miyu Oba , Yusuke Sakai , Hidetaka Kamigaito , Taro Watanabe

Under categorial grammars that have powerful rules like composition, a simple n-word sentence can have exponentially many parses. Generating all parses is inefficient and obscures whatever true semantic ambiguities are in the input. This…

cmp-lg · Computer Science 2008-02-03 Jason Eisner