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Parsing Expression Grammars (PEGs) describe top-down parsers. Unfortunately, the error-reporting techniques used in conventional top-down parsers do not directly apply to parsers based on Parsing Expression Grammars (PEGs), so they have to…

Programming Languages · Computer Science 2016-07-14 André Murbach Maidl , Sérgio Medeiros , Fabio Mascarenhas , Roberto Ierusalimschy

The relationship between communicated language and intended meaning is often probabilistic and sensitive to context. Numerous strategies attempt to estimate such a mapping, often leveraging recursive Bayesian models of communication. In…

Computation and Language · Computer Science 2023-05-03 Benjamin Lipkin , Lionel Wong , Gabriel Grand , Joshua B Tenenbaum

How can we perform computations over natural language representations to solve tasks that require symbolic and numeric reasoning? We propose natural language embedded programs (NLEP) as a unifying framework for addressing math/symbolic…

Computation and Language · Computer Science 2024-04-01 Tianhua Zhang , Jiaxin Ge , Hongyin Luo , Yung-Sung Chuang , Mingye Gao , Yuan Gong , Xixin Wu , Yoon Kim , Helen Meng , James Glass

Cohesive powers of computable structures can be viewed as effective ultraproducts over effectively indecomposable sets called cohesive sets. We investigate the isomorphism types of cohesive powers $\Pi _{C}% \mathcal{L}$ for familiar…

Language models have primarily been evaluated with perplexity. While perplexity quantifies the most comprehensible prediction performance, it does not provide qualitative information on the success or failure of models. Another approach for…

Computation and Language · Computer Science 2018-04-25 Shuntaro Takahashi , Kumiko Tanaka-Ishii

Chain of thought is a natural inference-time method for increasing the computational power of transformer-based large language models (LLMs), but comes at the cost of sequential decoding. Are there more efficient alternatives to expand a…

Machine Learning · Computer Science 2025-11-07 William Merrill , Ashish Sabharwal

Large language models (LLMs) are the result of a massive experiment in bottom-up, data-driven reverse engineering of language at scale. Despite their utility in a number of downstream NLP tasks, ample research has shown that LLMs are…

Artificial Intelligence · Computer Science 2024-08-05 Walid S. Saba

We describe a parser of English effectuated by biologically plausible neurons and synapses, and implemented through the Assembly Calculus, a recently proposed computational framework for cognitive function. We demonstrate that this device…

Computation and Language · Computer Science 2021-08-05 Daniel Mitropolsky , Michael J. Collins , Christos H. Papadimitriou

P systems are computing conceptual computing devices that are at least as powerful as Turing machines. However, until recently it was not known how one can encode any recursive function as a P~system. Here we propose a new encoding of…

Formal Languages and Automata Theory · Computer Science 2018-09-25 Apostolos Syropoulos , Stratos Doumanis , Konstantinos T. Sotiriades

e use Prolog as a flexible meta-language to provide executable specifications of some fundamental mathematical objects and their transformations. In the process, isomorphisms are unraveled between natural numbers and combinatorial objects…

Programming Languages · Computer Science 2011-12-19 Paul Tarau

The article continues the study of the genus of regular languages that the authors introduced in a 2012 paper. Generalizing a previous result, we produce a new family of regular languages on a two-letter alphabet having arbitrary high…

Formal Languages and Automata Theory · Computer Science 2019-11-15 Guillaume Bonfante , Florian Deloup

Parsing is an important problem in computer science and yet surprisingly little attention has been devoted to its formal verification. In this paper, we present TRX: a parser interpreter formally developed in the proof assistant Coq,…

Logic in Computer Science · Computer Science 2015-07-01 Adam Koprowski , Henri Binsztok

Recurrent neural network grammars (RNNGs) are generative models of (tree,string) pairs that rely on neural networks to evaluate derivational choices. Parsing with them using beam search yields a variety of incremental complexity metrics…

Computation and Language · Computer Science 2018-06-12 John Hale , Chris Dyer , Adhiguna Kuncoro , Jonathan R. Brennan

Compositional generalization is a key ability of humans that enables us to learn new concepts from only a handful examples. Neural machine learning models, including the now ubiquitous Transformers, struggle to generalize in this way, and…

Machine Learning · Computer Science 2024-01-19 Tim Klinger , Luke Liu , Soham Dan , Maxwell Crouse , Parikshit Ram , Alexander Gray

Regular languages -- the languages accepted by deterministic finite automata -- are known to be precisely the languages recognized by finite monoids. This characterization is the origin of algebraic language theory. In this paper, we…

Formal Languages and Automata Theory · Computer Science 2025-05-06 Fabian Lenke , Stefan Milius , Henning Urbat , Thorsten Wißmann

This paper presents an extension of the GLL parsing algorithm for context-free grammars which also supports parsing expression grammars with ordered choice and lookahead. The new PEGLL algorithm retains support for unordered choice, and…

Formal Languages and Automata Theory · Computer Science 2022-08-29 Aaron Moss , Brynn Harrington , Emily Hoppe

Cohesive powers of computable structures are effective analogs of ultrapowers, where cohesive sets play the role of ultrafilters. Let $\omega$, $\zeta$, and $\eta$ denote the respective order-types of the natural numbers, the integers, and…

Sequence to sequence (seq2seq) models are often employed in settings where the target output is natural language. However, the syntactic properties of the language generated from these models are not well understood. We explore whether such…

Computation and Language · Computer Science 2018-09-07 Johnny Tian-Zheng Wei , Khiem Pham , Brian Dillon , Brendan O'Connor

Parse trees are fundamental syntactic structures in both computational linguistics and compilers construction. We argue in this paper that, in both fields, there are good incentives for model-checking sets of parse trees for some word…

Logic in Computer Science · Computer Science 2013-08-23 Anudhyan Boral , Sylvain Schmitz

Originally proposed for handling time series data, Auto-regressive Decision Trees (ARDTs) have not yet been explored for language modeling. This paper delves into both the theoretical and practical applications of ARDTs in this new context.…

Computation and Language · Computer Science 2024-10-01 Yulu Gan , Tomer Galanti , Tomaso Poggio , Eran Malach