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An interesting line of research in natural language processing (NLP) aims to incorporate linguistic typology to bridge linguistic diversity and assist the research of low-resource languages. While most works construct linguistic similarity…

Computation and Language · Computer Science 2023-05-24 Haotian Ye , Yihong Liu , Hinrich Schütze

We regard explanations as a blending of the input sample and the model's output and offer a few definitions that capture various desired properties of the function that generates these explanations. We study the links between these…

Machine Learning · Computer Science 2020-01-16 Lior Wolf , Tomer Galanti , Tamir Hazan

Model interpretability methods are often used to explain NLP model decisions on tasks such as text classification, where the output space is relatively small. However, when applied to language generation, where the output space often…

Computation and Language · Computer Science 2022-05-24 Kayo Yin , Graham Neubig

In interactions between users and language model agents, user utterances frequently exhibit ellipsis (omission of words or phrases) or imprecision (lack of exactness) to prioritize efficiency. This can lead to varying interpretations of the…

Computation and Language · Computer Science 2024-10-07 Hyuhng Joon Kim , Youna Kim , Cheonbok Park , Junyeob Kim , Choonghyun Park , Kang Min Yoo , Sang-goo Lee , Taeuk Kim

A fundamental result in psycholinguistics is that less predictable words take a longer time to process. One theoretical explanation for this finding is Surprisal Theory (Hale, 2001; Levy, 2008), which quantifies a word's predictability as…

Computation and Language · Computer Science 2025-04-15 Ethan Gotlieb Wilcox , Tiago Pimentel , Clara Meister , Ryan Cotterell , Roger P. Levy

We propose two new conformity scores for conformal prediction, in a general multivariate regression framework. The underlying score functions are based on a covariance analysis of the residuals and the input points. We give theoretical…

Statistics Theory · Mathematics 2025-06-30 Iain Henderson , Adrien Mazoyer , Fabrice Gamboa

Spurious correlations occur when a model learns unreliable features from the data and are a well-known drawback of data-driven learning. Although there are several algorithms proposed to mitigate it, we are yet to jointly derive the…

Machine Learning · Computer Science 2023-08-23 Gautam Sreekumar , Vishnu Naresh Boddeti

This paper introduces an objective metric for evaluating a parsing scheme. It is based on Shannon's original work with letter sequences, which can be extended to part-of-speech tag sequences. It is shown that this regular language is an…

cmp-lg · Computer Science 2008-02-03 Caroline Lyon , Stephen Brown

We investigate structural implications arising from the condition that a given directed graph does not interpret, in the sense of primitive positive interpretation with parameters or orbits, every finite structure. Our results generalize…

Logic in Computer Science · Computer Science 2023-02-24 Libor Barto , Bertalan Bodor , Marcin Kozik , Antoine Mottet , Michael Pinsker

Evaluating whether large language models (LLMs) capture the structure of natural language beyond local fluency remains an open challenge. Existing evaluation methods, largely based on task performance or short-context behavior, provide…

Computation and Language · Computer Science 2026-05-26 Kumiko Tanaka-Ishii

Neural semantic parsers have shown good overall performance for a variety of linguistic phenomena, reaching semantic matching scores of more than 90%. But how do such parsers perform on strongly context-sensitive phenomena, where large…

Computation and Language · Computer Science 2025-08-21 Xiao Zhang , Johan bos

Most words have several senses and connotations which evolve in time due to semantic shift, so that closely related words may gain different or even opposite meanings over the years. This evolution is very relevant to the study of language…

Computation and Language · Computer Science 2018-05-31 Jean-François Delpech

Implicit arguments, which cannot be detected solely through syntactic cues, make it harder to extract predicate-argument tuples. We present a new model for implicit argument prediction that draws on reading comprehension, casting the…

Computation and Language · Computer Science 2018-11-09 Pengxiang Cheng , Katrin Erk

The social and implicit nature of human communication ramifies readers' understandings of written sentences. Single gold-standard interpretations rarely exist, challenging conventional assumptions in natural language processing. This work…

Computation and Language · Computer Science 2023-12-08 Liesbeth Allein , Maria Mihaela Truşcǎ , Marie-Francine Moens

We propose a straightforward extension of symbolic transfer entropy to enable the investigation of delayed directional relationships between coupled dynamical systems from time series. Analyzing time series from chaotic model systems, we…

Neurons and Cognition · Quantitative Biology 2016-10-10 Henning Dickten , Klaus Lehnertz

We consider shift spaces in which elements of the alphabet may overlap nontransitively. We define a notion of entropy for such spaces, give several techniques for computing lower bounds for it, and show that it is equal to a limit of…

Dynamical Systems · Mathematics 2010-11-16 Fabio Drucker , David Richeson , Jim Wiseman

A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of…

Artificial Intelligence · Computer Science 2013-03-25 Henry E. Kyburg

Natural language contexts display logical regularities with respect to substitutions of related concepts: these are captured in a functional order-theoretic property called monotonicity. For a certain class of NLI problems where the…

Computation and Language · Computer Science 2021-05-18 Julia Rozanova , Deborah Ferreira , Mokanarangan Thayaparan , Marco Valentino , André Freitas

Dependency syntax represents the structure of a sentence as a tree composed of dependencies, i.e., directed relations between lexical units. While in its more general form any such tree is allowed, in practice many are not plausible or are…

Computation and Language · Computer Science 2026-04-07 Gómez-Rodríguez , Carlos , Alemany-Puig , Lluís

Revealing the implicit semantic relation between the constituents of a noun-compound is important for many NLP applications. It has been addressed in the literature either as a classification task to a set of pre-defined relations or by…

Computation and Language · Computer Science 2018-05-08 Vered Shwartz , Ido Dagan
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