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A new language model for speech recognition is presented. The model develops hidden hierarchical syntactic-like structure incrementally and uses it to extract meaningful information from the word history, thus complementing the locality of…

Computation and Language · Computer Science 2007-05-23 Ciprian Chelba , Frederick Jelinek

Recent advancements in large language models (LLMs) have enhanced natural-language reasoning. However, their limited parametric memory and susceptibility to hallucination present persistent challenges for tasks requiring accurate,…

Computation and Language · Computer Science 2025-06-02 Yu-Hsuan Lin , Qian-Hui Chen , Yi-Jie Cheng , Jia-Ren Zhang , Yi-Hung Liu , Liang-Yu Hsia , Yun-Nung Chen

The aim of this paper is to introduce the notion of $a$-locally closed set by utilizing $a$-open sets defined by Ekici and to study some properties of this new notion. Also, some characterizations and many fundamental results regarding this…

General Topology · Mathematics 2024-08-07 Bilge İzci , Murad Özkoç

In everyday reasoning, when we think about a particular object, we associate it with a unique set of expected properties such as weight, size, or more abstract attributes like density or horsepower. These expectations are shaped by our…

Machine Learning · Computer Science 2025-07-01 Piotr Makarevich

Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommender systems - systems that are conversational, explainable,…

Information Retrieval · Computer Science 2024-08-06 Wensheng Lu , Jianxun Lian , Wei Zhang , Guanghua Li , Mingyang Zhou , Hao Liao , Xing Xie

We present a system for generating parsers based directly on the metaphor of parsing as deduction. Parsing algorithms can be represented directly as deduction systems, and a single deduction engine can interpret such deduction systems so as…

cmp-lg · Computer Science 2008-02-03 Stuart M. Shieber , Yves Schabes , Fernando C. N. Pereira

We propose a novel parameterized skill-learning algorithm that aims to learn transferable parameterized skills and synthesize them into a new action space that supports efficient learning in long-horizon tasks. We propose to leverage…

Machine Learning · Computer Science 2023-07-20 Haotian Fu , Shangqun Yu , Saket Tiwari , Michael Littman , George Konidaris

When training automated systems, it has been shown to be beneficial to adapt the representation of data by learning a problem-specific metric. This metric is global. We extend this idea and, for the widely used family of k nearest neighbors…

Machine Learning · Computer Science 2021-09-30 Jan Philip Göpfert , Heiko Wersing , Barbara Hammer

There are a few reasons for the recent increased interest in the study of local features of speech files. It is stated that many essential features of the speaker language used can appear in the form of the speech signal. The traditional…

Sound · Computer Science 2020-06-08 Rustam Latypov , Evgeni Stolov

Presented is a new method yielding parameterized solution to an interval parametric linear system. Some properties of this method are discussed. The solution enclosure it provides is compared to the enclosures by other methods. It is shown…

Numerical Analysis · Mathematics 2020-05-15 Evgenija D. Popova

This expository note introduces a normalization of the indexing of the lower and upper numbering ramification subgroups of local class field theory. We then look at how this normalization interacts with base change for Langlands parameters.

Number Theory · Mathematics 2025-09-19 Stephen DeBacker , David Schwein , Cheng-Chiang Tsai

A new understanding of the notion of regularizer is proposed. It is argued that this new notion is more realistic than the old one and better fits the practical computational needs. An example of the regularizer in the new sense is given. A…

Numerical Analysis · Mathematics 2025-10-20 A. G. Ramm

Pater's target article builds a persuasive case for establishing stronger ties between theoretical linguistics and connectionism (deep learning). This commentary extends his arguments to semantics, focusing in particular on issues of…

Computation and Language · Computer Science 2018-09-11 Christopher Potts

This survey paper aims at providing a "literary" anthology of mathematical morphology on graphs. It describes in the English language many ideas stemming from a large number of different papers, hence providing a unified view of an active…

Computer Vision and Pattern Recognition · Computer Science 2014-09-29 Laurent Najman , Jean Cousty

Lexical features are a major source of information in state-of-the-art coreference resolvers. Lexical features implicitly model some of the linguistic phenomena at a fine granularity level. They are especially useful for representing the…

Computation and Language · Computer Science 2017-04-25 Nafise Sadat Moosavi , Michael Strube

In the setting of minimal local grammar-based coding, the input string is represented as a grammar with the minimal output length defined via simple symbol-by-symbol encoding. This paper discusses four contributions to this field. First, we…

Information Theory · Computer Science 2025-04-17 Łukasz Dębowski

In this paper, we describe a new corpus-based approach to prepositional phrase attachment disambiguation, and present results comparing performance of this algorithm with other corpus-based approaches to this problem.

cmp-lg · Computer Science 2008-02-03 Eric Brill , Philip Resnik

We specify an algorithm that builds up a hierarchy of referential discourse segments from local centering data. The spatial extension and nesting of these discourse segments constrain the reachability of potential antecedents of an…

cmp-lg · Computer Science 2008-02-03 Udo Hahn , Michael Strube

This manuscript provides a short and practical introduction to the topic of language networks. This text aims at assisting researchers with no practical experience in text and/or network analysis. We provide a practical tutorial on how to…

Computation and Language · Computer Science 2020-10-15 Jorge A. V. Tohalino , Diego R. Amancio

Lexical Semantic Change Detection stands out as one of the few areas where Large Language Models (LLMs) have not been extensively involved. Traditional methods like PPMI, and SGNS remain prevalent in research, alongside newer BERT-based…

Computation and Language · Computer Science 2023-12-12 Ruiyu Wang , Matthew Choi
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