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相关论文: Metaphorical Paraphrase Generation: Feeding Metaph…

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This work describes the task of metaphoric paraphrase generation, in which we are given a literal sentence and are charged with generating a metaphoric paraphrase. We propose two different models for this task: a lexical replacement…

计算与语言 · 计算机科学 2020-03-02 Kevin Stowe , Leonardo Ribeiro , Iryna Gurevych

Generating metaphors is a challenging task as it requires a proper understanding of abstract concepts, making connections between unrelated concepts, and deviating from the literal meaning. In this paper, we aim to generate a metaphoric…

计算与语言 · 计算机科学 2021-04-13 Tuhin Chakrabarty , Xurui Zhang , Smaranda Muresan , Nanyun Peng

Metaphorical expressions are difficult linguistic phenomena, challenging diverse Natural Language Processing tasks. Previous works showed that paraphrasing a metaphor as its literal counterpart can help machines better process metaphors on…

计算与语言 · 计算机科学 2021-04-09 Rui Mao , Chenghua Lin , Frank Guerin

Paraphrasing is rooted in semantics. We show the effectiveness of transformers (Vaswani et al. 2017) for paraphrase generation and further improvements by incorporating PropBank labels via a multi-encoder. Evaluating on MSCOCO and…

计算与语言 · 计算机科学 2018-11-15 Su Wang , Rahul Gupta , Nancy Chang , Jason Baldridge

Generating metaphors is a difficult task as it requires understanding nuanced relationships between abstract concepts. In this paper, we aim to generate a metaphoric sentence given a literal expression by replacing relevant verbs. Guided by…

计算与语言 · 计算机科学 2021-06-03 Kevin Stowe , Tuhin Chakrabarty , Nanyun Peng , Smaranda Muresan , Iryna Gurevych

Literary tropes, from poetry to stories, are at the crux of human imagination and communication. Figurative language such as a simile go beyond plain expressions to give readers new insights and inspirations. In this paper, we tackle the…

计算与语言 · 计算机科学 2020-10-06 Tuhin Chakrabarty , Smaranda Muresan , Nanyun Peng

Paraphrase generation, a.k.a. paraphrasing, is a common and important task in natural language processing. Emotional paraphrasing, which changes the emotion embodied in a piece of text while preserving its meaning, has many potential…

计算与语言 · 计算机科学 2023-06-12 Justin J. Xie , Ameeta Agrawal

Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that transforms a literal sentence into three figurative variants: metonymic, metaphoric, and…

计算与语言 · 计算机科学 2026-04-21 Saptarshi Ghosh , Tianyu Jiang

Despite being a common figure of speech, hyperbole is under-researched in Figurative Language Processing. In this paper, we tackle the challenging task of hyperbole generation to transfer a literal sentence into its hyperbolic paraphrase.…

计算与语言 · 计算机科学 2022-05-05 Yunxiang Zhang , Xiaojun Wan

Automatic generation of paraphrases from a given sentence is an important yet challenging task in natural language processing (NLP), and plays a key role in a number of applications such as question answering, search, and dialogue. In this…

计算与语言 · 计算机科学 2018-08-24 Zichao Li , Xin Jiang , Lifeng Shang , Hang Li

Language enables humans to share knowledge, reason about the world, and pass on strategies for survival and innovation across generations. At the heart of this process is not just the ability to communicate but also the remarkable…

计算与语言 · 计算机科学 2026-02-25 Jan Philip Wahle

Verbal metonymy has received relatively scarce attention in the field of computational linguistics despite the fact that a model to accurately paraphrase metonymy has applications both in academia and the technology sector. The method…

计算与语言 · 计算机科学 2017-09-20 Alberto Morón Hernández

Natural language processing techniques are increasingly applied to identify social trends and predict behavior based on large text collections. Existing methods typically rely on surface lexical and syntactic information. Yet, research in…

计算与语言 · 计算机科学 2016-09-29 Ekaterina Shutova , Patricia Lichtenstein

Modern NLP defines the task of style transfer as modifying the style of a given sentence without appreciably changing its semantics, which implies that the outputs of style transfer systems should be paraphrases of their inputs. However,…

计算与语言 · 计算机科学 2020-10-13 Kalpesh Krishna , John Wieting , Mohit Iyyer

Contemporary research on computational processing of linguistic metaphors is divided into two main branches: metaphor recognition and metaphor interpretation. We take a different line of research and present an automated method for…

计算与语言 · 计算机科学 2014-09-29 Ekaterina Ovchinnikova , Vladimir Zaytsev , Suzanne Wertheim , Ross Israel

Natural Language Inference is an important task for Natural Language Understanding. It is concerned with classifying the logical relation between two sentences. In this paper, we propose several text generative neural networks for…

人工智能 · 计算机科学 2017-03-28 Janez Starc , Dunja Mladenić

Metaphor generation is a challenging task which can impact many downstream tasks such as improving user satisfaction with dialogue systems and story generation. This paper tackles the problem of Chinese nominal metaphor generation by…

计算与语言 · 计算机科学 2022-08-18 Yucheng Li , Chenghua Lin , Frank Geurin

At the intersection of creative text generation and literary theory, this study explores the role of literary metaphor and its capacity to generate a range of meanings. In this regard, literary metaphor is vital to the development of any…

计算与语言 · 计算机科学 2024-09-04 Imke van Heerden , Anil Bas

There are several linguistic claims about situations where words are more likely to be used as metaphors. However, few studies have sought to verify such claims with large corpora. This study entails a large-scale, corpus-based analysis of…

计算与语言 · 计算机科学 2024-04-02 Kotaro Aono , Ryohei Sasano , Koichi Takeda

An intuitive way for a human to write paraphrase sentences is to replace words or phrases in the original sentence with their corresponding synonyms and make necessary changes to ensure the new sentences are fluent and grammatically…

计算与语言 · 计算机科学 2018-06-22 Shaohan Huang , Yu Wu , Furu Wei , Ming Zhou
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