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Related papers: Syntactic-Head-Driven Generation

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Constraint-based grammars can, in principle, serve as the major linguistic knowledge source for both parsing and generation. Surface generation starts from input semantics representations that may vary across grammars. For many declarative…

Computation and Language · Computer Science 2007-05-23 Stephan Busemann

The distributed representations currently used are dense and uninterpretable, leading to interpretations that themselves are relative, overcomplete, and hard to interpret. We propose a method that transforms these word vectors into reduced…

Computation and Language · Computer Science 2024-11-14 Biraj Silwal

Most existing text generation models follow the sequence-to-sequence paradigm. Generative Grammar suggests that humans generate natural language texts by learning language grammar. We propose a syntax-guided generation schema, which…

Computation and Language · Computer Science 2023-06-27 Yafu Li , Leyang Cui , Jianhao Yan , Yongjing Yin , Wei Bi , Shuming Shi , Yue Zhang

Recall the classical text generation works, the generation framework can be briefly divided into two phases: \textbf{idea reasoning} and \textbf{surface realization}. The target of idea reasoning is to figure out the main idea which will be…

Computation and Language · Computer Science 2021-08-09 Wei Wang , Piji Li , Hai-Tao Zheng

Children learning their first language face multiple problems of induction: how to learn the meanings of words, and how to build meaningful phrases from those words according to syntactic rules. We consider how children might solve these…

Computation and Language · Computer Science 2018-05-15 Jon Gauthier , Roger Levy , Joshua B. Tenenbaum

The dominant language modeling paradigm handles text as a sequence of discrete tokens. While that approach can capture the latent structure of the text, it is inherently constrained to sequential dynamics for text generation. We propose a…

Computation and Language · Computer Science 2020-11-02 Noe Casas , José A. R. Fonollosa , Marta R. Costa-jussà

Although many AI applications of interest require specialized multi-modal models, relevant data to train such models is inherently scarce or inaccessible. Filling these gaps with human annotators is prohibitively expensive, error-prone, and…

Artificial Intelligence · Computer Science 2026-04-01 Tim R. Davidson , Benoit Seguin , Enrico Bacis , Cesar Ilharco , Hamza Harkous

Modern conversational AI systems support natural language understanding for a wide variety of capabilities. While a majority of these tasks can be accomplished using a simple and flat representation of intents and slots, more sophisticated…

Computation and Language · Computer Science 2020-11-05 Ke Tran , Ming Tan

We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic tags assigned to the target-language training texts…

Generating from Abstract Meaning Representation (AMR) is an underspecified problem, as many syntactic decisions are not constrained by the semantic graph. To explicitly account for this underspecification, we break down generating from AMR…

Computation and Language · Computer Science 2019-04-04 Kris Cao , Stephen Clark

Most generative document models act on bag-of-words input in an attempt to focus on the semantic content and thereby partially forego syntactic information. We argue that it is preferable to keep the original word order intact and…

Computation and Language · Computer Science 2018-06-06 Erik Holmer , Andreas Marfurt

Syntactic parsing is the task of assigning a syntactic structure to a sentence. There are two popular syntactic parsing methods: constituency and dependency parsing. Recent works have used syntactic embeddings based on constituency trees,…

Computation and Language · Computer Science 2023-02-20 Subba Reddy Oota , Mounika Marreddy , Manish Gupta , Bapi Raju Surampud

To harness the power of large language models in safety-critical domains, we need to ensure the explainability of their predictions. However, despite the significant attention to model interpretability, there remains an unexplored domain in…

Computation and Language · Computer Science 2024-06-04 Kenza Amara , Rita Sevastjanova , Mennatallah El-Assady

While deep generative models are showing exciting abilities in computer vision and natural language processing, their adoption in communication frameworks is still far underestimated. These methods are demonstrated to evolve solutions to…

Computation and Language · Computer Science 2024-01-17 Eleonora Grassucci , Jihong Park , Sergio Barbarossa , Seong-Lyun Kim , Jinho Choi , Danilo Comminiello

Syntactic bootstrapping (Gleitman, 1990) is the hypothesis that children use the syntactic environments in which a verb occurs to learn its meaning. In this paper, we examine whether large language models exhibit a similar behavior. We do…

Computation and Language · Computer Science 2025-08-19 Xiaomeng Zhu , R. Thomas McCoy , Robert Frank

As digital technologies advance, communication networks face challenges in handling the vast data generated by intelligent devices. Autonomous vehicles, smart sensors, and IoT systems necessitate new paradigms. This thesis addresses these…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Francesco Pezone

Headline generation aims to summarize a long document with a short, catchy title that reflects the main idea. This requires accurately capturing the core document semantics, which is challenging due to the lengthy and background…

Computation and Language · Computer Science 2024-03-26 Minghui Xu , Hao Fei , Fei Li , Shengqiong Wu , Rui Sun , Chong Teng , Donghong Ji

The standard tabulation techniques for logic programming presuppose fixed order of computation. Some data-driven control should be introduced in order to deal with diverse contexts. The present paper describes a data-driven method of…

Computation and Language · Computer Science 2007-05-23 Koiti Hasida , Takashi Miyata

Writing style is a combination of consistent decisions at different levels of language production including lexical, syntactic, and structural associated to a specific author (or author groups). While lexical-based models have been widely…

Computation and Language · Computer Science 2019-02-28 Fereshteh Jafariakinabad , Sansiri Tarnpradab , Kien A. Hua

Syntax is usually studied in the realm of linguistics and refers to the arrangement of words in a sentence. Similarly, an image can be considered as a visual 'sentence', with the semantic parts of the image acting as 'words'. While visual…

Computer Vision and Pattern Recognition · Computer Science 2024-02-01 Sayeed Shafayet Chowdhury , Soumyadeep Chandra , Kaushik Roy
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