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Knowing which words have been attended to in previous time steps while generating a translation is a rich source of information for predicting what words will be attended to in the future. We improve upon the attention model of Bahdanau et…

Neural and Evolutionary Computing · Computer Science 2016-07-19 Zichao Yang , Zhiting Hu , Yuntian Deng , Chris Dyer , Alex Smola

The long-distance agreement, evidence for syntactic structure, is increasingly used to assess the syntactic generalization of Neural Language Models. Much work has shown that transformers are capable of high accuracy in varied agreement…

Computation and Language · Computer Science 2023-01-05 Bingzhi Li , Guillaume Wisniewski , Benoît Crabbé

Modeling the structure of coherent texts is a key NLP problem. The task of coherently organizing a given set of sentences has been commonly used to build and evaluate models that understand such structure. We propose an end-to-end…

Computation and Language · Computer Science 2017-12-25 Lajanugen Logeswaran , Honglak Lee , Dragomir Radev

Combining the representations of the words that make up a sentence into a cohesive whole is difficult, since it needs to account for the order of words, and to establish how the words present relate to each other. The solution we propose…

Computation and Language · Computer Science 2021-03-04 Diego Maupomé , Marie-Jean Meurs

The paper reports on a series of experiments aiming at probing LeBenchmark, a pretrained acoustic model trained on 7k hours of spoken French, for syntactic information. Pretrained acoustic models are increasingly used for downstream speech…

Computation and Language · Computer Science 2024-03-05 Zdravko Dugonjić , Adrien Pupier , Benjamin Lecouteux , Maximin Coavoux

A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract meaningful information from the word history - thus enabling the…

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

Open information extraction (IE) is the task of extracting open-domain assertions from natural language sentences. A key step in open IE is confidence modeling, ranking the extractions based on their estimated quality to adjust precision…

Computation and Language · Computer Science 2019-06-03 Zhengbao Jiang , Pengcheng Yin , Graham Neubig

Distributed representation plays an important role in deep learning based natural language processing. However, the representation of a sentence often varies in different tasks, which is usually learned from scratch and suffers from the…

Computation and Language · Computer Science 2018-04-24 Renjie Zheng , Junkun Chen , Xipeng Qiu

Linguistic analysis of language models is one of the ways to explain and describe their reasoning, weaknesses, and limitations. In the probing part of the model interpretability research, studies concern individual languages as well as…

Computation and Language · Computer Science 2022-10-25 Oleg Serikov , Vitaly Protasov , Ekaterina Voloshina , Viktoria Knyazkova , Tatiana Shavrina

Context information around words helps in determining their actual meaning, for example "networks" used in contexts of artificial neural networks or biological neuron networks. Generative topic models infer topic-word distributions, taking…

Information Retrieval · Computer Science 2018-08-14 Pankaj Gupta , Florian Buettner , Hinrich Schütze

A critical part of reading is being able to understand the temporal relationships between events described in a passage of text, even when those relationships are not explicitly stated. However, current machine reading comprehension…

Computation and Language · Computer Science 2020-10-07 Qiang Ning , Hao Wu , Rujun Han , Nanyun Peng , Matt Gardner , Dan Roth

To address the need for a more comprehensive evaluation of French Natural Language Understanding (NLU), we introduce COLE, a new benchmark composed of 23 diverse task covering a broad range of NLU capabilities, including sentiment analysis,…

Computation and Language · Computer Science 2025-10-08 David Beauchemin , Yan Tremblay , Mohamed Amine Youssef , Richard Khoury

We investigate an extension of continuous online learning in recurrent neural network language models. The model keeps a separate vector representation of the current unit of text being processed and adaptively adjusts it after each…

Computation and Language · Computer Science 2017-03-07 Marek Rei

In this work, we aim at developing an extractive summarizer in the multi-document setting. We implement a rank based sentence selection using continuous vector representations along with key-phrases. Furthermore, we propose a model to…

Computation and Language · Computer Science 2020-06-26 Mir Tafseer Nayeem , Yllias Chali

Multimodal relation extraction (MRE) is the task of identifying the semantic relationships between two entities based on the context of the sentence image pair. Existing retrieval-augmented approaches mainly focused on modeling the…

Computation and Language · Computer Science 2023-05-26 Xuming Hu , Zhijiang Guo , Zhiyang Teng , Irwin King , Philip S. Yu

In this paper we present REG, a graph-based approach for study a fundamental problem of Natural Language Processing (NLP): the automatic text summarization. The algorithm maps a document as a graph, then it computes the weight of their…

Computation and Language · Computer Science 2015-01-07 Juan-Manuel Torres-Moreno , Javier Ramirez , Iria da Cunha

Recurrent neural networks (RNNs) have long been an architecture of interest for computational models of human sentence processing. The recently introduced Transformer architecture outperforms RNNs on many natural language processing tasks…

Computation and Language · Computer Science 2022-03-31 Danny Merkx , Stefan L. Frank

This report specifies an observational semantics and gives an original presentation of the Byrd's box model. The approach accounts for the semantics of Prolog tracers independently of a particular implementation. Traces are, in general,…

Programming Languages · Computer Science 2007-06-25 Pierre Deransart , Mireille Ducassé , Gérard Ferrand

General treebank analyses are graph structured, but parsers are typically restricted to tree structures for efficiency and modeling reasons. We propose a new representation and algorithm for a class of graph structures that is flexible…

Computation and Language · Computer Science 2020-06-05 Jonathan K. Kummerfeld , Dan Klein

We present a new English-French test set for the evaluation of Machine Translation (MT) for informal, written bilingual dialogue. The test set contains 144 spontaneous dialogues (5,700+ sentences) between native English and French speakers,…

Computation and Language · Computer Science 2019-06-03 Rachel Bawden , Sophie Rosset , Thomas Lavergne , Eric Bilinski