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We propose a categorial grammar based on classical multiplicative linear logic. This can be seen as an extension of abstract categorial grammars (ACG) and is at least as expressive. However, constituents of {\it linear logic grammars (LLG)}…

Logic · Mathematics 2020-08-04 Sergey Slavnov

This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up to a given degree, thus providing a more fine--grained…

Artificial Intelligence · Computer Science 2020-01-15 Anthony Hunter , Sylwia Polberg , Matthias Thimm

A number of cross-lingual transfer learning approaches based on neural networks have been proposed for the case when large amounts of parallel text are at our disposal. However, in many real-world settings, the size of parallel annotated…

Computation and Language · Computer Science 2020-01-31 Zuohui Fu , Yikun Xian , Shijie Geng , Yingqiang Ge , Yuting Wang , Xin Dong , Guang Wang , Gerard de Melo

We propose a new unsupervised method for lexical substitution using pre-trained language models. Compared to previous approaches that use the generative capability of language models to predict substitutes, our method retrieves substitutes…

Computation and Language · Computer Science 2022-09-20 Takashi Wada , Timothy Baldwin , Yuji Matsumoto , Jey Han Lau

To improve word representation learning, we propose a probabilistic prior which can be seamlessly integrated with word embedding models. Different from previous methods, word embedding is taken as a probabilistic generative model, and it…

Computation and Language · Computer Science 2023-09-22 Shaogang Ren , Dingcheng Li , Ping Li

We propose a concrete surface representation of abstract categorial grammars in the category of word cobordisms or cowordisms for short, which are certain bipartite graphs decorated with words in a given alphabet, generalizing linear logic…

Logic in Computer Science · Computer Science 2021-07-21 Sergey Slavnov

The transformer is a state-of-the-art neural translation model that uses attention to iteratively refine lexical representations with information drawn from the surrounding context. Lexical features are fed into the first layer and…

Computation and Language · Computer Science 2019-07-01 Denis Emelin , Ivan Titov , Rico Sennrich

The concept of paradeduction is presented in order to justify that we can overlook contradictory information taking into account only what is consistent. Besides that, paradeduction is used to show that there is a way to transform any…

Logic · Mathematics 2022-07-13 Edelcio G. de Souza , Alexandre Costa-Leite , Diogo H. B. Dias

Latent confounding has been a long-standing obstacle for causal reasoning from observational data. One popular approach is to model the data using acyclic directed mixed graphs (ADMGs), which describe ancestral relations between variables…

Machine Learning · Computer Science 2023-03-23 Matthew Ashman , Chao Ma , Agrin Hilmkil , Joel Jennings , Cheng Zhang

Formal and distributional semantic models offer complementary benefits in modeling meaning. The categorical compositional distributional (DisCoCat) model of meaning of Coecke et al. (arXiv:1003.4394v1 [cs.CL]) combines aspected of both to…

Computation and Language · Computer Science 2011-07-26 Edward Grefenstette , Mehrnoosh Sadrzadeh

Though there are some works on improving distributed word representations using lexicons, the improper overfitting of the words that have multiple meanings is a remaining issue deteriorating the learning when lexicons are used, which needs…

Computation and Language · Computer Science 2017-03-10 Yuanzhi Ke , Masafumi Hagiwara

Diagrammatic, analogical or iconic representations are often contrasted with linguistic or logical representations, in which the shape of the symbols is arbitrary. The aim of this paper is to make a case for the usefulness of diagrams in…

Computation and Language · Computer Science 2007-05-23 Catherine Recanati

Discourse relations bind smaller linguistic elements into coherent texts. However, automatically identifying discourse relations is difficult, because it requires understanding the semantics of the linked sentences. A more subtle challenge…

Computation and Language · Computer Science 2015-04-29 Yangfeng Ji , Jacob Eisenstein

The problem of explaining inconsistency-tolerant reasoning in knowledge bases (KBs) is a prominent topic in Artificial Intelligence (AI). While there is some work on this problem, the explanations provided by existing approaches often lack…

Artificial Intelligence · Computer Science 2025-02-18 Loan Ho , Stefan Schlobach

The cornerstone of multilingual neural translation is shared representations across languages. Given the theoretically infinite representation power of neural networks, semantically identical sentences are likely represented differently.…

Computation and Language · Computer Science 2022-11-21 Danni Liu , Jan Niehues

Word embeddings trained on large corpora have shown to encode high levels of unfair discriminatory gender, racial, religious and ethnic biases. In contrast, human-written dictionaries describe the meanings of words in a concise, objective…

Computation and Language · Computer Science 2021-01-26 Masahiro Kaneko , Danushka Bollegala

Crosslingual transfer is crucial to contemporary language models' multilingual capabilities, but how it occurs is not well understood. We ask what happens to a monolingual language model when it begins to be trained on a second language.…

Computation and Language · Computer Science 2025-06-05 Catherine Arnett , Tyler A. Chang , James A. Michaelov , Benjamin K. Bergen

In this paper, we present an analysis of computationally generated mixed-modality definite referring expressions using combinations of gesture and linguistic descriptions. In doing so, we expose some striking formal semantic properties of…

Computation and Language · Computer Science 2020-03-18 Nikhil Krishnaswamy , James Pustejovsky

We develop a model of abduction in abstract argumentation, where changes to an argumentation framework act as hypotheses to explain the support of an observation. We present dialogical proof theories for the main decision problems (i.e.,…

Artificial Intelligence · Computer Science 2014-07-16 Richard Booth , Dov Gabbay , Souhila Kaci , Tjitze Rienstra , Leendert van der Torre

Beyond word embeddings, continuous representations of knowledge graph (KG) components, such as entities, types and relations, are widely used for entity mention disambiguation, relation inference and deep question answering. Great strides…

Information Retrieval · Computer Science 2018-05-15 Sandeep Subramanian , Soumen Chakrabarti
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