105 citations · 335 across the 21 of their papers we have counts for
24 papers
lambeq: An Efficient High-Level Python Library for Quantum NLP
Dimitri Kartsaklis, Ian Fan, Richie Yeung +7
We present lambeq, the first high-level Python library for Quantum Natural Language Processing (QNLP). The open-source toolkit offers a detailed hierarchy of modules and classes im…
A CCG-Based Version of the DisCoCat Framework
Richie Yeung, Dimitri Kartsaklis
While the DisCoCat model (Coecke et al., 2010) has been proved a valuable tool for studying compositional aspects of language at the level of semantics, its strong dependency on pr…
QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer
Robin Lorenz, Anna Pearson, Konstantinos Meichanetzidis +2
Quantum Natural Language Processing (QNLP) deals with the design and implementation of NLP models intended to be run on quantum hardware. In this paper, we present results on the f…
Conversational Semantic Parsing for Dialog State Tracking
Jianpeng Cheng, Devang Agrawal, Hector Martinez Alonso +12
We consider a new perspective on dialog state tracking (DST), the task of estimating a user's goal through the course of a dialog. By formulating DST as a semantic parsing task ove…
Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces
Victor Prokhorov, Mohammad Taher Pilehvar, Dimitri Kartsaklis +2
Word embedding techniques heavily rely on the abundance of training data for individual words. Given the Zipfian distribution of words in natural language texts, a large number of…
Proceedings of the 2018 Workshop on Compositional Approaches in Physics, NLP, and Social Sciences
Martha Lewis, Bob Coecke, Jules Hedges +2
The ability to compose parts to form a more complex whole, and to analyze a whole as a combination of elements, is desirable across disciplines. This workshop bring together resear…
Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models
Mohammad Taher Pilehvar, Dimitri Kartsaklis, Victor Prokhorov +1
Rare word representation has recently enjoyed a surge of interest, owing to the crucial role that effective handling of infrequent words can play in accurate semantic understanding…
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
Dimitri Kartsaklis, Mohammad Taher Pilehvar, Nigel Collier
This paper addresses the problem of mapping natural language text to knowledge base entities. The mapping process is approached as a composition of a phrase or a sentence into a po…
Learning Rare Word Representations using Semantic Bridging
Victor Prokhorov, Mohammad Taher Pilehvar, Dimitri Kartsaklis +2
We propose a methodology that adapts graph embedding techniques (DeepWalk (Perozzi et al., 2014) and node2vec (Grover and Leskovec, 2016)) as well as cross-lingual vector space map…
Linguistic Matrix Theory
Dimitrios Kartsaklis, Sanjaye Ramgoolam, Mehrnoosh Sadrzadeh
Recent research in computational linguistics has developed algorithms which associate matrices with adjectives and verbs, based on the distribution of words in a corpus of text. Th…
Distributional Inclusion Hypothesis for Tensor-based Composition
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
According to the distributional inclusion hypothesis, entailment between words can be measured via the feature inclusions of their distributional vectors. In recent work, we showed…
Proceedings of the 2016 Workshop on Semantic Spaces at the Intersection of NLP, Physics and Cognitive Science
Dimitrios Kartsaklis, Martha Lewis, Laura Rimell
This volume contains the Proceedings of the 2016 Workshop on Semantic Spaces at the Intersection of NLP, Physics and Cognitive Science (SLPCS 2016), which was held on the 11th of J…
Coordination in Categorical Compositional Distributional Semantics
Dimitri Kartsaklis
An open problem with categorical compositional distributional semantics is the representation of words that are considered semantically vacuous from a distributional perspective, s…
Sentence Entailment in Compositional Distributional Semantics
Esma Balkir, Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
Distributional semantic models provide vector representations for words by gathering co-occurrence frequencies from corpora of text. Compositional distributional models extend thes…
Syntax-Aware Multi-Sense Word Embeddings for Deep Compositional Models of Meaning
Jianpeng Cheng, Dimitri Kartsaklis
Deep compositional models of meaning acting on distributional representations of words in order to produce vectors of larger text constituents are evolving to a popular area of NLP…
A Frobenius Model of Information Structure in Categorical Compositional Distributional Semantics
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
The categorical compositional distributional model of Coecke, Sadrzadeh and Clark provides a linguistically motivated procedure for computing the meaning of a sentence as a functio…
Compositional Distributional Semantics with Compact Closed Categories and Frobenius Algebras
Dimitri Kartsaklis
This thesis contributes to ongoing research related to the categorical compositional model for natural language of Coecke, Sadrzadeh and Clark in three ways: Firstly, I propose a c…
Open System Categorical Quantum Semantics in Natural Language Processing
Robin Piedeleu, Dimitri Kartsaklis, Bob Coecke +1
Originally inspired by categorical quantum mechanics (Abramsky and Coecke, LiCS'04), the categorical compositional distributional model of natural language meaning of Coecke, Sadrz…
Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning
Jianpeng Cheng, Dimitri Kartsaklis, Edward Grefenstette
This paper aims to explore the effect of prior disambiguation on neural network- based compositional models, with the hope that better semantic representations for text compounds c…
Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis, Nal Kalchbrenner, Mehrnoosh Sadrzadeh
This paper provides a method for improving tensor-based compositional distributional models of meaning by the addition of an explicit disambiguation step prior to composition. In c…
Evaluating Neural Word Representations in Tensor-Based Compositional Settings
Dmitrijs Milajevs, Dimitri Kartsaklis, Mehrnoosh Sadrzadeh +1
We provide a comparative study between neural word representations and traditional vector spaces based on co-occurrence counts, in a number of compositional tasks. We use three dif…
A Study of Entanglement in a Categorical Framework of Natural Language
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh
In both quantum mechanics and corpus linguistics based on vector spaces, the notion of entanglement provides a means for the various subsystems to communicate with each other. In t…
Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras
Dimitri Kartsaklis, Mehrnoosh Sadrzadeh, Stephen Pulman +1
Compact closed categories have found applications in modeling quantum information protocols by Abramsky-Coecke. They also provide semantics for Lambek's pregroup algebras, applied…
Compositional Operators in Distributional Semantics
Dimitri Kartsaklis
This survey presents in some detail the main advances that have been recently taking place in Computational Linguistics towards the unification of the two prominent semantic paradi…