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Found 14 papers, 5 papers with code
Higher-Order DisCoCat (Peirce-Lambek-Montague semantics)
We propose a new definition of higher-order DisCoCat (categorical compositional distributional) models where the meaning of a word is not a diagram, but a diagram-valued higher-order function.
Category Theory for Quantum Natural Language Processing
The second chapter uses DisCopy to implement QNLP models as parameterised functors from grammar to quantum circuits.
lambeq: An Efficient High-Level Python Library for Quantum NLP
We present lambeq, the first high-level Python library for Quantum Natural Language Processing (QNLP).
How to make qubits speak
This is a story about making quantum computers speak, and doing so in a quantum-native, compositional and meaning-aware manner.
Functorial Language Models
We introduce functorial language models: a principled way to compute probability distributions over word sequences given a monoidal functor from grammar to meaning.
Diagrammatic Differentiation for Quantum Machine Learning
We introduce diagrammatic differentiation for tensor calculus by generalising the dual number construction from rigs to monoidal categories.
Grammar-aware sentence classification on quantum computers
In this work, we focus on the capabilities of noisy intermediate-scale quantum (NISQ) hardware and perform the first implementation of an NLP task on a NISQ processor, using the DisCoCat framework.
Foundations for Near-Term Quantum Natural Language Processing
We recall how the quantum model for natural language that we employ canonically combines linguistic meanings with rich linguistic structure, most notably grammar.
Functorial Language Games for Question Answering
We present some categorical investigations into Wittgenstein's language-games, with applications to game-theoretic pragmatics and question-answering in natural language processing.
Quantum Natural Language Processing on Near-Term Quantum Computers
In this work, we describe a full-stack pipeline for natural language processing on near-term quantum computers, aka QNLP.
DisCoPy: Monoidal Categories in Python
We introduce DisCoPy, an open source toolbox for computing with monoidal categories.
Category Theory
Incremental Monoidal Grammars
In this work we define formal grammars in terms of free monoidal categories, along with a functor from the category of formal grammars to the category of automata.
Functorial Question Answering
Distributional compositional (DisCo) models are functors that compute the meaning of a sentence from the meaning of its words.
Towards Compositional Distributional Discourse Analysis
Categorical compositional distributional semantics provide a method to derive the meaning of a sentence from the meaning of its individual words: the grammatical reduction of a sentence automatically induces a linear map for composing the word vectors obtained from distributional semantics.
