Search Results for author: Stuart E. Middleton

Found 3 papers, 1 papers with code

IDN-Sum: A New Dataset for Interactive Digital Narrative Extractive Text Summarisation

1 code implementation COLING (CreativeSumm) 2022 Ashwathy T. Revi, Stuart E. Middleton, David E. Millard

In this paper, we describe the first IDN dataset (IDN-Sum) designed specifically for training and testing IDN text summarization algorithms.

Extractive Text Summarization

Do prompt positions really matter?

no code implementations23 May 2023 Junyu Mao, Stuart E. Middleton, Mahesan Niranjan

Prompt-based models have gathered a lot of attention from researchers due to their remarkable advancements in the fields of zero-shot and few-shot learning.

Few-Shot Learning Natural Language Understanding +2

Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model

no code implementations8 Dec 2020 Ryan Beal, Stuart E. Middleton, Timothy J. Norman, Sarvapali D. Ramchurn

In this paper, we present a new application-focused benchmark dataset and results from a set of baseline Natural Language Processing and Machine Learning models for prediction of match outcomes for games of football (soccer).

BIG-bench Machine Learning

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