no code implementations • EACL (WANLP) 2021 • Abdullah I. Alharbi, Mark Lee
Sarcasm detection and sentiment analysis are important tasks in Natural Language Understanding.
2 code implementations • EACL (WANLP) 2021 • Alaa Alharbi, Mark Lee
Exploration of this content revealed the most discussed topics and information types, and the paper presents a labelled dataset from seven emergency events that serves as a gold standard for several tasks in crisis informatics research.
no code implementations • NAACL (SMM4H) 2021 • Frances Adriana Laureano De Leon, Harish Tayyar Madabushi, Mark Lee
This paper describes the participation of the UoB-NLP team in the ProfNER-ST shared subtask 7a.
1 code implementation • COLING (TextGraphs) 2022 • Tuba Gokhan, Phillip Smith, Mark Lee
In this paper, we develop a Graph-Based Unsupervised Summarization(GUSUM) method for extractive text summarization based on the principle of including the most important sentences while excluding sentences with similar meanings in the summary.
no code implementations • OSACT (LREC) 2022 • Alaa Alharbi, Mark Lee
User-generated Social Media (SM) content has been explored as a valuable and accessible source of data about crises to enhance situational awareness and support humanitarian response efforts.
no code implementations • 14 Mar 2024 • Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier, Sam Dodge, BoWen Zhang, Philipp Dufter, Dhruti Shah, Xianzhi Du, Futang Peng, Floris Weers, Anton Belyi, Haotian Zhang, Karanjeet Singh, Doug Kang, Ankur Jain, Hongyu Hè, Max Schwarzer, Tom Gunter, Xiang Kong, Aonan Zhang, Jianyu Wang, Chong Wang, Nan Du, Tao Lei, Sam Wiseman, Guoli Yin, Mark Lee, ZiRui Wang, Ruoming Pang, Peter Grasch, Alexander Toshev, Yinfei Yang
Through careful and comprehensive ablations of the image encoder, the vision language connector, and various pre-training data choices, we identified several crucial design lessons.
Ranked #21 on Visual Question Answering on MM-Vet
1 code implementation • 7 Mar 2024 • Frances A. Laureano De Leon, Harish Tayyar Madabushi, Mark Lee
Code-switching is a prevalent linguistic phenomenon in which multilingual individuals seamlessly alternate between languages.
no code implementations • 12 Nov 2021 • Xin Zhang, Liangxiu Han, Tam Sobeih, Lewis Lappin, Mark Lee, Andew Howard, Aron Kisdi
In this work, we propose a novel deep learning framework: a self-supervised spectral-spatial attention-based vision transformer (SSVT).
no code implementations • SEMEVAL 2021 • Wei Li, Harish Tayyar Madabushi, Mark Lee
This paper describes our submission to SemEval 2021 Task 2.
no code implementations • ACL 2021 • Venelin Kovatchev, Phillip Smith, Mark Lee, Rory Devine
To determine the capabilities of automatic systems to generalize to unseen data, we create UK-MIND-20 - a new corpus of children's performance on tests of mindreading, consisting of 10, 320 question-answer pairs.
no code implementations • SEMEVAL 2020 • Abdullah I. Alharbi, Mark Lee
Social media platforms such as Twitter offer people an opportunity to publish short posts in which they can share their opinions and perspectives.
no code implementations • COLING 2020 • Venelin Kovatchev, Phillip Smith, Mark Lee, Imogen Grumley Traynor, Irene Luque Aguilera, Rory Devine
In this paper we present the first work on the automated scoring of mindreading ability in middle childhood and early adolescence.
1 code implementation • 16 Nov 2020 • Venelin Kovatchev, Phillip Smith, Mark Lee, Imogen Grumley Traynor, Irene Luque Aguilera, Rory T. Devine
In this paper we present the first work on the automated scoring of mindreading ability in middle childhood and early adolescence.
no code implementations • WS 2020 • Ghadi Alnafesah, Harish Tayyar Madabushi, Mark Lee
The idea that a shift in concreteness within a sentence indicates the presence of a metaphor has been around for a while.
no code implementations • LREC 2020 • Abdullah I. Alharbi, Mark Lee
A key challenge was the uniqueness of the language used on social media, prompting the out-of-vocabulary (OOV) problem.
1 code implementation • 20 Jun 2019 • Mark Lee, Zico Kolter
In this paper, we demonstrate a physical adversarial patch attack against object detectors, notably the YOLOv3 detector.
no code implementations • COLING 2018 • Harish Tayyar Madabushi, Mark Lee, John Barnden
We present a system for Answer Selection that integrates fine-grained Question Classification with a Deep Learning model designed for Answer Selection.
no code implementations • COLING 2016 • Harish Tayyar Madabushi, Mark Lee
We present in this paper a purely rule-based system for Question Classification which we divide into two parts: The first is the extraction of relevant words from a question by use of its structure, and the second is the classification of questions based on rules that associate these words to Concepts.
Ranked #1 on Text Classification on TREC-50
no code implementations • LREC 2012 • Nur-Hana Samsudin, Mark Lee
This paper describes research on building text-to-speech synthesis systems (TTS) for resource poor languages using available resources from other languages and describes our general approach to building cross-linguistic polyglot TTS.