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08/21/2023
Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP Concepts
Large Language Models (LLMs) have achieved significant success across va...
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08/19/2023
UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding
In the era of Large Language Models (LLMs), tremendous strides have been...
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05/29/2023
Deeply Coupled Cross-Modal Prompt Learning
Recent advancements in multimodal foundation models (e.g., CLIP) have ex...
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11/27/2022
PUnifiedNER: a Prompting-based Unified NER System for Diverse Datasets
Much of named entity recognition (NER) research focuses on developing da...
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10/08/2022
SDA: Simple Discrete Augmentation for Contrastive Sentence Representation Learning
Contrastive learning methods achieve state-of-the-art results in unsuper...
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09/30/2022
What Makes Pre-trained Language Models Better Zero/Few-shot Learners?
In this paper, we propose a theoretical framework to explain the efficac...
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03/24/2022
A Rationale-Centric Framework for Human-in-the-loop Machine Learning
We present a novel rationale-centric framework with human-in-the-loop – ...
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06/12/2021
A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data
Training deep learning models with limited labelled data is an attractiv...
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04/21/2020
Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets
Active learning has been shown to be an effective way to alleviate some ...
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10/04/2019
Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text Datasets
Manually labelling large collections of text data is a time-consuming, e...
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10/04/2019