Downstream Task

task ID: downstreamtask

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AbstractWith growing applications of Machine Learning in daily lives Natural Language Processing (NLP) has emerged as a heavily researched area. Finding its applications in tasks ranging from simple Q/A chatbots …...

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AbstractAdapter-based tuning has recently arisen as an alternative to fine-tuning. It works by adding light-weight adapter modules to a pretrained language model (PrLM) and only updating the parameters of adapter …...

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Unsupervised Conversation Disentanglement through Co-Training

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AbstractConversation disentanglement aims to separate intermingled messages into detached sessions, which is a fundamental task in understanding multi-party conversations. Existing work on conversation disentanglement relies heavily upon human-annotated datasets, which …...

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An Empirical Study on the Transferability of Transformer Modules in Parameter-efficient Fine-tuning

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AbstractBehavioural consistency is a critical condition for a language model (LM) to become trustworthy like humans. Despite its importance, however, there is little consensus on the definition of LM consistency, …...

4893

IgboBERT Models: Building and Training Transformer Models for the Igbo Language

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Publication: TIPSTER (2022)

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AbstractThis work presents a standard Igbo named entity recognition (IgboNER) dataset as well as the results from training and fine-tuning state-of-the-art transformer IgboNER models. We discuss the process of our …...

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OpenKorPOS: Democratizing Korean Tokenization with Voting-Based Open Corpus Annotation

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Publication: TIPSTER (2022)

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AbstractKorean is a language with complex morphology that uses spaces at larger-than-word boundaries, unlike other East-Asian languages. While morpheme-based text generation can provide significant semantic advantages compared to commonly used …...

14766