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05/25/2023
Overcoming Catastrophic Forgetting in Massively Multilingual Continual Learning
Real-life multilingual systems should be able to efficiently incorporate...
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12/19/2022
Dataless Knowledge Fusion by Merging Weights of Language Models
Fine-tuning pre-trained language models has become the prevalent paradig...
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10/16/2021
Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora
Pretrained language models (PTLMs) are typically learned over a large, s...
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04/18/2021
Lifelong Learning of Few-shot Learners across NLP Tasks
Recent advances in large pre-trained language models have greatly improv...
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03/18/2021
Refining Neural Networks with Compositional Explanations
Neural networks are prone to learning spurious correlations from biased ...
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10/24/2020
Efficiently Mitigating Classification Bias via Transfer Learning
Prediction bias in machine learning models refers to unintended model be...
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06/27/2020
Gradient Based Memory Editing for Task-Free Continual Learning
Prior work on continual learning often operate in a "task-aware" manner,...
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05/05/2020
Contextualizing Hate Speech Classifiers with Post-hoc Explanation
Hate speech classifiers trained on imbalanced datasets struggle to deter...
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05/02/2020
Visually Grounded Continual Learning of Compositional Semantics
Children's language acquisition from the visual world is a real-world ex...
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11/08/2019
Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models
The impressive performance of neural networks on natural language proces...
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08/31/2018
