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10/26/2022
Compressing And Debiasing Vision-Language Pre-Trained Models for Visual Question Answering
Despite the excellent performance of large-scale vision-language pre-tra...
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10/11/2022
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models
Despite the remarkable success of pre-trained language models (PLMs), th...
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10/10/2022
Language Prior Is Not the Only Shortcut: A Benchmark for Shortcut Learning in VQA
Visual Question Answering (VQA) models are prone to learn the shortcut s...
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10/10/2022
Towards Robust Visual Question Answering: Making the Most of Biased Samples via Contrastive Learning
Models for Visual Question Answering (VQA) often rely on the spurious co...
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04/24/2022
Learning to Win Lottery Tickets in BERT Transfer via Task-agnostic Mask Training
Recent studies on the lottery ticket hypothesis (LTH) show that pre-trai...
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06/10/2021
Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation
Recently, knowledge distillation (KD) has shown great success in BERT co...
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03/21/2021
ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques
Pre-trained language models of the BERT family have defined the state-of...
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12/03/2020
Learning Disentangled Intent Representations for Zero-shot Intent Detection
Zero-shot intent detection (ZSID) aims to deal with the continuously eme...
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02/28/2020
Exploring and Distilling Cross-Modal Information for Image Captioning
Recently, attention-based encoder-decoder models have been used extensiv...
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11/13/2019
Unsupervised Pre-training for Natural Language Generation: A Literature Review
Recently, unsupervised pre-training is gaining increasing popularity in ...
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05/15/2019
Aligning Visual Regions and Textual Concepts: Learning Fine-Grained Image Representations for Image Captioning
In image-grounded text generation, fine-grained representations of the i...
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08/27/2018
