Papers by Xiaopeng Lu
SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer Matching Retrieval (2021.naacl-main)
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| Challenge: | SPARTA is a novel neural retrieval method for open-domain question answering . it learns a sparse representation that can be efficiently implemented as an Inverted Index . |
| Approach: | They propose a method that learns a sparse representation that can be implemented as an Inverted Index. |
| Outcome: | The proposed method achieves state-of-the-art results on 4 open-domain question answering tasks and 11 retrieval question answering (ReQA) tasks. |
SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering (2021.eacl-demos)
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| Challenge: | Open-domain question answering (QA) requires large amounts of resources and is difficult to reproduce results due to complex configurations. |
| Approach: | They propose a simple and fair evaluation framework for open-domain question answering (QA) it modularizes the pipeline open- domain QA system, making it easily accessible . |
| Outcome: | The proposed evaluation framework is publicly available and anyone can contribute to the code and evaluations. |
An Explainable Toolbox for Evaluating Pre-trained Vision-Language Models (2022.emnlp-demos)
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| Challenge: | Existing studies evaluate VLP models by comparing the fine-tuned downstream task performance with the average downstream task accuracy. |
| Approach: | They propose a toolbox for evaluating Vision-Language Pretraining (VLP) models. |
| Outcome: | The proposed toolbox provides the preliminary datasets that deepen the image-texting ability of a VLP model. |
VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words (2021.acl-long)
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| Challenge: | Existing text-to-image retrieval models lack good representations for textual and visual modalities. |
| Approach: | They propose a novel text-to-image retrieval model that uses a transformer to match images with textual queries. |
| Outcome: | The proposed model outperforms state-of-the-art models in MSCOCO and Flickr30K . it achieves substantial speed advantages for a 1 million image index . |