58 citations · 174 across the 28 of their papers we have counts for
6 papers · 1 filter
VLDeformer: Vision-Language Decomposed Transformer for Fast Cross-Modal Retrieval
Lisai Zhang, Hongfa Wu, Qingcai Chen +6
Cross-model retrieval has emerged as one of the most important upgrades for text-only search engines (SE). Recently, with powerful representation for pairwise text-image inputs via…
Towards More Effective and Economic Sparsely-Activated Model
Hao Jiang, Ke Zhan, Jianwei Qu +14
The sparsely-activated models have achieved great success in natural language processing through large-scale parameters and relatively low computational cost, and gradually become…
Towards Efficient NLP: A Standard Evaluation and A Strong Baseline
Xiangyang Liu, Tianxiang Sun, Junliang He +7
Supersized pre-trained language models have pushed the accuracy of various natural language processing (NLP) tasks to a new state-of-the-art (SOTA). Rather than pursuing the reachl…
YES SIR!Optimizing Semantic Space of Negatives with Self-Involvement Ranker
Ruizhi Pu, Xinyu Zhang, Ruofei Lai +7
Pre-trained model such as BERT has been proved to be an effective tool for dealing with Information Retrieval (IR) problems. Due to its inspiring performance, it has been widely us…
Pre-training for Ad-hoc Retrieval: Hyperlink is Also You Need
Zhengyi Ma, Zhicheng Dou, Wei Xu +4
Designing pre-training objectives that more closely resemble the downstream tasks for pre-trained language models can lead to better performance at the fine-tuning stage, especiall…
Early Exiting with Ensemble Internal Classifiers
Tianxiang Sun, Yunhua Zhou, Xiangyang Liu +5
As a simple technique to accelerate inference of large-scale pre-trained models, early exiting has gained much attention in the NLP community. It allows samples to exit early at in…