20 citations · 37 across the 9 of their papers we have counts for
9 papers
TeachCLIP: Multi-Grained Teaching for Efficient Text-to-Video Retrieval
Kaibin Tian, Ruixiang Zhao, Hu Hu +4
For text-to-video retrieval (T2VR), which aims to retrieve unlabeled videos by ad-hoc textual queries, CLIP-based methods are dominating. Compared to CLIP4Clip which is efficient a…
ChinaOpen: A Dataset for Open-world Multimodal Learning
Aozhu Chen, Ziyuan Wang, Chengbo Dong +5
This paper introduces ChinaOpen, a dataset sourced from Bilibili, a popular Chinese video-sharing website, for open-world multimodal learning. While the state-of-the-art multimodal…
Multi-Feature Integration for Perception-Dependent Examination-Bias Estimation
Xiaoshu Chen, Xiangsheng Li, Kunliang Wei +4
Eliminating examination bias accurately is pivotal to apply click-through data to train an unbiased ranking model. However, most examination-bias estimators are limited to the hypo…
Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking
Xiangsheng Li, Xiaoshu Chen, Kunliang Wei +4
Pre-trained language models have achieved great success in various large-scale information retrieval tasks. However, most of pretraining tasks are based on counterfeit retrieval da…
BagFormer: Better Cross-Modal Retrieval via bag-wise interaction
Haowen Hou, Xiaopeng Yan, Yigeng Zhang +2
In the field of cross-modal retrieval, single encoder models tend to perform better than dual encoder models, but they suffer from high latency and low throughput. In this paper, w…
TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities
Zhe Zhao, Yudong Li, Cheng Hou +23
Recently, the success of pre-training in text domain has been fully extended to vision, audio, and cross-modal scenarios. The proposed pre-training models of different modalities a…
MKQ-BERT: Quantized BERT with 4-bits Weights and Activations
Hanlin Tang, Xipeng Zhang, Kai Liu +2
Recently, pre-trained Transformer based language models, such as BERT, have shown great superiority over the traditional methods in many Natural Language Processing (NLP) tasks. Ho…
TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis
Haisong Zhang, Lemao Liu, Haiyun Jiang +14
This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. Com…
STH: Spatio-Temporal Hybrid Convolution for Efficient Action Recognition
Xu Li, Jingwen Wang, Lin Ma +4
Effective and Efficient spatio-temporal modeling is essential for action recognition. Existing methods suffer from the trade-off between model performance and model complexity. In…