2 code implementations • 12 Jul 2022 • Guoxia Wang, Xiaomin Fang, Zhihua Wu, Yiqun Liu, Yang Xue, Yingfei Xiang, dianhai yu, Fan Wang, Yanjun Ma
Due to the complex model architecture and large memory consumption, it requires lots of computational resources and time to implement the training and inference of AlphaFold2 from scratch.
1 code implementation • 26 Jun 2022 • Chenyang Wang, Yuanqing Yu, Weizhi Ma, Min Zhang, Chong Chen, Yiqun Liu, Shaoping Ma
Then, we empirically analyze the learning dynamics of typical CF methods in terms of quantified alignment and uniformity, which shows that better alignment or uniformity both contribute to higher recommendation performance.
no code implementations • 8 Jun 2022 • Yifan Wang, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma
First, we summarize fairness definitions in the recommendation and provide several views to classify fairness issues.
1 code implementation • 25 Apr 2022 • Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
For example, representation-based retrieval models perform almost as well as interaction-based retrieval models in terms of interpolation but not extrapolation.
1 code implementation • 6 Apr 2022 • Zhumin Chu, Zhihong Wang, Yiqun Liu, Yingye Huang, Min Zhang, Shaoping Ma
25 search agents and 51 users are recruited for the field study that lasts about 45 days.
no code implementations • 5 Apr 2022 • Yangkun Li, Weizhi Ma, Chong Chen, Min Zhang, Yiqun Liu, Shaoping Ma, Yuekui Yang
Among various methods of coping with overfitting, dropout is one of the representative ways.
no code implementations • 8 Feb 2022 • Kaushik Rangadurai, Yiqun Liu, Siddarth Malreddy, Xiaoyi Liu, Piyush Maheshwari, Vishwanath Sangale, Fedor Borisyuk
In this paper, we present NxtPost, a deployed user-to-post content-based sequential recommender system for Facebook Groups.
no code implementations • 27 Nov 2021 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
Dense Retrieval (DR) reaches state-of-the-art results in first-stage retrieval, but little is known about the mechanisms that contribute to its success.
no code implementations • 14 Oct 2021 • Xuesong Chen, Ziyi Ye, Xiaohui Xie, Yiqun Liu, Weihang Su, Shuqi Zhu, Min Zhang, Shaoping Ma
While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades.
4 code implementations • 12 Oct 2021 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
However, the efficiency of most existing DR models is limited by the large memory cost of storing dense vectors and the time-consuming nearest neighbor search (NNS) in vector space.
no code implementations • 22 Sep 2021 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuancheng Li, Jiaji Li, Xuesong Chen, Min Zhang, Shaoping Ma
Inspired by these findings, we conduct supervised learning tasks to estimate the usefulness of non-click results with brain signals and conventional information (i. e., content and context factors).
no code implementations • 3 Aug 2021 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
Reading comprehension is a complex cognitive process involving many human brain activities.
5 code implementations • 2 Aug 2021 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
Compared with previous DR models that use brute-force search, JPQ almost matches the best retrieval performance with 30x compression on index size.
1 code implementation • 11 Jun 2021 • Bin Hao, Min Zhang, Weizhi Ma, Shaoyun Shi, Xinxing Yu, Houzhi Shan, Yiqun Liu, Shaoping Ma
To the best of our knowledge, this is the largest real-world interaction dataset for personalized recommendation.
4 code implementations • 16 Apr 2021 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma
ADORE replaces the widely-adopted static hard negative sampling method with a dynamic one to directly optimize the ranking performance.
1 code implementation • 27 Mar 2021 • Yiqun Liu, Yi Zeng, Jian Pu, Hongming Shan, Peiyang He, Junping Zhang
In this work, we propose a self-supervised gait recognition method, termed SelfGait, which takes advantage of the massive, diverse, unlabeled gait data as a pre-training process to improve the representation abilities of spatiotemporal backbones.
no code implementations • 24 Dec 2020 • Yunqiu Shao, Bulou Liu, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma
We participated in the two case law tasks, i. e., the legal case retrieval task and the legal case entailment task.
2 code implementations • 20 Oct 2020 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma
Through this process, it teaches the DR model how to retrieve relevant documents from the entire corpus instead of how to rerank a potentially biased sample of documents.
1 code implementation • ECCV 2020 • Yuzhi Wang, Haibin Huang, Qin Xu, Jiaming Liu, Yiqun Liu, Jue Wang
Deep learning-based image denoising approaches have been extensively studied in recent years, prevailing in many public benchmark datasets.
no code implementations • 1 Aug 2020 • Jie Zou, Evangelos Kanoulas, Yiqun Liu
Search and recommender systems that take the initiative to ask clarifying questions to better understand users' information needs are receiving increasing attention from the research community.
2 code implementations • 1 Jul 2020 • Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma
However, existing KG enhanced recommendation methods have largely focused on exploring advanced neural network architectures to better investigate the structural information of KG.
Ranked #1 on
Recommendation Systems
on Amazon-Book
3 code implementations • 28 Jun 2020 • Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma
Although exact term match between queries and documents is the dominant method to perform first-stage retrieval, we propose a different approach, called RepBERT, to represent documents and queries with fixed-length contextualized embeddings.
2 code implementations • WWW 2020 • Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma Department of Computer Science and Technology, Institute for Articial Intelligence, Beijing National Research Center for Information Science and Technology, Tsinghua University cc17@mails.tsinghua.edu.cn, z-m@tsinghua.edu.cn
Factorization Machines (FM) with negative sampling is a popular solution for context-aware recommendation.
no code implementations • 13 Apr 2020 • Yiqun Liu, Shouzhen Chen, Lei Chen, Hai Chu, Xiaoyang Xu, Junping Zhang, Leiming Ma
We thus propose an end-to-end deep-learning BCoP model named Spatio-Temporal feature Auto-Selective (STAS) model to select optimal ST regularity from EC via the ST Feature-selective Mechanisms (SFM/TFM).
no code implementations • 15 Oct 2019 • Xiaoyang Xu, Yiqun Liu, Hanqing Chao, Youcheng Luo, Hai Chu, Lei Chen, Junping Zhang, Leiming Ma
To the best of our knowledge, it is the first expert-free models for bias correction.
1 code implementation • 9 Mar 2019 • Weizhi Ma, Min Zhang, Yue Cao, Woojeong, Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, Xiang Ren
The framework encourages two modules to complement each other in generating effective and explainable recommendation: 1) inductive rules, mined from item-centric knowledge graphs, summarize common multi-hop relational patterns for inferring different item associations and provide human-readable explanation for model prediction; 2) recommendation module can be augmented by induced rules and thus have better generalization ability dealing with the cold-start issue.
2 code implementations • 25 Sep 2018 • Fuli Feng, Xiangnan He, Xiang Wang, Cheng Luo, Yiqun Liu, Tat-Seng Chua
Our RSR method advances existing solutions in two major aspects: 1) tailoring the deep learning models for stock ranking, and 2) capturing the stock relations in a time-sensitive manner.
no code implementations • COLING 2016 • Meng Zhang, Yang Liu, Huanbo Luan, Yiqun Liu, Maosong Sun
Being able to induce word translations from non-parallel data is often a prerequisite for cross-lingual processing in resource-scarce languages and domains.
no code implementations • 11 Feb 2015 • Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma
In this paper, we focus on the problem of phrase-level sentiment polarity labelling and attempt to bridge the gap between phrase-level and review-level sentiment analysis.