1 code implementation • 24 Apr 2024 • Zhiyu He, Jiayu Li, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma
Meanwhile, EEG signals are collected with a portable device.
no code implementations • 29 Mar 2024 • Hanyu Li, Weizhi Ma, Peijie Sun, Jiayu Li, Cunxiang Yin, Yancheng He, Guoqiang Xu, Min Zhang, Shaoping Ma
In CUT, user similarity in the target domain is adopted as a constraint for user transformation learning to filter the user collaborative information from the source domain.
1 code implementation • 27 Mar 2024 • Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jia Chen, Shaoping Ma
Our in-depth analysis of these logs reveals that user prompt reformulation is heavily dependent on the individual user's capability, resulting in significant variance in the quality of reformulation pairs.
no code implementations • 17 Mar 2024 • Ruizhe Zhang, Haitao Li, Yueyue Wu, Qingyao Ai, Yiqun Liu, Min Zhang, Shaoping Ma
In recent years, the utilization of large language models for natural language dialogue has gained momentum, leading to their widespread adoption across various domains.
no code implementations • 5 Feb 2024 • Yifan Wang, Peijie Sun, Weizhi Ma, Min Zhang, Yuan Zhang, Peng Jiang, Shaoping Ma
Fairness of recommender systems (RS) has attracted increasing attention recently.
no code implementations • 29 Sep 2023 • Qian Dong, Yiding Liu, Qingyao Ai, Zhijing Wu, Haitao Li, Yiqun Liu, Shuaiqiang Wang, Dawei Yin, Shaoping Ma
Large language models (LLMs) have demonstrated remarkable capabilities across various research domains, including the field of Information Retrieval (IR).
no code implementations • 25 Jul 2023 • Yunqiu Shao, Haitao Li, Yueyue Wu, Yiqun Liu, Qingyao Ai, Jiaxin Mao, Yixiao Ma, Shaoping Ma
Through a laboratory user study, we reveal significant differences in user behavior and satisfaction under different search intents in legal case retrieval.
1 code implementation • 24 Jul 2023 • Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia, Jingjie Li, Shaoping Ma
To directly introduce the correct feedback label information, we propose an Unbiased delayed feedback Label Correction framework (ULC), which uses an auxiliary model to correct labels for observed negative feedback samples.
no code implementations • 1 Jul 2023 • Weihang Su, Xiangsheng Li, Yiqun Liu, Min Zhang, Shaoping Ma
Our team(THUIR2) participated in both FOSS and POSS subtasks of the NTCIR-161 Session Search (SS) Task.
1 code implementation • 4 Jun 2023 • Qian Dong, Yiding Liu, Qingyao Ai, Haitao Li, Shuaiqiang Wang, Yiqun Liu, Dawei Yin, Shaoping Ma
Moreover, the proposed implicit interaction is compatible with special pre-training and knowledge distillation for passage retrieval, which brings a new state-of-the-art performance.
1 code implementation • 17 Aug 2022 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
We explore the effectiveness of BTA for satisfaction modeling in two popular information access scenarios, i. e., search and recommendation.
1 code implementation • 11 Aug 2022 • Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao, Xiaohui Xie, Min Zhang, Shaoping Ma
By making the REM and DAMs disentangled, DDR enables a flexible training paradigm in which REM is trained with supervision once and DAMs are trained with unsupervised data.
2 code implementations • 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, Qingyao Ai, Zhihong Wang, Yiqun Liu, Yingye Huang, Rui Zhang, Min Zhang, Shaoping Ma
This raises the question of how to accurately model user satisfaction in conversational search scenarios.
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 • 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).
1 code implementation • 3 Aug 2021 • Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma
In this paper, we carefully design a lab-based user study to investigate brain activities during reading comprehension.
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.
2 code implementations • 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.
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.
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.
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.
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.