55 citations · 104 across the 15 of their papers we have counts for
15 papers
GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network
Kaiyuan Zhang, Ziyi Ye, Qingyao Ai +2
Electroencephalography(EEG) classification is a crucial task in neuroscience, neural engineering, and several commercial applications. Traditional EEG classification models, howeve…
Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback
Qian Dong, Yiding Liu, Qingyao Ai +6
Large language models (LLMs) have demonstrated remarkable capabilities across various research domains, including the field of Information Retrieval (IR). However, the responses ge…
THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailment
Haitao Li, Changyue Wang, Weihang Su +3
This paper describes the approach of the THUIR team at the COLIEE 2023 Legal Case Entailment task. This task requires the participant to identify a specific paragraph from a given…
THUIR@COLIEE 2023: Incorporating Structural Knowledge into Pre-trained Language Models for Legal Case Retrieval
Haitao Li, Weihang Su, Changyue Wang +3
Legal case retrieval techniques play an essential role in modern intelligent legal systems. As an annually well-known international competition, COLIEE is aiming to achieve the sta…
CaseEncoder: A Knowledge-enhanced Pre-trained Model for Legal Case Encoding
Yixiao Ma, Yueyue Wu, Weihang Su +2
Legal case retrieval is a critical process for modern legal information systems. While recent studies have utilized pre-trained language models (PLMs) based on the general domain s…
A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning
Jiangui Chen, Ruqing Zhang, Jiafeng Guo +4
Knowledge-intensive language tasks (KILTs) benefit from retrieving high-quality relevant contexts from large external knowledge corpora. Learning task-specific retrievers that retu…
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank
Jia Chen, Haitao Li, Weihang Su +2
This paper introduces the approaches we have used to participate in the WSDM Cup 2023 Task 1: Unbiased Learning to Rank. In brief, we have attempted a combination of both tradition…
Constructing Tree-based Index for Efficient and Effective Dense Retrieval
Haitao Li, Qingyao Ai, Jingtao Zhan +4
Recent studies have shown that Dense Retrieval (DR) techniques can significantly improve the performance of first-stage retrieval in IR systems. Despite its empirical effectiveness…
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
Haitao Li, Qingyao Ai, Jia Chen +5
Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in the intelligent legal system. Despite the success that pre-training has achieved in a…
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
Xiaohui Xie, Qian Dong, Bingning Wang +8
Passage ranking involves two stages: passage retrieval and passage re-ranking, which are important and challenging topics for both academics and industries in the area of Informati…
Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank
Haitao Li, Jia Chen, Weihang Su +2
This paper describes the approach of the THUIR team at the WSDM Cup 2023 Pre-training for Web Search task. This task requires the participant to rank the relevant documents for eac…
Diverse legal case search
Ruizhe Zhang, Qingyao Ai, Yueyue Wu +2
In last decades, legal case search has received more and more attention. Legal practitioners need to work or enhance their efficiency by means of class case search. In the process…
Corrected Evaluation Results of the NTCIR WWW-2, WWW-3, and WWW-4 English Subtasks
Tetsuya Sakai, Sijie Tao, Maria Maistro +7
Unfortunately, the official English (sub)task results reported in the NTCIR-14 WWW-2, NTCIR-15 WWW-3, and NTCIR-16 WWW-4 overview papers are incorrect due to noise in the official…
CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks
Jiangui Chen, Ruqing Zhang, Jiafeng Guo +3
Knowledge-intensive language tasks (KILT) usually require a large body of information to provide correct answers. A popular paradigm to solve this problem is to combine a search sy…
THUIR@COLIEE-2020: Leveraging Semantic Understanding and Exact Matching for Legal Case Retrieval and Entailment
Yunqiu Shao, Bulou Liu, Jiaxin Mao +3
In this paper, we present our methodologies for tackling the challenges of legal case retrieval and entailment in the Competition on Legal Information Extraction / Entailment 2020…