Search Results for author:
Found 6 papers, 4 papers with code
Wikiformer: Pre-training with Structured Information of Wikipedia for Ad-hoc Retrieval
With the development of deep learning and natural language processing techniques, pre-trained language models have been widely used to solve information retrieval (IR) problems.
THUIR2 at NTCIR-16 Session Search (SS) Task
Our team(THUIR2) participated in both FOSS and POSS subtasks of the NTCIR-161 Session Search (SS) Task.
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
T2Ranking comprises more than 300K queries and over 2M unique passages from real-world search engines.
Multi-Feature Integration for Perception-Dependent Examination-Bias Estimation
Eliminating examination bias accurately is pivotal to apply click-through data to train an unbiased ranking model.
Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking
Pre-trained language models have achieved great success in various large-scale information retrieval tasks.
Pre-training Methods in Information Retrieval
The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to the user's information need.
