98 citations · 486 across the 56 of their papers we have counts for
11 papers · 1 filter
CDSM: Cascaded Deep Semantic Matching on Textual Graphs Leveraging Ad-hoc Neighbor Selection
Jing Yao, Zheng Liu, Junhan Yang +3
Deep semantic matching aims to discriminate the relationship between documents based on deep neural networks. In recent years, it becomes increasingly popular to organize documents…
MCP: Self-supervised Pre-training for Personalized Chatbots with Multi-level Contrastive Sampling
Zhaoheng Huang, Zhicheng Dou, Yutao Zhu +1
Personalized chatbots focus on endowing the chatbots with a consistent personality to behave like real users and further act as personal assistants. Previous studies have explored…
From Easy to Hard: A Dual Curriculum Learning Framework for Context-Aware Document Ranking
Yutao Zhu, Jian-Yun Nie, Yixuan Su +3
Contextual information in search sessions is important for capturing users' search intents. Various approaches have been proposed to model user behavior sequences to improve docume…
Pre-training for Information Retrieval: Are Hyperlinks Fully Explored?
Jiawen Wu, Xinyu Zhang, Yutao Zhu +7
Recent years have witnessed great progress on applying pre-trained language models, e.g., BERT, to information retrieval (IR) tasks. Hyperlinks, which are commonly used in Web page…
Enhancing User Behavior Sequence Modeling by Generative Tasks for Session Search
Haonan Chen, Zhicheng Dou, Yutao Zhu +3
Users' search tasks have become increasingly complicated, requiring multiple queries and interactions with the results. Recent studies have demonstrated that modeling the historica…
Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer
Yujia Zhou, Jing Yao, Zhicheng Dou +3
Document retrieval has been extensively studied within the index-retrieve framework for decades, which has withstood the test of time. Unfortunately, such a pipelined framework lim…
Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding
Zhaoye Fei, Yu Tian, Yongkang Wu +9
Generalized text representations are the foundation of many natural language understanding tasks. To fully utilize the different corpus, it is inevitable that models need to unders…
Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generation
Hanxun Zhong, Zhicheng Dou, Yutao Zhu +2
Personalized dialogue systems explore the problem of generating responses that are consistent with the user's personality, which has raised much attention in recent years. Existing…
DynamicRetriever: A Pre-training Model-based IR System with Neither Sparse nor Dense Index
Yujia Zhou, Jing Yao, Zhicheng Dou +2
Web search provides a promising way for people to obtain information and has been extensively studied. With the surgence of deep learning and large-scale pre-training techniques, v…
KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models
Daniel Gao, Yantao Jia, Lei Li +6
Previous works show the great potential of pre-trained language models (PLMs) for storing a large amount of factual knowledge. However, to figure out whether PLMs can be reliable k…
Socialformer: Social Network Inspired Long Document Modeling for Document Ranking
Yujia Zhou, Zhicheng Dou, Huaying Yuan +1
Utilizing pre-trained language models has achieved great success for neural document ranking. Limited by the computational and memory requirements, long document modeling becomes a…