activity
20152023
most citedA Survey of Large Language Models

1.5k citations · 1.8k across the 32 of their papers we have counts for

collaborators
Showing 2021Show all

7 papers · 1 filter

cs.IR2021★ 30 cited

Contrastive Learning of User Behavior Sequence for Context-Aware Document Ranking

Yutao Zhu, Jian-Yun Nie, Zhicheng Dou +5

Context information in search sessions has proven to be useful for capturing user search intent. Existing studies explored user behavior sequences in sessions in different ways to…

cs.CL2021★ 21 cited

Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals

Yutao Zhu, Jian-Yun Nie, Kun Zhou +3

A proactive dialogue system has the ability to proactively lead the conversation. Different from the general chatbots which only react to the user, proactive dialogue systems can b…

cs.CL2021

Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessment

Xinying Qiu, Yuan Chen, Hanwu Chen +3

Deep learning models for automatic readability assessment generally discard linguistic features traditionally used in machine learning models for the task. We propose to incorporat…

cs.IR2021

The DELICES project: Indexing scientific literature through semantic expansion

Florian Boudin, Béatrice Daille, Evelyne Jacquey +1

Scientific digital libraries play a critical role in the development and dissemination of scientific literature. Despite dedicated search engines, retrieving relevant publications…

cs.CL2021★ 1 cited

BERT4SO: Neural Sentence Ordering by Fine-tuning BERT

Yutao Zhu, Jian-Yun Nie, Kun Zhou +3

Sentence ordering aims to arrange the sentences of a given text in the correct order. Recent work frames it as a ranking problem and applies deep neural networks to it. In this wor…

cs.CL2021★ 7 cited

Neural Sentence Ordering Based on Constraint Graphs

Yutao Zhu, Kun Zhou, Jian-Yun Nie +2

Sentence ordering aims at arranging a list of sentences in the correct order. Based on the observation that sentence order at different distances may rely on different types of inf…

cs.CL2021★ 2 cited

Content Selection Network for Document-grounded Retrieval-based Chatbots

Yutao Zhu, Jian-Yun Nie, Kun Zhou +2

Grounding human-machine conversation in a document is an effective way to improve the performance of retrieval-based chatbots. However, only a part of the document content may be r…