1.5k citations · 1.8k across the 32 of their papers we have counts for
32 papers
Learning to Relate to Previous Turns in Conversational Search
Fengran Mo, Jian-Yun Nie, Kaiyu Huang +4
Conversational search allows a user to interact with a search system in multiple turns. A query is strongly dependent on the conversation context. An effective way to improve retri…
Word Grounded Graph Convolutional Network
Zhibin Lu, Qianqian Xie, Benyou Wang +1
Graph Convolutional Networks (GCNs) have shown strong performance in learning text representations for various tasks such as text classification, due to its expressive power in mod…
GlyphDiffusion: Text Generation as Image Generation
Junyi Li, Wayne Xin Zhao, Jian-Yun Nie +1
Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel d…
ConvGQR: Generative Query Reformulation for Conversational Search
Fengran Mo, Kelong Mao, Yutao Zhu +3
In conversational search, the user's real search intent for the current turn is dependent on the previous conversation history. It is challenging to determine a good search query f…
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models
Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao +2
Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i.e., content that conflicts with the source or cannot be verified by the factual knowledge. To…
WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web Corpus
Hongjing Qian, Yutao Zhu, Zhicheng Dou +7
In this paper, we introduce a new NLP task -- generating short factual articles with references for queries by mining supporting evidence from the Web. In this task, called WebBrai…
A Survey of Large Language Models
Wayne Xin Zhao, Kun Zhou, Junyi Li +19
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for compre…
CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval
Nam Le Hai, Thomas Gerald, Thibault Formal +3
Conversational search is a difficult task as it aims at retrieving documents based not only on the current user query but also on the full conversation history. Most of the previou…
TextBox 2.0: A Text Generation Library with Pre-trained Language Models
Tianyi Tang, Junyi Li, Zhipeng Chen +9
To facilitate research on text generation, this paper presents a comprehensive and unified library, TextBox 2.0, focusing on the use of pre-trained language models (PLMs). To be co…
Tapping the Potential of Coherence and Syntactic Features in Neural Models for Automatic Essay Scoring
Xinying Qiu, Shuxuan Liao, Jiajun Xie +1
In the prompt-specific holistic score prediction task for Automatic Essay Scoring, the general approaches include pre-trained neural model, coherence model, and hybrid model that i…
ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation
Junyi Li, Tianyi Tang, Wayne Xin Zhao +2
We study the text generation task under the approach of pre-trained language models (PLMs). Typically, an auto-regressive (AR) method is adopted for generating texts in a token-by-…
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…
PReGAN: Answer Oriented Passage Ranking with Weakly Supervised GAN
Pan Du, Jian-Yun Nie, Yutao Zhu +3
Beyond topical relevance, passage ranking for open-domain factoid question answering also requires a passage to contain an answer (answerability). While a few recent studies have i…
A Customized Text Sanitization Mechanism with Differential Privacy
Huimin Chen, Fengran Mo, Yanhao Wang +4
As privacy issues are receiving increasing attention within the Natural Language Processing (NLP) community, numerous methods have been proposed to sanitize texts subject to differ…
Self-supervised Context-aware Style Representation for Expressive Speech Synthesis
Yihan Wu, Xi Wang, Shaofei Zhang +3
Expressive speech synthesis, like audiobook synthesis, is still challenging for style representation learning and prediction. Deriving from reference audio or predicting style tags…
Learning to Transfer Prompts for Text Generation
Junyi Li, Tianyi Tang, Jian-Yun Nie +2
Pretrained language models (PLMs) have made remarkable progress in text generation tasks via fine-tuning. While, it is challenging to fine-tune PLMs in a data-scarce situation. The…
Pretrained Language Models for Text Generation: A Survey
Junyi Li, Tianyi Tang, Wayne Xin Zhao +2
Text Generation aims to produce plausible and readable text in a human language from input data. The resurgence of deep learning has greatly advanced this field, in particular, wit…
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…
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…
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…
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…
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…
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…
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…