b'Chenyan Xiong'

research

∙ 08/27/2023

Text Matching Improves Sequential Recommendation by Reducing Popularity Biases

This paper proposes Text mAtching based SequenTial rEcommendation model ...

0 Zhenghao Liu, et al. ∙

research

∙ 07/01/2023

Improving Multitask Retrieval by Promoting Task Specialization

In multitask retrieval, a single retriever is trained to retrieve releva...

0 Wenzheng Zhang, et al. ∙

research

∙ 05/31/2023

Structure-Aware Language Model Pretraining Improves Dense Retrieval on Structured Data

This paper presents Structure Aware Dense Retrieval (SANTA) model, which...

0 Xinze Li, et al. ∙

research

∙ 05/27/2023

Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In

Retrieval augmentation can aid language models (LMs) in knowledge-intens...

0 Zichun Yu, et al. ∙

research

∙ 05/24/2023

Fusion-in-T5: Unifying Document Ranking Signals for Improved Information Retrieval

Common IR pipelines are typically cascade systems that may involve multi...

0 Shi Yu, et al. ∙

research

∙ 05/21/2023

Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers

This paper explores the effectiveness of model-generated signals in impr...

0 Linyuan Gong, et al. ∙

research

∙ 05/10/2023

Unsupervised Dense Retrieval Training with Web Anchors

In this work, we present an unsupervised retrieval method with contrasti...

1 Yiqing Xie, et al. ∙

research

∙ 02/07/2023

Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories

In this paper we improve the zero-shot generalization ability of languag...

0 Suyu Ge, et al. ∙

research

∙ 11/29/2022

ClueWeb22: 10 Billion Web Documents with Visual and Semantic Information

ClueWeb22, the newest iteration of the ClueWeb line of datasets, provide...

0 Arnold Overwijk, et al. ∙

research

∙ 10/31/2022

Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives

In this paper, we investigate the instability in the standard dense retr...

0 Si Sun, et al. ∙

research

∙ 10/27/2022

COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning

We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to ...

0 Yue Yu, et al. ∙

research

∙ 09/01/2022

Universal Multi-Modality Retrieval with One Unified Embedding Space

This paper presents Vision-Language Universal Search (VL-UnivSearch), wh...

0 Zhenghao Liu, et al. ∙

research

∙ 05/06/2022

Dimension Reduction for Efficient Dense Retrieval via Conditional Autoencoder

Dense retrievers encode texts and map them in an embedding space using p...

0 Zhenghao Liu, et al. ∙

research

∙ 05/04/2022

P^3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning

Compared to other language tasks, applying pre-trained language models (...

0 Xiaomeng Hu, et al. ∙

research

∙ 04/13/2022

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals

We present an efficient method of pretraining large-scale autoencoding l...

0 Payal Bajaj, et al. ∙

research

∙ 04/07/2022

Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators

We present a new framework AMOS that pretrains text encoders with an Adv...

0 Yu Meng, et al. ∙

research

∙ 01/13/2022

Neural Approaches to Conversational Information Retrieval

A conversational information retrieval (CIR) system is an information re...

10 Jianfeng Gao, et al. ∙

research

∙ 10/14/2021

Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations

Dense retrieval (DR) methods conduct text retrieval by first encoding te...

0 Ji Xin, et al. ∙

research

∙ 10/10/2021

Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation

Open-domain question answering answers a question based on evidence retr...

0 Chen Zhao, et al. ∙

research

∙ 09/09/2021

TIAGE: A Benchmark for Topic-Shift Aware Dialog Modeling

Human conversations naturally evolve around different topics and fluentl...

0 Huiyuan Xie, et al. ∙

research

∙ 08/30/2021

Improving Query Representations for Dense Retrieval with Pseudo Relevance Feedback

Dense retrieval systems conduct first-stage retrieval using embedded rep...

0 HongChien Yu, et al. ∙

research

∙ 07/16/2021

More Robust Dense Retrieval with Contrastive Dual Learning

Dense retrieval conducts text retrieval in the embedding space and has s...

0 Yizhi Li, et al. ∙

research

∙ 06/25/2021

Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature

Information overload is a prevalent challenge in many high-value domains...

12 Yu Wang, et al. ∙

research

∙ 05/10/2021

Few-Shot Conversational Dense Retrieval

Dense retrieval (DR) has the potential to resolve the query understandin...

0 Shi Yu, et al. ∙

research

∙ 04/13/2021

Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval

Complex question answering often requires finding a reasoning chain that...

0 Chen Zhao, et al. ∙

research

∙ 03/23/2021

Complex Factoid Question Answering with a Free-Text Knowledge Graph

We introduce DELFT, a factoid question answering system which combines t...

0 Chen Zhao, et al. ∙

research

∙ 03/02/2021

Data Augmentation for Abstractive Query-Focused Multi-Document Summarization

The progress in Query-focused Multi-Document Summarization (QMDS) has be...

2 Ramakanth Pasunuru, et al. ∙

research

∙ 02/18/2021

Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder

Many real-world applications use Siamese networks to efficiently match t...

0 Shuqi Lu, et al. ∙

research

∙ 02/16/2021

COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

We present COCO-LM, a new self-supervised learning framework that pretra...

0 Yu Meng, et al. ∙

research

∙ 01/30/2021

OpenMatch: An Open-Source Package for Information Retrieval

Information Retrieval (IR) is an important task and can be used in many ...

0 Zhenghao Liu, et al. ∙

research

∙ 12/29/2020

Meta Adaptive Neural Ranking with Contrastive Synthetic Supervision

Neural Information Retrieval (Neu-IR) models have shown their effectiven...

0 Si Sun, et al. ∙

research

∙ 11/03/2020

CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search

Neural rankers based on deep pretrained language models (LMs) have been ...

0 Chenyan Xiong, et al. ∙

research

∙ 10/23/2020

Long Document Ranking with Query-Directed Sparse Transformer

The computing cost of transformer self-attention often necessitates brea...

0 Jyun-Yu Jiang, et al. ∙

research

∙ 10/14/2020

Text Classification Using Label Names Only: A Language Model Self-Training Approach

Current text classification methods typically require a good number of h...

0 Yu Meng, et al. ∙

research

∙ 07/01/2020

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Conducting text retrieval in a dense learned representation space has ma...

0 Lee Xiong, et al. ∙

research

∙ 06/29/2020

Knowledge-Aware Language Model Pretraining

How much knowledge do pretrained language models hold? Recent research o...

5 Corby Rosset, et al. ∙

research

∙ 06/18/2020

Proceedings of the KG-BIAS Workshop 2020 at AKBC 2020

The KG-BIAS 2020 workshop touches on biases and how they surface in know...

0 Edgar Meij, et al. ∙

research

∙ 06/09/2020

Few-Shot Generative Conversational Query Rewriting

Conversational query rewriting aims to reformulate a concise conversatio...

0 Shi Yu, et al. ∙

research

∙ 04/28/2020

Joint Keyphrase Chunking and Salience Ranking with BERT

An effective keyphrase extraction system requires to produce self-contai...

0 Si Sun, et al. ∙

research

∙ 03/30/2020

TREC CAsT 2019: The Conversational Assistance Track Overview

The Conversational Assistance Track (CAsT) is a new track for TREC 2019 ...

0 Jeffrey Dalton, et al. ∙

research

∙ 01/28/2020

Selective Weak Supervision for Neural Information Retrieval

This paper democratizes neural information retrieval to scenarios where ...

1 Kaitao Zhang, et al. ∙

research

∙ 11/08/2019

Unsupervised Common Question Generation from Multiple Documents using Reinforced Contrastive Coordinator

Web search engines today return a ranked list of document links in respo...

0 Woon Sang Cho, et al. ∙

research

∙ 11/07/2019

Conversation Generation with Concept Flow

Human conversations naturally evolve around related entities and connect...

0 Houyu Zhang, et al. ∙

research

∙ 11/06/2019

Open Domain Web Keyphrase Extraction Beyond Language Modeling

This paper studies keyphrase extraction in real-world scenarios where do...

0 Lee Xiong, et al. ∙

research

∙ 10/22/2019

Kernel Graph Attention Network for Fact Verification

This paper presents Kernel Graph Attention Network (KGAT), which conduct...

0 Zhenghao Liu, et al. ∙

research

∙ 08/28/2019

Explore Entity Embedding Effectiveness in Entity Retrieval

This paper explores entity embedding effectiveness in ad-hoc entity retr...

0 Zhenghao Liu, et al. ∙

research

∙ 08/21/2019

Latent Relation Language Models

In this paper, we propose Latent Relation Language Models (LRLMs), a cla...

0 Hiroaki Hayashi, et al. ∙

research

∙ 08/08/2019

Neural Document Expansion with User Feedback

This paper presents a neural document expansion approach (NeuDEF) that e...

0 Yue Yin, et al. ∙

research

∙ 07/24/2019

Generic Intent Representation in Web Search

This paper presents GEneric iNtent Encoder (GEN Encoder) which learns a ...

0 Hongfei Zhang, et al. ∙

research

∙ 04/16/2019

Understanding the Behaviors of BERT in Ranking

This paper studies the performances and behaviors of BERT in ranking tas...

0 Yifan Qiao, et al. ∙

Chenyan Xiong

Featured Co-authors