b'Jiafeng Guo'

research

∙ 08/29/2023

Continual Learning for Generative Retrieval over Dynamic Corpora

Generative retrieval (GR) directly predicts the identifiers of relevant ...

0 Jiangui Chen, et al. ∙

research

∙ 08/24/2023

Inducing Causal Structure for Abstractive Text Summarization

The mainstream of data-driven abstractive summarization models tends to ...

0 Lu Chen, et al. ∙

research

∙ 08/22/2023

L^2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible Representations

First-stage retrieval is a critical task that aims to retrieve relevant ...

0 Yinqiong Cai, et al. ∙

research

∙ 08/22/2023

Pre-training with Aspect-Content Text Mutual Prediction for Multi-Aspect Dense Retrieval

Grounded on pre-trained language models (PLMs), dense retrieval has been...

0 Xiaojie Sun, et al. ∙

research

∙ 08/19/2023

Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method

Neural ranking models (NRMs) and dense retrieval (DR) models have given ...

0 Yu-An Liu, et al. ∙

research

∙ 07/19/2023

Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community

The research field of Information Retrieval (IR) has evolved significant...

0 Qingyao Ai, et al. ∙

research

∙ 06/22/2023

On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective

Recently, we have witnessed generative retrieval increasingly gaining at...

0 Yu-An Liu, et al. ∙

research

∙ 05/24/2023

Semantic-Enhanced Differentiable Search Index Inspired by Learning Strategies

Recently, a new paradigm called Differentiable Search Index (DSI) has be...

0 Yubao Tang, et al. ∙

research

∙ 05/22/2023

Semantic Structure Enhanced Event Causality Identification

Event Causality Identification (ECI) aims to identify causal relations b...

0 Zhilei Hu, et al. ∙

research

∙ 05/10/2023

Few-shot Link Prediction on N-ary Facts

N-ary facts composed of a primary triple (head entity, relation, tail en...

0 Jiyao Wei, et al. ∙

research

∙ 05/03/2023

Visual Transformation Telling

In this paper, we propose a new visual reasoning task, called Visual Tra...

0 Xin Hong, et al. ∙

research

∙ 05/02/2023

Visual Reasoning: from State to Transformation

Most existing visual reasoning tasks, such as CLEVR in VQA, ignore an im...

0 Xin Hong, et al. ∙

research

∙ 04/28/2023

Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models

Neural ranking models (NRMs) have attracted considerable attention in in...

0 Yu-An Liu, et al. ∙

research

∙ 04/28/2023

A Unified Generative Retriever for Knowledge-Intensive Language Tasks via Prompt Learning

Knowledge-intensive language tasks (KILTs) benefit from retrieving high-...

0 Jiangui Chen, et al. ∙

research

∙ 02/18/2023

Ensemble Ranking Model with Multiple Pretraining Strategies for Web Search

An effective ranking model usually requires a large amount of training d...

0 Xiaojie Sun, et al. ∙

research

∙ 02/15/2023

Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank

Unbiased learning to rank (ULTR) aims to mitigate various biases existin...

0 Lulu Yu, et al. ∙

research

∙ 12/16/2022

Rich Event Modeling for Script Event Prediction

Script is a kind of structured knowledge extracted from texts, which con...

0 Long Bai, et al. ∙

research

∙ 11/09/2022

Visual Named Entity Linking: A New Dataset and A Baseline

Visual Entity Linking (VEL) is a task to link regions of images with the...

0 Wenxiang Sun, et al. ∙

research

∙ 10/28/2022

LegoNet: A Fast and Exact Unlearning Architecture

Machine unlearning aims to erase the impact of specific training samples...

0 Sihao Yu, et al. ∙

research

∙ 10/18/2022

HiSMatch: Historical Structure Matching based Temporal Knowledge Graph Reasoning

A Temporal Knowledge Graph (TKG) is a sequence of KGs with respective ti...

0 Zixuan Li, et al. ∙

research

∙ 09/14/2022

Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models

Neural ranking models (NRMs) have achieved promising results in informat...

0 Chen Wu, et al. ∙

research

∙ 09/12/2022

Hard Negatives or False Negatives: Correcting Pooling Bias in Training Neural Ranking Models

Neural ranking models (NRMs) have become one of the most important techn...

0 Yinqiong Cai, et al. ∙

research

∙ 08/21/2022

Scattered or Connected? An Optimized Parameter-efficient Tuning Approach for Information Retrieval

Pre-training and fine-tuning have achieved significant advances in the i...

0 Xinyu Ma, et al. ∙

research

∙ 08/21/2022

A Contrastive Pre-training Approach to Learn Discriminative Autoencoder for Dense Retrieval

Dense retrieval (DR) has shown promising results in information retrieva...

0 Xinyu Ma, et al. ∙

research

∙ 08/16/2022

CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks

Knowledge-intensive language tasks (KILT) usually require a large body o...

0 Jiangui Chen, et al. ∙

research

∙ 04/22/2022

Pre-train a Discriminative Text Encoder for Dense Retrieval via Contrastive Span Prediction

Dense retrieval has shown promising results in many information retrieva...

0 Xinyu Ma, et al. ∙

research

∙ 04/12/2022

GERE: Generative Evidence Retrieval for Fact Verification

Fact verification (FV) is a challenging task which aims to verify a clai...

0 Jiangui Chen, et al. ∙

research

∙ 03/15/2022

Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning

A Temporal Knowledge Graph (TKG) is a sequence of KGs corresponding to d...

0 Zixuan Li, et al. ∙

research

∙ 12/31/2021

What is Event Knowledge Graph: A Survey

Besides entity-centric knowledge, usually organized as Knowledge Graph (...

0 Saiping Guan, et al. ∙

research

∙ 11/27/2021

Interpreting Dense Retrieval as Mixture of Topics

Dense Retrieval (DR) reaches state-of-the-art results in first-stage ret...

0 Jingtao Zhan, et al. ∙

research

∙ 11/27/2021

Pre-training Methods in Information Retrieval

The core of information retrieval (IR) is to identify relevant informati...

0 Yixing Fan, et al. ∙

research

∙ 10/12/2021

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

Dense Retrieval (DR) has achieved state-of-the-art first-stage ranking e...

0 Jingtao Zhan, et al. ∙

research

∙ 09/08/2021

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

Sarcasm employs ambivalence, where one says something positive but actua...

0 Yiyi Liu, et al. ∙

research

∙ 08/16/2021

Toward the Understanding of Deep Text Matching Models for Information Retrieval

Semantic text matching is a critical problem in information retrieval. R...

0 Lijuan Chen, et al. ∙

research

∙ 08/11/2021

FedMatch: Federated Learning Over Heterogeneous Question Answering Data

Question Answering (QA), a popular and promising technique for intellige...

0 Jiangui Chen, et al. ∙

research

∙ 08/11/2021

Are Neural Ranking Models Robust?

Recently, we have witnessed the bloom of neural ranking models in the in...

0 Chen Wu, et al. ∙

research

∙ 08/02/2021

Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance

Recently, Information Retrieval community has witnessed fast-paced advan...

0 Jingtao Zhan, et al. ∙

research

∙ 07/18/2021

A Discriminative Semantic Ranker for Question Retrieval

Similar question retrieval is a core task in community-based question an...

0 Yinqiong Cai, et al. ∙

research

∙ 06/01/2021

Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs

Temporal Knowledge Graphs (TKGs) have been developed and used in many di...

0 Zixuan Li, et al. ∙

research

∙ 04/21/2021

Link Prediction on N-ary Relational Data Based on Relatedness Evaluation

With the overwhelming popularity of Knowledge Graphs (KGs), researchers ...

0 Saiping Guan, et al. ∙

research

∙ 04/21/2021

Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

Knowledge Graph (KG) reasoning that predicts missing facts for incomplet...

0 Zixuan Li, et al. ∙

research

∙ 04/20/2021

B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc Retrieval

Pre-training and fine-tuning have achieved remarkable success in many do...

0 Xinyu Ma, et al. ∙

research

∙ 04/16/2021

Optimizing Dense Retrieval Model Training with Hard Negatives

Ranking has always been one of the top concerns in information retrieval...

0 Jingtao Zhan, et al. ∙

research

∙ 04/02/2021

Sketch and Customize: A Counterfactual Story Generator

Recent text generation models are easy to generate relevant and fluent t...

0 Changying Hao, et al. ∙

research

∙ 03/08/2021

Semantic Models for the First-stage Retrieval: A Comprehensive Review

Multi-stage ranking pipelines have been a practical solution in modern s...

0 Yinqiong Cai, et al. ∙

research

∙ 03/01/2021

A Linguistic Study on Relevance Modeling in Information Retrieval

Relevance plays a central role in information retrieval (IR), which has ...

0 Yixing Fan, et al. ∙

research

∙ 02/25/2021

Learning to Truncate Ranked Lists for Information Retrieval

Ranked list truncation is of critical importance in a variety of profess...

0 Chen Wu, et al. ∙

research

∙ 12/25/2020

Dynamic-K Recommendation with Personalized Decision Boundary

In this paper, we investigate the recommendation task in the most common...

0 Yan Gao, et al. ∙

research

∙ 11/26/2020

Transformation Driven Visual Reasoning

This paper defines a new visual reasoning paradigm by introducing an imp...

0 Xin Hong, et al. ∙

research

∙ 10/20/2020

PROP: Pre-training with Representative Words Prediction for Ad-hoc Retrieval

Recently pre-trained language representation models such as BERT have sh...

0 Xinyu Ma, et al. ∙

Jiafeng Guo

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