Search Results for author: Xueqi Cheng

Found 45 papers, 26 papers with code

LoL: A Comparative Regularization Loss over Query Reformulation Losses for Pseudo-Relevance Feedback

1 code implementation25 Apr 2022 Yunchang Zhu, Liang Pang, Yanyan Lan, HuaWei Shen, Xueqi Cheng

Ideally, if a PRF model can distinguish between irrelevant and relevant information in the feedback, the more feedback documents there are, the better the revised query will be.

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

no code implementations22 Apr 2022 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Xueqi Cheng

% Therefore, in this work, we propose to drop out the decoder and introduce a novel contrastive span prediction task to pre-train the encoder alone.

Contrastive Learning Information Retrieval +1

GERE: Generative Evidence Retrieval for Fact Verification

1 code implementation12 Apr 2022 Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Yixing Fan, Xueqi Cheng

This classical approach has clear drawbacks as follows: i) a large document index as well as a complicated search process is required, leading to considerable memory and computational overhead; ii) independent scoring paradigms fail to capture the interactions among documents and sentences in ranking; iii) a fixed number of sentences are selected to form the final evidence set.

Fact Verification

Improving Multi-task Generalization Ability for Neural Text Matching via Prompt Learning

no code implementations6 Apr 2022 Shicheng Xu, Liang Pang, HuaWei Shen, Xueqi Cheng

It is because the end-to-end supervised learning on task-specific dataset makes model overemphasize the data sample bias and task-specific signals instead of the essential matching signals, which ruins the generalization of model to different tasks.

Information Retrieval Paraphrase Identification +2

PRADA: Practical Black-Box Adversarial Attacks against Neural Ranking Models

no code implementations4 Apr 2022 Chen Wu, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Yixing Fan, Xueqi Cheng

In this paper, we introduce the Adversarial Document Ranking Attack (ADRA) task against NRMs, which aims to promote a target document in rankings by adding adversarial perturbations to its text.

Document Ranking Information Retrieval

Complex Evolutional Pattern Learning for Temporal Knowledge Graph Reasoning

1 code implementation ACL 2022 Zixuan Li, Saiping Guan, Xiaolong Jin, Weihua Peng, Yajuan Lyu, Yong Zhu, Long Bai, Wei Li, Jiafeng Guo, Xueqi Cheng

Furthermore, these models are all trained offline, which cannot well adapt to the changes of evolutional patterns from then on.

What is Event Knowledge Graph: A Survey

1 code implementation31 Dec 2021 Saiping Guan, Xueqi Cheng, Long Bai, Fujun Zhang, Zixuan Li, Yutao Zeng, Xiaolong Jin, Jiafeng Guo

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG).

Question Answering Text Generation

Piecing and Chipping: An effective solution for the information-erasing view generation in Self-supervised Learning

no code implementations29 Sep 2021 Jingwei Liu, Yi Gu, Shentong Mo, Zhun Sun, Shumin Han, Jiafeng Guo, Xueqi Cheng

In self-supervised learning frameworks, deep networks are optimized to align different views of an instance that contains the similar visual semantic information.

Data Augmentation Self-Supervised Learning

Integrating Deep Event-Level and Script-Level Information for Script Event Prediction

1 code implementation EMNLP 2021 Long Bai, Saiping Guan, Jiafeng Guo, Zixuan Li, Xiaolong Jin, Xueqi Cheng

In this paper, we propose a Transformer-based model, called MCPredictor, which integrates deep event-level and script-level information for script event prediction.

Transductive Learning for Unsupervised Text Style Transfer

1 code implementation EMNLP 2021 Fei Xiao, Liang Pang, Yanyan Lan, Yan Wang, HuaWei Shen, Xueqi Cheng

The proposed transductive learning approach is general and effective to the task of unsupervised style transfer, and we will apply it to the other two typical methods in the future.

Style Transfer Text Style Transfer +1

Adaptive Information Seeking for Open-Domain Question Answering

1 code implementation EMNLP 2021 Yunchang Zhu, Liang Pang, Yanyan Lan, HuaWei Shen, Xueqi Cheng

Information seeking is an essential step for open-domain question answering to efficiently gather evidence from a large corpus.

Open-Domain Question Answering

Single Node Injection Attack against Graph Neural Networks

1 code implementation30 Aug 2021 Shuchang Tao, Qi Cao, HuaWei Shen, JunJie Huang, Yunfan Wu, Xueqi Cheng

In this paper, we focus on an extremely limited scenario of single node injection evasion attack, i. e., the attacker is only allowed to inject one single node during the test phase to hurt GNN's performance.

Signed Bipartite Graph Neural Networks

1 code implementation22 Aug 2021 JunJie Huang, HuaWei Shen, Qi Cao, Shuchang Tao, Xueqi Cheng

Signed bipartite networks are different from classical signed networks, which contain two different node sets and signed links between two node sets.

Link Sign Prediction Network Embedding

Toward the Understanding of Deep Text Matching Models for Information Retrieval

no code implementations16 Aug 2021 Lijuan Chen, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng

We further extend these constraints to the semantic settings, which are shown to be better satisfied for all the deep text matching models.

Information Retrieval Semantic Text Matching +1

FedMatch: Federated Learning Over Heterogeneous Question Answering Data

1 code implementation11 Aug 2021 Jiangui Chen, Ruqing Zhang, Jiafeng Guo, Yixing Fan, Xueqi Cheng

A possible solution to this dilemma is a new approach known as federated learning, which is a privacy-preserving machine learning technique over distributed datasets.

Federated Learning Question Answering

Conditional GANs with Auxiliary Discriminative Classifier

1 code implementation21 Jul 2021 Liang Hou, Qi Cao, HuaWei Shen, Siyuan Pan, Xiaoshuang Li, Xueqi Cheng

Specifically, the proposed auxiliary \textit{discriminative} classifier becomes generator-aware by recognizing the labels of the real data and the generated data \textit{discriminatively}.

A Discriminative Semantic Ranker for Question Retrieval

no code implementations18 Jul 2021 Yinqiong Cai, Yixing Fan, Jiafeng Guo, Ruqing Zhang, Yanyan Lan, Xueqi Cheng

However, these methods often lose the discriminative power as term-based methods, thus introduce noise during retrieval and hurt the recall performance.

Question Answering Re-Ranking

INMO: A Model-Agnostic and Scalable Module for Inductive Collaborative Filtering

1 code implementation12 Jul 2021 Yunfan Wu, Qi Cao, HuaWei Shen, Shuchang Tao, Xueqi Cheng

INMO generates the inductive embeddings for users (items) by characterizing their interactions with some template items (template users), instead of employing an embedding lookup table.

Collaborative Filtering Recommendation Systems

Self-Supervised GANs with Label Augmentation

1 code implementation NeurIPS 2021 Liang Hou, HuaWei Shen, Qi Cao, Xueqi Cheng

Recently, transformation-based self-supervised learning has been applied to generative adversarial networks (GANs) to mitigate catastrophic forgetting in the discriminator by introducing a stationary learning environment.

Data Augmentation Image Generation +2

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

no code implementations ACL 2021 Zixuan Li, Xiaolong Jin, Saiping Guan, Wei Li, Jiafeng Guo, Yuanzhuo Wang, Xueqi Cheng

Specifically, at the clue searching stage, CluSTeR learns a beam search policy via reinforcement learning (RL) to induce multiple clues from historical facts.

Knowledge Graphs reinforcement-learning

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

1 code implementation21 Apr 2021 Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, Xueqi Cheng

However, they mainly focus on link prediction on binary relational data, where facts are usually represented as triples in the form of (head entity, relation, tail entity).

Knowledge Graphs Link Prediction

Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

1 code implementation21 Apr 2021 Zixuan Li, Xiaolong Jin, Wei Li, Saiping Guan, Jiafeng Guo, HuaWei Shen, Yuanzhuo Wang, Xueqi Cheng

To capture these properties effectively and efficiently, we propose a novel Recurrent Evolution network based on Graph Convolution Network (GCN), called RE-GCN, which learns the evolutional representations of entities and relations at each timestamp by modeling the KG sequence recurrently.

Representation Learning

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

1 code implementation20 Apr 2021 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Yingyan Li, Xueqi Cheng

The basic idea of PROP is to construct the \textit{representative words prediction} (ROP) task for pre-training inspired by the query likelihood model.

Information Retrieval Language Modelling

Locate Who You Are: Matching Geo-location to Text for User Identity Linkage

no code implementations19 Apr 2021 Jiangli Shao, Yongqing Wang, Hao Gao, HuaWei Shen, Yangyang Li, Xueqi Cheng

However, encouraged by online services, users would also post asymmetric information across networks, such as geo-locations and texts.

Anchor link prediction

Sketch and Customize: A Counterfactual Story Generator

1 code implementation2 Apr 2021 Changying Hao, Liang Pang, Yanyan Lan, Yan Wang, Jiafeng Guo, Xueqi Cheng

In the sketch stage, a skeleton is extracted by removing words which are conflict to the counterfactual condition, from the original ending.

Text Generation

GCN-ALP: Addressing Matching Collisions in Anchor Link Prediction

no code implementations19 Mar 2021 Hao Gao, Yongqing Wang, Shanshan Lyu, HuaWei Shen, Xueqi Cheng

However, the low quality of observed user data confuses the judgment on anchor links, resulting in the matching collision problem in practice.

Anchor link prediction

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

1 code implementation8 Mar 2021 Jiafeng Guo, Yinqiong Cai, Yixing Fan, Fei Sun, Ruqing Zhang, Xueqi Cheng

We believe it is the right time to survey current status, learn from existing methods, and gain some insights for future development.

Re-Ranking Semantic Retrieval

A Linguistic Study on Relevance Modeling in Information Retrieval

no code implementations1 Mar 2021 Yixing Fan, Jiafeng Guo, Xinyu Ma, Ruqing Zhang, Yanyan Lan, Xueqi Cheng

We employ 16 linguistic tasks to probe a unified retrieval model over these three retrieval tasks to answer this question.

Information Retrieval Natural Language Understanding +1

Learning to Truncate Ranked Lists for Information Retrieval

no code implementations25 Feb 2021 Chen Wu, Ruqing Zhang, Jiafeng Guo, Yixing Fan, Yanyan Lan, Xueqi Cheng

One is the widely adopted metric such as F1 which acts as a balanced objective, and the other is the best F1 under some minimal recall constraint which represents a typical objective in professional search.

Information Retrieval

Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching

1 code implementation16 Jan 2021 Liang Pang, Yanyan Lan, Xueqi Cheng

However, these models designed for short texts cannot well address the long-form text matching problem, because there are many contexts in long-form texts can not be directly aligned with each other, and it is difficult for existing models to capture the key matching signals from such noisy data.

Community Question Answering Information Retrieval +3

Modelling Universal Order Book Dynamics in Bitcoin Market

no code implementations15 Jan 2021 Fabin Shi, Nathan Aden, Shengda Huang, Neil Johnson, Xiaoqian Sun, Jinhua Gao, Li Xu, HuaWei Shen, Xueqi Cheng, Chaoming Song

Understanding the emergence of universal features such as the stylized facts in markets is a long-standing challenge that has drawn much attention from economists and physicists.

SDGNN: Learning Node Representation for Signed Directed Networks

1 code implementation7 Jan 2021 JunJie Huang, HuaWei Shen, Liang Hou, Xueqi Cheng

Guided by related sociological theories, we propose a novel Signed Directed Graph Neural Networks model named SDGNN to learn node embeddings for signed directed networks.

Network Embedding

Towards Powerful Graph Neural Networks: Diversity Matters

no code implementations1 Jan 2021 Xu Bingbing, HuaWei Shen, Qi Cao, YuanHao Liu, Keting Cen, Xueqi Cheng

For a target node, diverse sampling offers it diverse neighborhoods, i. e., rooted sub-graphs, and the representation of target node is finally obtained via aggregating the representation of diverse neighborhoods obtained using any GNN model.

Graph Representation Learning Node Classification

Slimmable Generative Adversarial Networks

1 code implementation10 Dec 2020 Liang Hou, Zehuan Yuan, Lei Huang, HuaWei Shen, Xueqi Cheng, Changhu Wang

In particular, for real-time generation tasks, different devices require generators of different sizes due to varying computing power.

AugSplicing: Synchronized Behavior Detection in Streaming Tensors

1 code implementation3 Dec 2020 Jiabao Zhang, Shenghua Liu, Wenting Hou, Siddharth Bhatia, HuaWei Shen, Wenjian Yu, Xueqi Cheng

Therefore, we propose a fast streaming algorithm, AugSplicing, which can detect the top dense blocks by incrementally splicing the previous detection with the incoming ones in new tuples, avoiding re-runs over all the history data at every tracking time step.

Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings

no code implementations COLING 2020 Yutao Zeng, Xiaolong Jin, Saiping Guan, Jiafeng Guo, Xueqi Cheng

To resolve event coreference, existing methods usually calculate the similarities between event mentions and between specific kinds of event arguments.

Coreference Resolution Event Coreference Resolution

Transformation Driven Visual Reasoning

1 code implementation CVPR 2021 Xin Hong, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng

Following this definition, a new dataset namely TRANCE is constructed on the basis of CLEVR, including three levels of settings, i. e.~Basic (single-step transformation), Event (multi-step transformation), and View (multi-step transformation with variant views).

Visual Question Answering Visual Reasoning +1

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

1 code implementation20 Oct 2020 Xinyu Ma, Jiafeng Guo, Ruqing Zhang, Yixing Fan, Xiang Ji, Xueqi Cheng

Recently pre-trained language representation models such as BERT have shown great success when fine-tuned on downstream tasks including information retrieval (IR).

Information Retrieval Language Modelling

Summarizing graphs using configuration model

no code implementations19 Oct 2020 Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, HuaWei Shen, Xueqi Cheng

As a solution, graph summarization, which aims to find a compact representation that preserves the important properties of a given graph, has received much attention, and numerous algorithms have been developed for it.

Social and Information Networks

Beyond Language: Learning Commonsense from Images for Reasoning

1 code implementation Findings of the Association for Computational Linguistics 2020 Wanqing Cui, Yanyan Lan, Liang Pang, Jiafeng Guo, Xueqi Cheng

This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP.

Language Modelling Question Answering

DeepHawkes: Bridging the gap between prediction and understanding of information cascades

1 code implementation CIKM 2017 Qi Cao, HuaWei Shen, Keting Cen, Wentao Ouyang, Xueqi Cheng

In this paper, we propose DeepHawkes to combat the defects of existing methods, leveraging end-to-end deep learning to make an analogy to interpretable factors of Hawkes process — a widely-used generative process to model information cascade.

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