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Red Alarm for Pre-trained Models: Universal Vulnerabilities by Neuron-Level Backdoor Attacks
Due to the success of pre-trained models (PTMs), people usually fine-tun...
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ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning
Pre-trained Language Models (PLMs) have shown strong performance in vari...
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Meta Adaptive Neural Ranking with Contrastive Synthetic Supervision
Neural Information Retrieval (Neu-IR) models have shown their effectiven...
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CPM: A Large-scale Generative Chinese Pre-trained Language Model
Pre-trained Language Models (PLMs) have proven to be beneficial for vari...
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ONION: A Simple and Effective Defense Against Textual Backdoor Attacks
Backdoor attacks, which are a kind of emergent training-time threat to d...
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TLab: Traffic Map Movie Forecasting Based on HR-NET
The problem of the effective prediction for large-scale spatio-temporal ...
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Denoising Relation Extraction from Document-level Distant Supervision
Distant supervision (DS) has been widely used to generate auto-labeled d...
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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 ...
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Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment
Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of...
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Learning from Context or Names? An Empirical Study on Neural Relation Extraction
Neural models have achieved remarkable success on relation extraction (R...
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Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph
Multi-hop reasoning has been widely studied in recent years to seek an e...
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Partially-Aligned Data-to-Text Generation with Distant Supervision
The Data-to-Text task aims to generate human-readable text for describin...
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Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models
Several recent efforts have been devoted to enhancing pre-trained langua...
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Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect
Recommender systems aim to provide item recommendations for users, and a...
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Learning to Attack: Towards Textual Adversarial Attacking in Real-world Situations
Adversarial attacking aims to fool deep neural networks with adversarial...
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OpenAttack: An Open-source Textual Adversarial Attack Toolkit
Textual adversarial attacking has received wide and increasing attention...
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Country Image in COVID-19 Pandemic: A Case Study of China
Country image has a profound influence on international relations and ec...
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A Smoothed Analysis of Online Lasso for the Sparse Linear Contextual Bandit Problem
We investigate the sparse linear contextual bandit problem where the par...
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Adaptive Graph Encoder for Attributed Graph Embedding
Attributed graph embedding, which learns vector representations from gra...
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Crossmodal Language Grounding in an Embodied Neurocognitive Model
Human infants are able to acquire natural language seemingly easily at a...
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Graph Policy Network for Transferable Active Learning on Graphs
Graph neural networks (GNNs) have been attracting increasing popularity ...
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Few-Shot Generative Conversational Query Rewriting
Conversational query rewriting aims to reformulate a concise conversatio...
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Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen
The curse of knowledge can impede communication between experts and laym...
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Joint Keyphrase Chunking and Salience Ranking with BERT
An effective keyphrase extraction system requires to produce self-contai...
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KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and Completion
Knowledge graphs (KGs) contains an instance-level entity graph and an on...
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MAVEN: A Massive General Domain Event Detection Dataset
Event detection (ED), which identifies event trigger words and classifie...
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How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence
Legal Artificial Intelligence (LegalAI) focuses on applying the technolo...
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Train No Evil: Selective Masking for Task-guided Pre-training
Recently, pre-trained language models mostly follow the pre-training-the...
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Coreferential Reasoning Learning for Language Representation
Language representation models such as BERT could effectively capture co...
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More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
Relational facts are an important component of human knowledge, which ar...
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Selective Weak Supervision for Neural Information Retrieval
This paper democratizes neural information retrieval to scenarios where ...
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Lexical Sememe Prediction using Dictionary Definitions by Capturing Local Semantic Correspondence
Sememes, defined as the minimum semantic units of human languages in lin...
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CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension
We present a Chinese judicial reading comprehension (CJRC) dataset which...
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Towards Building a Multilingual Sememe Knowledge Base: Predicting Sememes for BabelNet Synsets
A sememe is defined as the minimum semantic unit of human languages. Sem...
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JEC-QA: A Legal-Domain Question Answering Dataset
We present JEC-QA, the largest question answering dataset in the legal d...
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CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain
In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Simila...
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KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Pre-trained language representation models (PLMs) learn effective langua...
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Incentivized Exploration for Multi-Armed Bandits under Reward Drift
We study incentivized exploration for the multi-armed bandit (MAB) probl...
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Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective large-scale traffic state prediction system is...
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Conversation Generation with Concept Flow
Human conversations naturally evolve around related entities and connect...
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Multi-Paragraph Reasoning with Knowledge-enhanced Graph Neural Network
Multi-paragraph reasoning is indispensable for open-domain question answ...
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Adversarial Language Games for Advanced Natural Language Intelligence
While adversarial games have been well studied in various board games an...
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Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations
Deep neural networks usually require massive labeled data, which restric...
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Learning to Annotate: Modularizing Data Augmentation for TextClassifiers with Natural Language Explanations
Deep neural networks usually require massive labeled data, which restric...
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FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
We present FewRel 2.0, a more challenging task to investigate two aspect...
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NumNet: Machine Reading Comprehension with Numerical Reasoning
Numerical reasoning, such as addition, subtraction, sorting and counting...
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Towards Scalable Koopman Operator Learning: Convergence Rates and A Distributed Learning Algorithm
In this paper, we propose an alternating optimization algorithm to the n...
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OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
OpenNRE is an open-source and extensible toolkit that provides a unified...
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Course Concept Expansion in MOOCs with External Knowledge and Interactive Game
As Massive Open Online Courses (MOOCs) become increasingly popular, it i...
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Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations
Multi-hop knowledge graph (KG) reasoning is an effective and explainable...
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