Search Results for author: Xu Han

Found 84 papers, 50 papers with code

BMInf: An Efficient Toolkit for Big Model Inference and Tuning

1 code implementation ACL 2022 Xu Han, Guoyang Zeng, Weilin Zhao, Zhiyuan Liu, Zhengyan Zhang, Jie zhou, Jun Zhang, Jia Chao, Maosong Sun

In recent years, large-scale pre-trained language models (PLMs) containing billions of parameters have achieved promising results on various NLP tasks.

Quantization

Meta Reinforcement Learning with Successor Feature Based Context

no code implementations29 Jul 2022 Xu Han, Feng Wu

Most reinforcement learning (RL) methods only focus on learning a single task from scratch and are not able to use prior knowledge to learn other tasks more effectively.

Continuous Control Meta Reinforcement Learning +1

GACT: Activation Compressed Training for Generic Network Architectures

1 code implementation22 Jun 2022 Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, Alvin Cheung

Training large neural network (NN) models requires extensive memory resources, and Activation Compressed Training (ACT) is a promising approach to reduce training memory footprint.

Likelihood ratio test for structural changes in factor models

no code implementations16 Jun 2022 Jushan Bai, Jiangtao Duan, Xu Han

This paper considers the likelihood ratio (LR) test for a variance change in the estimated factors.

Quantum Kerr Learning

no code implementations20 May 2022 Junyu Liu, Changchun Zhong, Matthew Otten, Cristian L. Cortes, Chaoyang Ti, Stephen K Gray, Xu Han

Quantum machine learning is a rapidly evolving area that could facilitate important applications for quantum computing and significantly impact data science.

Sampling-based Fast Gradient Rescaling Method for Highly Transferable Adversarial Attacks

no code implementations6 Apr 2022 Xu Han, Anmin Liu, Yifeng Xiong, Yanbo Fan, Kun He

Deviation between the original gradient and the generated noises may lead to inaccurate gradient update estimation and suboptimal solutions for adversarial transferability, which is crucial for black-box attacks.

Predicting Physics in Mesh-reduced Space with Temporal Attention

no code implementations ICLR 2022 Xu Han, Han Gao, Tobias Pfaff, Jian-Xun Wang, Li-Ping Liu

Graph-based next-step prediction models have recently been very successful in modeling complex high-dimensional physical systems on irregular meshes.

Decoupled Low-light Image Enhancement

1 code implementation29 Nov 2021 Shijie Hao, Xu Han, Yanrong Guo, Meng Wang

On the other hand, since the parameter matrix learned from the first stage is aware of the lightness distribution and the scene structure, it can be incorporated into the second stage as the complementary information.

Low-Light Image Enhancement

OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication

1 code implementation16 Sep 2021 Runsheng Xu, Hao Xiang, Xin Xia, Xu Han, Jinlong Li, Jiaqi Ma

We then construct a comprehensive benchmark with a total of 16 implemented models to evaluate several information fusion strategies~(i. e. early, late, and intermediate fusion) with state-of-the-art LiDAR detection algorithms.

3D Object Detection

PPT: Pre-trained Prompt Tuning for Few-shot Learning

1 code implementation ACL 2022 Yuxian Gu, Xu Han, Zhiyuan Liu, Minlie Huang

To ensure the generalization of PPT, we formulate similar classification tasks into a unified task form and pre-train soft prompts for this unified task.

Few-Shot Learning

Prompt-Learning for Fine-Grained Entity Typing

no code implementations24 Aug 2021 Ning Ding, Yulin Chen, Xu Han, Guangwei Xu, Pengjun Xie, Hai-Tao Zheng, Zhiyuan Liu, Juanzi Li, Hong-Gee Kim

In this work, we investigate the application of prompt-learning on fine-grained entity typing in fully supervised, few-shot and zero-shot scenarios.

Entity Typing Language Modelling +3

Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

no code implementations22 Jul 2021 Xiaofeng Liu, Bo Hu, Linghao Jin, Xu Han, Fangxu Xing, Jinsong Ouyang, Jun Lu, Georges El Fakhri, Jonghye Woo

In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training.

Bayesian Inference Domain Generalization

CPM-2: Large-scale Cost-effective Pre-trained Language Models

2 code implementations20 Jun 2021 Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan YAO, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun

We present a suite of cost-effective techniques for the use of PLMs to deal with the efficiency issues of pre-training, fine-tuning, and inference.

Nonparametric Empirical Bayes Estimation and Testing for Sparse and Heteroscedastic Signals

1 code implementation16 Jun 2021 Junhui Cai, Xu Han, Ya'acov Ritov, Linda Zhao

In contrast to the state-of-the-art methods, the proposed methods solve the estimation and testing problem at once with several merits: 1) an accurate sparsity estimation; 2) point estimates with shrinkage/soft-thresholding property; 3) credible intervals for uncertainty quantification; 4) an optimal multiple testing procedure that controls false discovery rate.

Pre-processing with Orthogonal Decompositions for High-dimensional Explanatory Variables

no code implementations16 Jun 2021 Xu Han, Ethan X Fang, Cheng Yong Tang

Strong correlations between explanatory variables are problematic for high-dimensional regularized regression methods.

Open Hierarchical Relation Extraction

1 code implementation NAACL 2021 Kai Zhang, Yuan YAO, Ruobing Xie, Xu Han, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun

To establish the bidirectional connections between OpenRE and relation hierarchy, we propose the task of open hierarchical relation extraction and present a novel OHRE framework for the task.

Relation Extraction

Fully Hyperbolic Neural Networks

1 code implementation ACL 2022 Weize Chen, Xu Han, Yankai Lin, Hexu Zhao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Hyperbolic neural networks have shown great potential for modeling complex data.

Knowledge Inheritance for Pre-trained Language Models

2 code implementations NAACL 2022 Yujia Qin, Yankai Lin, Jing Yi, Jiajie Zhang, Xu Han, Zhengyan Zhang, Yusheng Su, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Specifically, we introduce a pre-training framework named "knowledge inheritance" (KI) and explore how could knowledge distillation serve as auxiliary supervision during pre-training to efficiently learn larger PLMs.

Domain Adaptation Knowledge Distillation +1

PTR: Prompt Tuning with Rules for Text Classification

2 code implementations24 May 2021 Xu Han, Weilin Zhao, Ning Ding, Zhiyuan Liu, Maosong Sun

This indicates that PTR is a promising approach to take advantage of both human prior knowledge and PLMs for those complicated classification tasks.

Classification Natural Language Inference +3

Manual Evaluation Matters: Reviewing Test Protocols of Distantly Supervised Relation Extraction

1 code implementation Findings (ACL) 2021 Tianyu Gao, Xu Han, Keyue Qiu, Yuzhuo Bai, Zhiyu Xie, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Distantly supervised (DS) relation extraction (RE) has attracted much attention in the past few years as it can utilize large-scale auto-labeled data.

Relation Extraction

Few-NERD: A Few-Shot Named Entity Recognition Dataset

4 code implementations ACL 2021 Ning Ding, Guangwei Xu, Yulin Chen, Xiaobin Wang, Xu Han, Pengjun Xie, Hai-Tao Zheng, Zhiyuan Liu

In this paper, we present Few-NERD, a large-scale human-annotated few-shot NER dataset with a hierarchy of 8 coarse-grained and 66 fine-grained entity types.

few-shot-ner Few-shot NER +2

Visual Distant Supervision for Scene Graph Generation

1 code implementation ICCV 2021 Yuan YAO, Ao Zhang, Xu Han, Mengdi Li, Cornelius Weber, Zhiyuan Liu, Stefan Wermter, Maosong Sun

In this work, we propose visual distant supervision, a novel paradigm of visual relation learning, which can train scene graph models without any human-labeled data.

Graph Generation Predicate Classification +1

Quasi-maximum likelihood estimation of break point in high-dimensional factor models

no code implementations25 Feb 2021 Jiangtao Duan, Jushan Bai, Xu Han

This paper estimates the break point for large-dimensional factor models with a single structural break in factor loadings at a common unknown date.

CSS-LM: A Contrastive Framework for Semi-supervised Fine-tuning of Pre-trained Language Models

1 code implementation7 Feb 2021 Yusheng Su, Xu Han, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Peng Li, Jie zhou, Maosong Sun

We then perform contrastive semi-supervised learning on both the retrieved unlabeled and original labeled instances to help PLMs capture crucial task-related semantic features.

Identity-aware Facial Expression Recognition in Compressed Video

no code implementations1 Jan 2021 Xiaofeng Liu, Linghao Jin, Xu Han, Jun Lu, Jane You, Lingsheng Kong

In the up to two orders of magnitude compressed domain, we can explicitly infer the expression from the residual frames and possible to extract identity factors from the I frame with a pre-trained face recognition network.

Face Recognition Facial Expression Recognition

GAN Ensemble for Anomaly Detection

1 code implementation14 Dec 2020 Xu Han, Xiaohui Chen, Li-Ping Liu

Motivated by the observation that GAN ensembles often outperform single GANs in generation tasks, we propose to construct GAN ensembles for anomaly detection.

Anomaly Detection

Neural Gibbs Sampling for Joint Event Argument Extraction

1 code implementation Asian Chapter of the Association for Computational Linguistics 2020 Xiaozhi Wang, Shengyu Jia, Xu Han, Zhiyuan Liu, Juanzi Li, Peng Li, Jie zhou

Existing EAE methods either extract each event argument roles independently or sequentially, which cannot adequately model the joint probability distribution among event arguments and their roles.

Event Argument Extraction Event Extraction

Deep Reinforcement Learning of Transition States

no code implementations13 Nov 2020 Jun Zhang, Yao-Kun Lei, Zhen Zhang, Xu Han, Maodong Li, Lijiang Yang, Yi Isaac Yang, Yi Qin Gao

Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL$^\ddag$) to automatically unravel chemical reaction mechanisms.

reinforcement-learning

Denoising Relation Extraction from Document-level Distant Supervision

1 code implementation EMNLP 2020 Chaojun Xiao, Yuan YAO, Ruobing Xie, Xu Han, Zhiyuan Liu, Maosong Sun, Fen Lin, Leyu Lin

Distant supervision (DS) has been widely used to generate auto-labeled data for sentence-level relation extraction (RE), which improves RE performance.

Denoising Relation Extraction

Mutual Information Regularized Identity-aware Facial ExpressionRecognition in Compressed Video

no code implementations20 Oct 2020 Xiaofeng Liu, Linghao Jin, Xu Han, Jane You

In the up to two orders of magnitude compressed domain, we can explicitly infer the expression from the residual frames and possibly extract identity factors from the I frame with a pre-trained face recognition network.

Face Recognition Facial Expression Recognition

Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

1 code implementation EMNLP 2020 Xin Lv, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu, Wei zhang, Yichi Zhang, Hao Kong, Suhui Wu

On the one hand, sparse KGs contain less information, which makes it difficult for the model to choose correct paths.

Learning from Context or Names? An Empirical Study on Neural Relation Extraction

1 code implementation EMNLP 2020 Hao Peng, Tianyu Gao, Xu Han, Yankai Lin, Peng Li, Zhiyuan Liu, Maosong Sun, Jie zhou

We find that (i) while context is the main source to support the predictions, RE models also heavily rely on the information from entity mentions, most of which is type information, and (ii) existing datasets may leak shallow heuristics via entity mentions and thus contribute to the high performance on RE benchmarks.

Relation Extraction

IsOBS: An Information System for Oracle Bone Script

no code implementations EMNLP 2020 Xu Han, Yuzhuo Bai, Keyue Qiu, Zhiyuan Liu, Maosong Sun

Oracle bone script (OBS) is the earliest known ancient Chinese writing system and the ancestor of modern Chinese.

Few-Shot Learning

CokeBERT: Contextual Knowledge Selection and Embedding towards Enhanced Pre-Trained Language Models

1 code implementation29 Sep 2020 Yusheng Su, Xu Han, Zhengyan Zhang, Peng Li, Zhiyuan Liu, Yankai Lin, Jie zhou, Maosong Sun

In this paper, we propose a novel framework named Coke to dynamically select contextual knowledge and embed knowledge context according to textual context for PLMs, which can avoid the effect of redundant and ambiguous knowledge in KGs that cannot match the input text.

Knowledge Graphs

A Deep Network for Joint Registration and Reconstruction of Images with Pathologies

no code implementations17 Aug 2020 Xu Han, Zhengyang Shen, Zhenlin Xu, Spyridon Bakas, Hamed Akbari, Michel Bilello, Christos Davatzikos, Marc Niethammer

They are therefore not designed for the registration of images with strong pathologies for example in the context of brain tumors, and traumatic brain injuries.

Image Registration

Continual Relation Learning via Episodic Memory Activation and Reconsolidation

no code implementations ACL 2020 Xu Han, Yi Dai, Tianyu Gao, Yankai Lin, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

Continual relation learning aims to continually train a model on new data to learn incessantly emerging novel relations while avoiding catastrophically forgetting old relations.

Continual Learning

Adversarial Language Games for Advanced Natural Language Intelligence

no code implementations5 Nov 2019 Yuan Yao, Haoxi Zhong, Zhengyan Zhang, Xu Han, Xiaozhi Wang, Chaojun Xiao, Guoyang Zeng, Zhiyuan Liu, Maosong Sun

In this work, we propose a challenging adversarial language game called Adversarial Taboo as an example, in which an attacker and a defender compete around a target word.

Board Games Natural Language Processing

HMEAE: Hierarchical Modular Event Argument Extraction

1 code implementation IJCNLP 2019 Xiaozhi Wang, Ziqi Wang, Xu Han, Zhiyuan Liu, Juanzi Li, Peng Li, Maosong Sun, Jie zhou, Xiang Ren

Existing event extraction methods classify each argument role independently, ignoring the conceptual correlations between different argument roles.

Event Argument Extraction Event Extraction +1

VoteNet+ : An Improved Deep Learning Label Fusion Method for Multi-atlas Segmentation

no code implementations1 Nov 2019 Zhipeng Ding, Xu Han, Marc Niethammer

Specifically, we first illustrate that using a deep convolutional neural network to predict atlas probabilities can better distinguish correct atlas labels from incorrect ones than relying on image intensity difference as is typical in JLF.

FewRel 2.0: Towards More Challenging Few-Shot Relation Classification

1 code implementation IJCNLP 2019 Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie zhou

We present FewRel 2. 0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of instances?

Classification Domain Adaptation +2

OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction

1 code implementation IJCNLP 2019 Xu Han, Tianyu Gao, Yuan YAO, Demin Ye, Zhiyuan Liu, Maosong Sun

OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE).

Information Retrieval Question Answering +1

Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations

1 code implementation IJCNLP 2019 Xin Lv, Yuxian Gu, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu

Multi-hop knowledge graph (KG) reasoning is an effective and explainable method for predicting the target entity via reasoning paths in query answering (QA) task.

Link Prediction Meta-Learning

Neural Snowball for Few-Shot Relation Learning

1 code implementation29 Aug 2019 Tianyu Gao, Xu Han, Ruobing Xie, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun

To address new relations with few-shot instances, we propose a novel bootstrapping approach, Neural Snowball, to learn new relations by transferring semantic knowledge about existing relations.

Knowledge Graphs Relation Extraction

Efficient training and design of photonic neural network through neuroevolution

no code implementations4 Aug 2019 Tian Zhang, Jia Wang, Yihang Dan, Yuxiang Lanqiu, Jian Dai, Xu Han, Xiaojuan Sun, Kun Xu

Recently, optical neural networks (ONNs) integrated in photonic chips has received extensive attention because they are expected to implement the same pattern recognition tasks in the electronic platforms with high efficiency and low power consumption.

GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification

2 code implementations ACL 2019 Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, LiFeng Wang, Changcheng Li, Maosong Sun

Fact verification (FV) is a challenging task which requires to retrieve relevant evidence from plain text and use the evidence to verify given claims.

Fact Verification

Quantifying Similarity between Relations with Fact Distribution

1 code implementation ACL 2019 Weize Chen, Hao Zhu, Xu Han, Zhiyuan Liu, Maosong Sun

We introduce a conceptually simple and effective method to quantify the similarity between relations in knowledge bases.

General Classification Open Information Extraction

DocRED: A Large-Scale Document-Level Relation Extraction Dataset

4 code implementations ACL 2019 Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zheng-Hao Liu, Zhiyuan Liu, Lixin Huang, Jie zhou, Maosong Sun

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs.

Relation Extraction

Adversarial Training for Weakly Supervised Event Detection

1 code implementation NAACL 2019 Xiaozhi Wang, Xu Han, Zhiyuan Liu, Maosong Sun, Peng Li

Modern weakly supervised methods for event detection (ED) avoid time-consuming human annotation and achieve promising results by learning from auto-labeled data.

Event Detection

ERNIE: Enhanced Language Representation with Informative Entities

1 code implementation ACL 2019 Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, Qun Liu

Neural language representation models such as BERT pre-trained on large-scale corpora can well capture rich semantic patterns from plain text, and be fine-tuned to consistently improve the performance of various NLP tasks.

Entity Linking Entity Typing +5

VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation

no code implementations18 Apr 2019 Zhipeng Ding, Xu Han, Marc Niethammer

Experiments on 3D brain MRI data show that by selecting a good initial atlas set MAS with VoteNet significantly outperforms a number of other label fusion strategies as well as a direct DL segmentation approach.

Medical Image Segmentation Semantic Segmentation

Networks for Joint Affine and Non-parametric Image Registration

2 code implementations CVPR 2019 Zhengyang Shen, Xu Han, Zhenlin Xu, Marc Niethammer

In contrast to existing approaches, our framework combines two registration methods: an affine registration and a vector momentum-parameterized stationary velocity field (vSVF) model.

Image Registration Medical Image Registration

Knowledge Representation Learning: A Quantitative Review

2 code implementations28 Dec 2018 Yankai Lin, Xu Han, Ruobing Xie, Zhiyuan Liu, Maosong Sun

Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowledge-driven tasks.

General Classification Information Retrieval +7

Robust low-rank multilinear tensor approximation for a joint estimation of the multilinear rank and the loading matrices

no code implementations14 Nov 2018 Xu Han, Laurent Albera, Amar Kachenoura, Huazhong Shu, Lotfi Senhadji

Based on the low-rank property and an over-estimation of the core tensor, this joint estimation problem is solved by promoting (group) sparsity of the over-estimated core tensor.

Tensor Decomposition

DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction

1 code implementation ACL 2019 Shun Zheng, Xu Han, Yankai Lin, Peilin Yu, Lu Chen, Ling Huang, Zhiyuan Liu, Wei Xu

To demonstrate the effectiveness of DIAG-NRE, we apply it to two real-world datasets and present both significant and interpretable improvements over state-of-the-art methods.

Relation Extraction

OpenKE: An Open Toolkit for Knowledge Embedding

1 code implementation EMNLP 2018 Xu Han, Shulin Cao, Xin Lv, Yankai Lin, Zhiyuan Liu, Maosong Sun, Juanzi Li

We release an open toolkit for knowledge embedding (OpenKE), which provides a unified framework and various fundamental models to embed knowledge graphs into a continuous low-dimensional space.

Information Retrieval Knowledge Graphs +2

Sentence Segmentation for Classical Chinese Based on LSTM with Radical Embedding

no code implementations5 Oct 2018 Xu Han, Hongsu Wang, Sanqian Zhang, Qunchao Fu, Jun S. Liu

In this paper, we develop a low than character feature embedding called radical embedding, and apply it on LSTM model for sentence segmentation of pre modern Chinese texts.

Sentence segmentation

Hierarchical Relation Extraction with Coarse-to-Fine Grained Attention

1 code implementation EMNLP 2018 Xu Han, Pengfei Yu, Zhiyuan Liu, Maosong Sun, Peng Li

In this paper, we aim to incorporate the hierarchical information of relations for distantly supervised relation extraction and propose a novel hierarchical attention scheme.

Knowledge Graphs Relation Extraction

Adversarial Multi-lingual Neural Relation Extraction

1 code implementation COLING 2018 Xiaozhi Wang, Xu Han, Yankai Lin, Zhiyuan Liu, Maosong Sun

To address these issues, we propose an adversarial multi-lingual neural relation extraction (AMNRE) model, which builds both consistent and individual representations for each sentence to consider the consistency and diversity among languages.

Question Answering Relation Extraction

Denoising Distant Supervision for Relation Extraction via Instance-Level Adversarial Training

no code implementations28 May 2018 Xu Han, Zhiyuan Liu, Maosong Sun

As shown in the experiments on a large-scale benchmark dataset in relation extraction, our denoising method can effectively filter out noisy instances and achieve significant improvements as compared with the state-of-the-art models.

Denoising Relation Extraction

Seed-Point Detection of Clumped Convex Objects by Short-Range Attractive Long-Range Repulsive Particle Clustering

1 code implementation11 Apr 2018 James Kapaldo, Xu Han, Domingo Mery

Locating the center of convex objects is important in both image processing and unsupervised machine learning/data clustering fields.

Efficient Registration of Pathological Images: A Joint PCA/Image-Reconstruction Approach

no code implementations31 Mar 2017 Xu Han, Xiao Yang, Stephen Aylward, Roland Kwitt, Marc Niethammer

Registration involving one or more images containing pathologies is challenging, as standard image similarity measures and spatial transforms cannot account for common changes due to pathologies.

Image Reconstruction

Joint Representation Learning of Text and Knowledge for Knowledge Graph Completion

no code implementations13 Nov 2016 Xu Han, Zhiyuan Liu, Maosong Sun

Joint representation learning of text and knowledge within a unified semantic space enables us to perform knowledge graph completion more accurately.

General Classification Knowledge Graph Completion +2

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