Search Results for author: Xian Wu

Found 67 papers, 24 papers with code

Biomedical Entity Linking as Multiple Choice Question Answering

no code implementations23 Feb 2024 Zhenxi Lin, Ziheng Zhang, Xian Wu, Yefeng Zheng

Although biomedical entity linking (BioEL) has made significant progress with pre-trained language models, challenges still exist for fine-grained and long-tailed entities.

Entity Linking Multiple-choice +1

Large Language Model Distilling Medication Recommendation Model

1 code implementation5 Feb 2024 Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Zijian Zhang, Feng Tian, Yefeng Zheng

In this paper, we introduce a novel approach called Large Language Model Distilling Medication Recommendation (LEADER).

Knowledge Distillation Language Modelling +2

Large Language Models for Generative Information Extraction: A Survey

1 code implementation29 Dec 2023 Derong Xu, Wei Chen, Wenjun Peng, Chao Zhang, Tong Xu, Xiangyu Zhao, Xian Wu, Yefeng Zheng, Enhong Chen

Information extraction (IE) aims to extract structural knowledge (such as entities, relations, and events) from plain natural language texts.

COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goal

1 code implementation19 Dec 2023 Yi Cheng, Wenge Liu, Jian Wang, Chak Tou Leong, Yi Ouyang, Wenjie Li, Xian Wu, Yefeng Zheng

In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond traditional service-focused dialogue systems.

Improving Biomedical Entity Linking with Retrieval-enhanced Learning

1 code implementation15 Dec 2023 Zhenxi Lin, Ziheng Zhang, Xian Wu, Yefeng Zheng

Biomedical entity linking (BioEL) has achieved remarkable progress with the help of pre-trained language models.

Contrastive Learning Entity Linking +1

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network

1 code implementation15 Nov 2023 Yongqi Zhang, Quanming Yao, Ling Yue, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng

Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patient care and contribute to efficient drug development.

A Survey of Large Language Models in Medicine: Principles, Applications, and Challenges

1 code implementation9 Nov 2023 Hongjian Zhou, Fenglin Liu, Boyang Gu, Xinyu Zou, Jinfa Huang, Jinge Wu, Yiru Li, Sam S. Chen, Peilin Zhou, Junling Liu, Yining Hua, Chengfeng Mao, Chenyu You, Xian Wu, Yefeng Zheng, Lei Clifton, Zheng Li, Jiebo Luo, David A. Clifton

LLMs in medicine to assist physicians for patient care are emerging as a promising research direction in both artificial intelligence and clinical medicine.

MOELoRA: An MOE-based Parameter Efficient Fine-Tuning Method for Multi-task Medical Applications

1 code implementation21 Oct 2023 Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu, Derong Xu, Feng Tian, Yefeng Zheng

Additionally, we propose a task-motivated gate function for all MOELoRA layers that can regulate the contributions of each expert and generate distinct parameters for various tasks.

Multi-Task Learning

Relation-aware Ensemble Learning for Knowledge Graph Embedding

2 code implementations13 Oct 2023 Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng

Knowledge graph (KG) embedding is a fundamental task in natural language processing, and various methods have been proposed to explore semantic patterns in distinctive ways.

Ensemble Learning Knowledge Graph Embedding +1

A Critical Escape Probability Formulation for Enhancing the Transient Stability of Power Systems with System Parameter Design

no code implementations13 Sep 2023 Xian Wu, Kaihua Xi, Aijie Cheng, Chenghui Zhang, Hai Xiang Lin

For the enhancement of the transient stability of power systems, the key is to define a quantitative optimization formulation with system parameters as decision variables.

JoTR: A Joint Transformer and Reinforcement Learning Framework for Dialog Policy Learning

1 code implementation1 Sep 2023 Wai-Chung Kwan, Huimin Wang, Hongru Wang, Zezhong Wang, Xian Wu, Yefeng Zheng, Kam-Fai Wong

In addition, JoTR employs reinforcement learning with a reward-shaping mechanism to efficiently finetune the word-level dialogue policy, which allows the model to learn from its interactions, improving its performance over time.

Action Generation

MultiCapCLIP: Auto-Encoding Prompts for Zero-Shot Multilingual Visual Captioning

1 code implementation25 Aug 2023 Bang Yang, Fenglin Liu, Xian Wu, YaoWei Wang, Xu sun, Yuexian Zou

To deal with the label shortage problem, we present a simple yet effective zero-shot approach MultiCapCLIP that can generate visual captions for different scenarios and languages without any labeled vision-caption pairs of downstream datasets.

Image Captioning Video Captioning

ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation

1 code implementation11 Mar 2023 Bang Yang, Fenglin Liu, Yuexian Zou, Xian Wu, YaoWei Wang, David A. Clifton

We present the results of extensive experiments on twelve NLG tasks, showing that, without using any labeled downstream pairs for training, ZeroNLG generates high-quality and believable outputs and significantly outperforms existing zero-shot methods.

Image Captioning Machine Translation +5

Exploring Social Media for Early Detection of Depression in COVID-19 Patients

1 code implementation23 Feb 2023 Jiageng Wu, Xian Wu, Yining Hua, Shixu Lin, Yefeng Zheng, Jie Yang

Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression.

Knowledge Distillation

Explicit formulas for the Variance of the State of a Linearized Power System driven by Gaussian stochastic disturbances

no code implementations13 Feb 2023 Xian Wu, Kaihua Xi, Aijie Cheng, Hai Xiang Lin, Jan H van Schuppen, Chenghui Zhang

In the linearized system of the power systems, the disturbance is modeled by a Brownian motion process, and the fluctuations are described by the covariance matrix of the associated stochastic process at the invariant probability distribution.

Aligning Source Visual and Target Language Domains for Unpaired Video Captioning

no code implementations22 Nov 2022 Fenglin Liu, Xian Wu, Chenyu You, Shen Ge, Yuexian Zou, Xu sun

To this end, we introduce the unpaired video captioning task aiming to train models without coupled video-caption pairs in target language.

Translation Video Captioning

Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations

4 code implementations21 Nov 2022 Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge, Guoli Song, David A. Clifton, Jie Chen

Most video-and-language representation learning approaches employ contrastive learning, e. g., CLIP, to project the video and text features into a common latent space according to the semantic similarities of text-video pairs.

Ranked #2 on Video Retrieval on LSMDC (text-to-video Mean Rank metric)

Contrastive Learning Representation Learning +5

DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention

no code implementations28 Oct 2022 Fenglin Liu, Xian Wu, Shen Ge, Xuancheng Ren, Wei Fan, Xu sun, Yuexian Zou

To enhance the correlation between vision and language in disentangled spaces, we introduce the visual concepts to DiMBERT which represent visual information in textual format.

Image Captioning Language Modelling +3

Generating Accurate and Faithful Discharge Instructions: Task, Dataset, and Model

2 code implementations23 Oct 2022 Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu sun, Yang Yang, David A. Clifton

We build a benchmark clinical dataset and propose the Re3Writer, which imitates the working patterns of physicians to first retrieve related working experience from historical PIs written by physicians, then reason related medical knowledge.

Prophet Attention: Predicting Attention with Future Attention for Image Captioning

no code implementations19 Oct 2022 Fenglin Liu, Xuancheng Ren, Xian Wu, Wei Fan, Yuexian Zou, Xu sun

Especially for image captioning, the attention based models are expected to ground correct image regions with proper generated words.

Image Captioning

Multi-modal Contrastive Representation Learning for Entity Alignment

1 code implementation COLING 2022 Zhenxi Lin, Ziheng Zhang, Meng Wang, Yinghui Shi, Xian Wu, Yefeng Zheng

Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities.

Ranked #2 on Multi-modal Entity Alignment on UMVM-oea-d-w-v1 (using extra training data)

Contrastive Learning Knowledge Graphs +2

Competence-based Multimodal Curriculum Learning for Medical Report Generation

no code implementations ACL 2021 Fenglin Liu, Shen Ge, Yuexian Zou, Xian Wu

Medical report generation task, which targets to produce long and coherent descriptions of medical images, has attracted growing research interests recently.

Image Captioning Medical Report Generation

Graph-in-Graph Network for Automatic Gene Ontology Description Generation

no code implementations10 Jun 2022 Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Adelaide Woicik, Sheng Wang

This task aims to automatically generate a sentence that describes the function of a GO term belonging to one of the three categories, i. e., molecular function, biological process, and cellular component.


DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches

no code implementations4 May 2022 Xian Wu, Chen Wang, Hongbo Fu, Ariel Shamir, Song-Hai Zhang, Shi-Min Hu

Researchers have explored various ways to generate realistic images from freehand sketches, e. g., for objects and human faces.

Image Generation Sketch-to-Image Translation

End-to-end Spoken Conversational Question Answering: Task, Dataset and Model

no code implementations Findings (NAACL) 2022 Chenyu You, Nuo Chen, Fenglin Liu, Shen Ge, Xian Wu, Yuexian Zou

To evaluate the capacity of SCQA systems in a dialogue-style interaction, we assemble a Spoken Conversational Question Answering (Spoken-CoQA) dataset with more than 40k question-answer pairs from 4k conversations.

Conversational Question Answering Spoken Language Understanding +1

AutoField: Automating Feature Selection in Deep Recommender Systems

1 code implementation19 Apr 2022 Yejing Wang, Xiangyu Zhao, Tong Xu, Xian Wu

Thereby, feature selection is a critical process in developing deep learning-based recommender systems.

AutoML feature selection +1

Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback

no code implementations Findings (NAACL) 2022 Yunfan Hu, Zhaopeng Qiu, Xian Wu

On one hand, the user may exit immediately after clicking the news as he dislikes the news content, leaving the noise in his positive implicit feedback; on the other hand, the user may be recommended multiple interesting news at the same time and only click one of them, producing the noise in his negative implicit feedback.

Denoising News Recommendation

AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

no code implementations18 Mar 2022 Di You, Fenglin Liu, Shen Ge, Xiaoxia Xie, Jing Zhang, Xian Wu

The acquired disease-grounded visual features can better represent the abnormal regions of the input image, which could alleviate data bias problem; 2) MGT module effectively uses the multi-grained features and Transformer framework to generate the long medical report.

Descriptive Image Captioning +1

Conditional Generation Net for Medication Recommendation

1 code implementation14 Feb 2022 Rui Wu, Zhaopeng Qiu, Jiacheng Jiang, Guilin Qi, Xian Wu

Medication recommendation targets to provide a proper set of medicines according to patients' diagnoses, which is a critical task in clinics.

Multi-Label Classification

Knowledge Matters: Radiology Report Generation with General and Specific Knowledge

no code implementations30 Dec 2021 Shuxin Yang, Xian Wu, Shen Ge, Shaohua Kevin Zhou, Li Xiao

In this paper, we propose a knowledge-enhanced radiology report generation approach introduces two types of medical knowledge: 1) General knowledge, which is input independent and provides the broad knowledge for report generation; 2) Specific knowledge, which is input dependent and provides the fine-grained knowledge for report generation.

General Knowledge Image Captioning

NeRF-SR: High-Quality Neural Radiance Fields using Supersampling

1 code implementation3 Dec 2021 Chen Wang, Xian Wu, Yuan-Chen Guo, Song-Hai Zhang, Yu-Wing Tai, Shi-Min Hu

We present NeRF-SR, a solution for high-resolution (HR) novel view synthesis with mostly low-resolution (LR) inputs.

Novel View Synthesis Vocal Bursts Intensity Prediction

EDGE: Explaining Deep Reinforcement Learning Policies

1 code implementation NeurIPS 2021 Wenbo Guo, Xian Wu, Usmann Khan, Xinyu Xing

With the rapid development of deep reinforcement learning (DRL) techniques, there is an increasing need to understand and interpret DRL policies.

MuJoCo Games reinforcement-learning +2

Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model

no code implementations4 Jul 2021 Zhiqi Huang, Fenglin Liu, Xian Wu, Shen Ge, Helin Wang, Wei Fan, Yuexian Zou

As a result, the proposed approach can handle various tasks including: Audio-Oriented Multimodal Machine Comprehension, Machine Reading Comprehension and Machine Listening Comprehension, in a single model, making fair comparisons possible between our model and the existing unimodal MC models.

Knowledge Distillation Machine Reading Comprehension

Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation

no code implementations CVPR 2021 Fenglin Liu, Xian Wu, Shen Ge, Wei Fan, Yuexian Zou

In detail, PoKE explores the posterior knowledge, which provides explicit abnormal visual regions to alleviate visual data bias; PrKE explores the prior knowledge from the prior medical knowledge graph (medical knowledge) and prior radiology reports (working experience) to alleviate textual data bias.

Contrastive Attention for Automatic Chest X-ray Report Generation

no code implementations Findings (ACL) 2021 Fenglin Liu, Changchang Yin, Xian Wu, Shen Ge, Ping Zhang, Yuexian Zou, Xu sun

In addition, according to the analysis, the CA model can help existing models better attend to the abnormal regions and provide more accurate descriptions which are crucial for an interpretable diagnosis.

BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning

no code implementations2 May 2021 Lun Wang, Zaynah Javed, Xian Wu, Wenbo Guo, Xinyu Xing, Dawn Song

Recent research has confirmed the feasibility of backdoor attacks in deep reinforcement learning (RL) systems.

Atari Games Backdoor Attack +2

Control optimization for parametric hamiltonians by pulse reconstruction

no code implementations24 Feb 2021 Piero Luchi, Francesco Turro, Valentina Amitrano, Francesco Pederiva, Xian Wu, Kyle Wendt, Jonathan L Dubois, Sofia Quaglioni

Optimal control techniques provide a means to tailor the control pulses required to generate customized quantum gates, which helps to improve the resilience of quantum simulations to gate errors and device noise.

Quantum Physics

Prophet Attention: Predicting Attention with Future Attention

no code implementations NeurIPS 2020 Fenglin Liu, Xuancheng Ren, Xian Wu, Shen Ge, Wei Fan, Yuexian Zou, Xu sun

Especially for image captioning, the attention based models are expected to ground correct image regions with proper generated words.

Image Captioning

Automatic Distractor Generation for Multiple Choice Questions in Standard Tests

no code implementations COLING 2020 Zhaopeng Qiu, Xian Wu, Wei Fan

To assess the knowledge proficiency of a learner, multiple choice question is an efficient and widespread form in standard tests.

Distractor Generation Multiple-choice

Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records

no code implementations1 Aug 2020 Jiatu Shi, Huaxiu Yao, Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao

The goal is to facilitate the learning process in the target segments by leveraging the learned knowledge from data-sufficient source segments.

Meta-Learning Relation

Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms

no code implementations NeurIPS 2020 Guy Bresler, Prateek Jain, Dheeraj Nagaraj, Praneeth Netrapalli, Xian Wu

Our improved rate serves as one of the first results where an algorithm outperforms SGD-DD on an interesting Markov chain and also provides one of the first theoretical analyses to support the use of experience replay in practice.


Jointly Predicting Job Performance, Personality, Cognitive Ability, Affect, and Well-Being

no code implementations10 Jun 2020 Pablo Robles-Granda, Suwen Lin, Xian Wu, Sidney D'Mello, Gonzalo J. Martinez, Koustuv Saha, Kari Nies, Gloria Mark, Andrew T. Campbell, Munmun De Choudhury, Anind D. Dey, Julie Gregg, Ted Grover, Stephen M. Mattingly, Shayan Mirjafari, Edward Moskal, Aaron Striegel, Nitesh V. Chawla

In this paper, we create a benchmark for predictive analysis of individuals from a perspective that integrates: physical and physiological behavior, psychological states and traits, and job performance.

Rethinking and Improving Natural Language Generation with Layer-Wise Multi-View Decoding

no code implementations16 May 2020 Fenglin Liu, Xuancheng Ren, Guangxiang Zhao, Chenyu You, Xuewei Ma, Xian Wu, Xu sun

While it is common practice to draw information from only the last encoder layer, recent work has proposed to use representations from different encoder layers for diversified levels of information.

Abstractive Text Summarization Image Captioning +5

JMNet: A joint matting network for automatic human matting

no code implementations14 Apr 2020 Xian Wu, Xiao-Nan Fang, Tao Chen, Fang-Lue Zhang

We propose a novel end-to-end deep learning framework, the Joint Matting Network (JMNet), to automatically generate alpha mattes for human images.

Image Matting Pose Estimation

Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series

no code implementations10 Feb 2020 Xian Wu, Chao Huang, Pablo Roblesgranda, Nitesh Chawla

The prevalence of wearable sensors (e. g., smart wristband) is creating unprecedented opportunities to not only inform health and wellness states of individuals, but also assess and infer personal attributes, including demographic and personality attributes.

Representation Learning Time Series +1

Automated Relational Meta-learning

1 code implementation ICLR 2020 Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li

In order to efficiently learn with small amount of data on new tasks, meta-learning transfers knowledge learned from previous tasks to the new ones.

Few-Shot Image Classification Meta-Learning


no code implementations25 Sep 2019 Xian Wu, Yuandong Tian, Lexing Ying

We apply our theoretical framework to different models for the noise distribution of the policy and value network as well as the distribution of rewards, and show that for these general models, the sample complexity is polynomial in D, where D is the depth of the search tree.

Board Games

Multi-Grained Named Entity Recognition

1 code implementation ACL 2019 Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip Yu

This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totally nested.

Multi-Grained Named Entity Recognition named-entity-recognition +5

Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model

no code implementations NeurIPS 2018 Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye

In this paper we consider the problem of computing an $\epsilon$-optimal policy of a discounted Markov Decision Process (DMDP) provided we can only access its transition function through a generative sampling model that given any state-action pair samples from the transition function in $O(1)$ time.

Deep Portrait Image Completion and Extrapolation

no code implementations23 Aug 2018 Xian Wu, Rui-Long Li, Fang-Lue Zhang, Jian-Cheng Liu, Jue Wang, Ariel Shamir, Shi-Min Hu

We evaluate our method on public portrait image datasets, and show that it outperforms other state-of-art general image completion methods.


Near-Optimal Time and Sample Complexities for Solving Discounted Markov Decision Process with a Generative Model

1 code implementation5 Jun 2018 Aaron Sidford, Mengdi Wang, Xian Wu, Lin F. Yang, Yinyu Ye

In this paper we consider the problem of computing an $\epsilon$-optimal policy of a discounted Markov Decision Process (DMDP) provided we can only access its transition function through a generative sampling model that given any state-action pair samples from the transition function in $O(1)$ time.

Optimization and Control

Interpretable Video Captioning via Trajectory Structured Localization

no code implementations CVPR 2018 Xian Wu, Guanbin Li, Qingxing Cao, Qingge Ji, Liang Lin

Automatically describing open-domain videos with natural language are attracting increasing interest in the field of artificial intelligence.

Image Captioning Sentence +2

Neural Tensor Factorization

no code implementations13 Feb 2018 Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Nitesh Chawla

Neural collaborative filtering (NCF) and recurrent recommender systems (RRN) have been successful in modeling user-item relational data.

Collaborative Filtering Link Prediction +1

Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes

1 code implementation27 Oct 2017 Aaron Sidford, Mengdi Wang, Xian Wu, Yinyu Ye

Given a discounted Markov Decision Process (DMDP) with $|S|$ states, $|A|$ actions, discount factor $\gamma\in(0, 1)$, and rewards in the range $[-M, M]$, we show how to compute an $\epsilon$-optimal policy, with probability $1 - \delta$ in time \[ \tilde{O}\left( \left(|S|^2 |A| + \frac{|S| |A|}{(1 - \gamma)^3} \right) \log\left( \frac{M}{\epsilon} \right) \log\left( \frac{1}{\delta} \right) \right) ~ .

Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning

no code implementations4 Oct 2017 Dongyu Zhang, Liang Lin, Tianshui Chen, Xian Wu, Wenwei Tan, Ebroul Izquierdo

Sketch portrait generation benefits a wide range of applications such as digital entertainment and law enforcement.

Representation Learning

Learning to Segment Object Candidates via Recursive Neural Networks

no code implementations4 Dec 2016 Tianshui Chen, Liang Lin, Xian Wu, Nong Xiao, Xiaonan Luo

To avoid the exhaustive search over locations and scales, current state-of-the-art object detection systems usually involve a crucial component generating a batch of candidate object proposals from images.

Object object-detection +1

End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning

no code implementations28 Jan 2015 Liliang Zhang, Liang Lin, Xian Wu, Shengyong Ding, Lei Zhang

Sketch-based face recognition is an interesting task in vision and multimedia research, yet it is quite challenging due to the great difference between face photos and sketches.

Face Recognition Representation Learning

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