no code implementations • COLING 2022 • Xian Wu, Shuxin Yang, Zhaopeng Qiu, Shen Ge, Yangtian Yan, Xingwang Wu, Yefeng Zheng, S. Kevin Zhou, Li Xiao
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
1 code implementation • 5 May 2024 • Zelei Cheng, Xian Wu, Jiahao Yu, Sabrina Yang, Gang Wang, Xinyu Xing
In this paper, we propose RICE, an innovative refining scheme for reinforcement learning that incorporates explanation methods to break through the training bottlenecks.
1 code implementation • 20 Mar 2024 • Xiaoyu Li, Dedong Liu, Lijun Zhao, Yitao Wu, Xian Wu, Jinghan Gao
3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception.
Ranked #1 on 3D Multi-Object Tracking on nuScenes
no code implementations • 15 Mar 2024 • Rui Zhang, Dawei Cheng, Xin Liu, Jie Yang, Yi Ouyang, Xian Wu, Yefeng Zheng
We find that in graph anomaly detection, the homophily distribution differences between different classes are significantly greater than those in homophilic and heterophilic graphs.
no code implementations • 11 Mar 2024 • Jiageng Wu, Xian Wu, Yefeng Zheng, Jie Yang
With appropriate data selection and training techniques, Large Language Models (LLMs) have demonstrated exceptional success in various medical examinations and multiple-choice questions.
no code implementations • 11 Mar 2024 • Jiageng Wu, Xian Wu, Jie Yang
Clinical reasoning refers to the cognitive process that physicians employ in evaluating and managing patients.
1 code implementation • 4 Mar 2024 • Derong Xu, Ziheng Zhang, Zhenxi Lin, Xian Wu, Zhihong Zhu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links.
1 code implementation • 28 Feb 2024 • Derong Xu, Ziheng Zhang, Zhihong Zhu, Zhenxi Lin, Qidong Liu, Xian Wu, Tong Xu, Xiangyu Zhao, Yefeng Zheng, Enhong Chen
In this paper, we propose two model editing studies and validate them in the medical domain: (1) directly editing the factual medical knowledge and (2) editing the explanations to facts.
1 code implementation • 23 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.
1 code implementation • 5 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).
1 code implementation • 29 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.
1 code implementation • 19 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.
1 code implementation • 15 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.
1 code implementation • 15 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.
1 code implementation • 9 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
Therefore, this review aims to provide a detailed overview of the development and deployment of LLMs in medicine, including the challenges and opportunities they face.
2 code implementations • 21 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.
2 code implementations • 13 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.
Ranked #1 on Link Property Prediction on ogbl-biokg
no code implementations • 13 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.
1 code implementation • 1 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.
1 code implementation • 25 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.
no code implementations • 17 May 2023 • Jiageng Wu, Xian Wu, Zhaopeng Qiu, Minghui Li, Yingying Zhang, Yefeng Zheng, Changzheng Yuan, Jie Yang
We systematically evaluate LLMs in the Chinese medical context and develop a novel in-context learning framework to enhance their performance.
1 code implementation • 11 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.
1 code implementation • 23 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.
no code implementations • 13 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.
no code implementations • 22 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.
4 code implementations • 21 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)
1 code implementation • 12 Nov 2022 • Xian Wu, Shuxin Yang, Zhaopeng Qiu, Shen Ge, Yangtian Yan, Xingwang Wu, Yefeng Zheng, S. Kevin Zhou, Li Xiao
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
no code implementations • 28 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.
2 code implementations • 23 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.
no code implementations • 19 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.
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)
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.
no code implementations • 10 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.
no code implementations • 4 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.
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.
Ranked #1 on Spoken Language Understanding on Spoken-SQuAD
1 code implementation • 19 Apr 2022 • Yejing Wang, Xiangyu Zhao, Tong Xu, Xian Wu
Thereby, feature selection is a critical process in developing deep learning-based recommender systems.
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.
no code implementations • 18 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.
1 code implementation • 14 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.
no code implementations • 30 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.
no code implementations • 30 Dec 2021 • Shuxin Yang, Xian Wu, Shen Ge, S. Kevin Zhou, Li Xiao
In clinics, a radiology report is crucial for guiding a patient's treatment.
1 code implementation • 3 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.
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.
no code implementations • NeurIPS 2021 • Fenglin Liu, Chenyu You, Xian Wu, Shen Ge, Sheng Wang, Xu sun
KGAE consists of a pre-constructed knowledge graph, a knowledge-driven encoder and a knowledge-driven decoder.
no code implementations • 18 Sep 2021 • Dongsheng Chen, Zhiqi Huang, Xian Wu, Shen Ge, Yuexian Zou
Intent detection (ID) and Slot filling (SF) are two major tasks in spoken language understanding (SLU).
no code implementations • Findings (ACL) 2021 • Fenglin Liu, Xuancheng Ren, Xian Wu, Bang Yang, Shen Ge, Yuexian Zou, Xu sun
Video captioning combines video understanding and language generation.
no code implementations • 4 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.
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.
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.
no code implementations • 2 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.
no code implementations • 24 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
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.
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.
no code implementations • 1 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.
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.
no code implementations • 10 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.
no code implementations • 16 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.
no code implementations • 14 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.
no code implementations • 10 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.
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.
no code implementations • 25 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.
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.
Ranked #5 on Nested Mention Recognition on ACE 2005
Multi-Grained Named Entity Recognition named-entity-recognition +5
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.
no code implementations • 1 Nov 2018 • Sheng Shen, Yaliang Li, Nan Du, Xian Wu, Yusheng Xie, Shen Ge, Tao Yang, Kai Wang, Xingzheng Liang, Wei Fan
Question answering (QA) has achieved promising progress recently.
no code implementations • 27 Sep 2018 • Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip S. Yu
In this paper, we focus on a new Named Entity Recognition (NER) task, i. e., the Multi-grained NER task.
no code implementations • 23 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.
Graphics
1 code implementation • 5 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
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.
no code implementations • 13 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.
1 code implementation • 27 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) ~ .
no code implementations • 4 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.
no code implementations • 1 Jun 2017 • Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla
From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm.
no code implementations • 4 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.
no code implementations • 28 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.