1 code implementation • 10 Dec 2023 • Yougang Lyu, Jitai Hao, Zihan Wang, Kai Zhao, Shen Gao, Pengjie Ren, Zhumin Chen, Fang Wang, Zhaochun Ren
Multiple defendants in a criminal fact description generally exhibit complex interactions, and cannot be well handled by existing Legal Judgment Prediction (LJP) methods which focus on predicting judgment results (e. g., law articles, charges, and terms of penalty) for single-defendant cases.
2 code implementations • 2 Dec 2023 • Hongyi Wang, Luyang Luo, Fang Wang, Ruofeng Tong, Yen-Wei Chen, Hongjie Hu, Lanfen Lin, Hao Chen
Based on this idea, we design Iteratively Coupled Multiple Instance Learning (ICMIL) to couple the embedder and the bag classifier at a low cost.
no code implementations • 23 Oct 2023 • Ying Liu, Haozhu Wang, Huixue Zhou, Mingchen Li, Yu Hou, Sicheng Zhou, Fang Wang, Rama Hoetzlein, Rui Zhang
It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering.
1 code implementation • 27 Sep 2023 • Yijun Tian, Huan Song, Zichen Wang, Haozhu Wang, Ziqing Hu, Fang Wang, Nitesh V. Chawla, Panpan Xu
While existing work has explored utilizing knowledge graphs (KGs) to enhance language modeling via joint training and customized model architectures, applying this to LLMs is problematic owing to their large number of parameters and high computational cost.
1 code implementation • 24 Sep 2023 • Haoran Wang, Zeshen Tang, Leya Yang, Yaoru Sun, Fang Wang, Siyu Zhang, Yeming Chen
Here, we propose a goal-conditioned HRL framework named Guided Cooperation via Model-based Rollout (GCMR), aiming to bridge inter-layer information synchronization and cooperation by exploiting forward dynamics.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 21 Sep 2023 • Yidong Liu, FuKai Shang, Fang Wang, Rui Xu, Jun Wang, Wei Li, Yao Li, Conghui He
With the advancement of deep learning technologies, general-purpose large models such as GPT-4 have demonstrated exceptional capabilities across various domains.
1 code implementation • 6 Sep 2023 • Shuo Liu, Lulu Han, Xiaoyang Liu, Junli Ren, Fang Wang, YingLiu, Yuanshan Lin
Wherein, a basic module performs target association based on IoU of detection boxes between successive frames to deal with morphological change of fish; an interaction module combines IoU of detection boxes and IoU of fish entity to handle occlusions; a refind module use spatio-temporal information uses spatio-temporal information to overcome the tracking failure resulting from the missed detection by the detector under complex environment.
no code implementations • 26 Jul 2023 • Siyu Zhang, Yeming Chen, Yaoru Sun, Fang Wang, Haibo Shi, Haoran Wang
Visual question answering (VQA) has been intensively studied as a multimodal task that requires effort in bridging vision and language to infer answers correctly.
1 code implementation • 28 Mar 2023 • Hongyi Wang, Luyang Luo, Fang Wang, Ruofeng Tong, Yen-Wei Chen, Hongjie Hu, Lanfen Lin, Hao Chen
In ICMIL, we use category information in the bag-level classifier to guide the patch-level fine-tuning of the patch feature extractor.
1 code implementation • 28 Mar 2023 • Peng Fang, Arijit Khan, Siqiang Luo, Fang Wang, Dan Feng, Zhenli Li, Wei Yin, Yuchao Cao
Graph embedding maps graph nodes to low-dimensional vectors, and is widely adopted in machine learning tasks.
no code implementations • 13 Feb 2023 • Fei Kong, Xiyue Wang, Jinxi Xiang, Sen yang, Xinran Wang, Meng Yue, Jun Zhang, Junhan Zhao, Xiao Han, Yuhan Dong, Biyue Zhu, Fang Wang, Yueping Liu
We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19, 461 whole-slide images of prostate cancer from multiple centers.
1 code implementation • 18 Dec 2022 • Yuncong Li, Fang Wang, Sheng-hua Zhong
Aspect sentiment triplet extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences.
1 code implementation • 15 Apr 2022 • Yuncong Li, Fang Wang, Sheng-hua Zhong
Moreover, the performance of these models on the first type of instance cannot reflect their performance on entire space.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +4
1 code implementation • 14 Mar 2022 • Rui Xia, Chao Xue, Boyu Deng, Fang Wang, JingChao Wang
We study an NLP model called LSRA, which introduces IB with a pyramid-free structure.
1 code implementation • 14 Oct 2021 • Fang Wang, Yuncong Li, Sheng-hua Zhong, Cunxiang Yin, Yancheng He
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term (aspect), sentiment and opinion term (opinion) triplets from sentences and can tell a complete story, i. e., the discussed aspect, the sentiment toward the aspect, and the cause of the sentiment.
no code implementations • 24 Sep 2021 • Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee, Matthew Pastewait, Christian Piers, Jie Liu, Fang Wang, Li Wang, Chiung-Ying Chiu, Wenchi Wang, Christina Jackson, Wei-Lun Chao, Dinggang Shen, Ching-Chang Ko
Our TS-MDL first adopts an end-to-end \emph{i}MeshSegNet method (i. e., a variant of the existing MeshSegNet with both improved accuracy and efficiency) to label each tooth on the downsampled scan.
no code implementations • 31 Aug 2021 • Jingtang Liang, Cheng Wang, Yujie Cheng, Zheng Wang, Fang Wang, Liyu Huang, Zhibin Yu, YuBo Wang
Mitotic figure count is an important marker of tumor proliferation and has been shown to be associated with patients' prognosis.
no code implementations • 26 Jun 2021 • Peng Wang, Gang Xin, Fang Wang
Correspondingly, the basic search behaviour is derived, which constitutes the basic iterative process of a simple optimization system.
no code implementations • 20 May 2021 • Jingyi Zhang, Huolan Zhu, Yongkai Chen, Chenguang Yang, Huimin Cheng, Yi Li, Wenxuan Zhong, Fang Wang
Background: Extensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate.
5 code implementations • 29 Mar 2021 • Yuncong Li, Fang Wang, Wenjun Zhang, Sheng-hua Zhong, Cunxiang Yin, Yancheng He
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences and tries to provide a complete solution for aspect-based sentiment analysis (ABSA).
Ranked #1 on Aspect-Sentiment-Opinion Triplet Extraction on Res14
Aspect-Based Sentiment Analysis Aspect-Sentiment-Opinion Triplet Extraction +2
no code implementations • 25 Mar 2021 • Ruiqing Yan, Lanchang Sun, Fang Wang, XiaoMing Zhang
Though pre-trained language models such as Bert and XLNet, have rapidly advanced the state-of-the-art on many NLP tasks, they implicit semantics only relying on surface information between words in corpus.
no code implementations • 11 Mar 2021 • Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu
The multilingual pre-trained language models (e. g, mBERT, XLM and XLM-R) have shown impressive performance on cross-lingual natural language understanding tasks.
no code implementations • 11 Dec 2020 • Xiaoqi Jiao, Huating Chang, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu
Comprehensive experiments on the evaluation benchmarks demonstrate that 1) layer mapping strategy has a significant effect on task-agnostic BERT distillation and different layer mappings can result in quite different performances; 2) the optimal layer mapping strategy from the proposed search process consistently outperforms the other heuristic ones; 3) with the optimal layer mapping, our student model achieves state-of-the-art performance on the GLUE tasks.
no code implementations • 2 May 2020 • Yimin Hou, Shuyue Jia, Xiangmin Lun, Shu Zhang, Tao Chen, Fang Wang, Jinglei Lv
The introduced deep feature mining approach can precisely recognize human motion intents from raw EEG signals, which paves the road to translate the EEG based MI recognition to practical BCI systems.
7 code implementations • Findings of the Association for Computational Linguistics 2020 • Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, Qun Liu
To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer-based models.
Ranked #1 on Natural Language Inference on MultiNLI Dev
1 code implementation • CONLL 2018 • Yufei Chen, Sheng Huang, Fang Wang, Junjie Cao, Weiwei Sun, Xiaojun Wan
We present experiments for cross-domain semantic dependency analysis with a neural Maximum Subgraph parser.
no code implementations • COLING 2018 • Xiaoqi Jiao, Fang Wang, Dan Feng
This paper proposes a simple CNN model for creating general-purpose sentence embeddings that can transfer easily across domains and can also act as effective initialization for downstream tasks.
no code implementations • 3 Jun 2017 • Hu Han, Anil K. Jain, Fang Wang, Shiguang Shan, Xilin Chen
In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes.
Ranked #5 on Facial Attribute Classification on LFWA
no code implementations • 3 Oct 2016 • Cornelia Fermüller, Fang Wang, Yezhou Yang, Konstantinos Zampogiannis, Yi Zhang, Francisco Barranco, Michael Pfeiffer
In psychophysical experiments, we evaluated human observers' skills in predicting actions from video sequences of different length, depicting the hand movement in the preparation and execution of actions before and after contact with the object.
no code implementations • 18 Nov 2015 • Aiwen Jiang, Fang Wang, Fatih Porikli, Yi Li
We then feed the episodes to a standard question answering module together with the contextual visual information and linguistic information.
no code implementations • CVPR 2015 • Fang Wang, Le Kang, Yi Li
Almost always in state of the art approaches a large amount of "best views" are computed for 3D models, with the hope that the query sketch matches one of these 2D projections of 3D models using predefined features.
no code implementations • CVPR 2013 • Fang Wang, Yi Li
Our method outperformed the state of the art on the LSP, both in the scenarios when the training images are from the same dataset and from the PARSE dataset.
no code implementations • 23 Apr 2013 • Fang Wang, Yi Li
When the structure of the compositional parts is a tree, we derive an efficient approach to estimating human poses in images.