Search Results for author: Wei Peng

Found 92 papers, 38 papers with code

Cross-lingual Feature Extraction from Monolingual Corpora for Low-resource Unsupervised Bilingual Lexicon Induction

no code implementations COLING 2022 Zihao Feng, Hailong Cao, Tiejun Zhao, Weixuan Wang, Wei Peng

Despite their progress in high-resource language settings, unsupervised bilingual lexicon induction (UBLI) models often fail on corpora with low-resource distant language pairs due to insufficient initialization.

Bilingual Lexicon Induction Word Embeddings

Huawei AARC’s Submissions to the WMT21 Biomedical Translation Task: Domain Adaption from a Practical Perspective

no code implementations WMT (EMNLP) 2021 Weixuan Wang, Wei Peng, Xupeng Meng, Qun Liu

This paper describes Huawei Artificial Intelligence Application Research Center’s neural machine translation systems and submissions to the WMT21 biomedical translation shared task.

Domain Adaptation Machine Translation +1

When does Further Pre-training MLM Help? An Empirical Study on Task-Oriented Dialog Pre-training

1 code implementation EMNLP (insights) 2021 Qi Zhu, Yuxian Gu, Lingxiao Luo, Bing Li, Cheng Li, Wei Peng, Minlie Huang, Xiaoyan Zhu

Further pre-training language models on in-domain data (domain-adaptive pre-training, DAPT) or task-relevant data (task-adaptive pre-training, TAPT) before fine-tuning has been shown to improve downstream tasks’ performances.

Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings

1 code implementation EMNLP 2021 Weixuan Wang, Wei Peng, Meng Zhang, Qun Liu

Neural Machine Translation (NMT) has shown a strong ability to utilize local context to disambiguate the meaning of words.

Machine Translation NMT +3

A Survey on Hallucination in Large Vision-Language Models

no code implementations1 Feb 2024 Hanchao Liu, Wenyuan Xue, Yifei Chen, Dapeng Chen, Xiutian Zhao, Ke Wang, Liping Hou, Rongjun Li, Wei Peng

In this comprehensive survey, we dissect LVLM-related hallucinations in an attempt to establish an overview and facilitate future mitigation.

Hallucination

Large language models in healthcare and medical domain: A review

no code implementations12 Dec 2023 Zabir Al Nazi, Wei Peng

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension.

Document Classification named-entity-recognition +4

Towards General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

2 code implementations4 Dec 2023 Mohammed Baharoon, Waseem Qureshi, Jiahong Ouyang, Yanwu Xu, Abdulrhman Aljouie, Wei Peng

To measure the effectiveness and generalizability of DINOv2's feature representations, we analyze the model across medical image analysis tasks including disease classification and organ segmentation on both 2D and 3D images, and under different settings like kNN, few-shot learning, linear-probing, end-to-end fine-tuning, and parameter-efficient fine-tuning.

Few-Shot Learning Organ Segmentation +1

Align before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition

no code implementations27 Nov 2023 Yifei Chen, Dapeng Chen, Ruijin Liu, Sai Zhou, Wenyuan Xue, Wei Peng

With the aligned entities, we feed their text embeddings to a transformer-based video adapter as the queries, which can help extract the semantics of the most important entities from a video to a vector.

Action Recognition Representation Learning +1

Assessing the Reliability of Large Language Model Knowledge

1 code implementation15 Oct 2023 Weixuan Wang, Barry Haddow, Alexandra Birch, Wei Peng

Large language models (LLMs) have been treated as knowledge bases due to their strong performance in knowledge probing tasks.

Hallucination Knowledge Probing +3

Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs

no code implementations7 Oct 2023 Wei Peng, Tomas Bosschieter, Jiahong Ouyang, Robert Paul, Ehsan Adeli, Qingyu Zhao, Kilian M. Pohl

Generative AI models hold great potential in creating synthetic brain MRIs that advance neuroimaging studies by, for example, enriching data diversity.

MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images

no code implementations5 Oct 2023 Yanwu Xu, Li Sun, Wei Peng, Shyam Visweswaran, Kayhan Batmanghelich

This study focuses on two main objectives: (1) the development of a method for creating images based on textual prompts and anatomical components, and (2) the capability to generate new images conditioning on anatomical elements.

Anatomy Image Generation +1

Neuro-Symbolic Recommendation Model based on Logic Query

no code implementations14 Sep 2023 Maonian Wu, Bang Chen, Shaojun Zhu, Bo Zheng, Wei Peng, Mingyi Zhang

A recommendation system assists users in finding items that are relevant to them.

Modality Unifying Network for Visible-Infrared Person Re-Identification

no code implementations ICCV 2023 Hao Yu, Xu Cheng, Wei Peng, Weihao Liu, Guoying Zhao

Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-modality discrepancies and intra-class variations.

Person Re-Identification

PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer

no code implementations29 Aug 2023 Ruijin Liu, Ning Lu, Dapeng Chen, Cheng Li, Zejian yuan, Wei Peng

We present PBFormer, an efficient yet powerful scene text detector that unifies the transformer with a novel text shape representation Polynomial Band (PB).

Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach

1 code implementation17 Aug 2023 Ziyin Zhang, Ning Lu, Minghui Liao, Yongshuai Huang, Cheng Li, Min Wang, Wei Peng

It incorporates a framewise regularization term in CTC loss to emphasize individual supervision, and leverages the maximizing-a-posteriori of latent alignment to solve the inconsistency problem that arises in distillation between CTC-based models.

ChartDETR: A Multi-shape Detection Network for Visual Chart Recognition

no code implementations15 Aug 2023 Wenyuan Xue, Dapeng Chen, Baosheng Yu, Yifei Chen, Sai Zhou, Wei Peng

Visual chart recognition systems are gaining increasing attention due to the growing demand for automatically identifying table headers and values from chart images.

Keypoint Detection

Generative AI for Medical Imaging: extending the MONAI Framework

2 code implementations27 Jul 2023 Walter H. L. Pinaya, Mark S. Graham, Eric Kerfoot, Petru-Daniel Tudosiu, Jessica Dafflon, Virginia Fernandez, Pedro Sanchez, Julia Wolleb, Pedro F. da Costa, Ashay Patel, Hyungjin Chung, Can Zhao, Wei Peng, Zelong Liu, Xueyan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso

We have implemented these models in a generalisable fashion, illustrating that their results can be extended to 2D or 3D scenarios, including medical images with different modalities (like CT, MRI, and X-Ray data) and from different anatomical areas.

Anomaly Detection Denoising +2

Neural-Symbolic Recommendation with Graph-Enhanced Information

1 code implementation11 Jul 2023 Bang Chen, Wei Peng, Maonian Wu, Bo Zheng, Shaojun Zhu

Some researchers use user behavior for logic reasoning to achieve recommendation prediction from the perspective of cognitive reasoning, but this kind of reasoning is a local one and ignores implicit information on a global scale.

Recommendation Systems

Learning Homographic Disambiguation Representation for Neural Machine Translation

no code implementations12 Apr 2023 Weixuan Wang, Wei Peng, Qun Liu

Visualization methods like heatmaps, T-SNE and translation examples are also utilized to demonstrate the effects of the proposed method.

Machine Translation Natural Language Inference +3

Knowledge-augmented Frame Semantic Parsing with Hybrid Prompt-tuning

no code implementations25 Mar 2023 Rui Zhang, Yajing Sun, Jingyuan Yang, Wei Peng

We propose a novel Knowledge-Augmented Frame Semantic Parsing Architecture (KAF-SPA) to enhance semantic representation by incorporating accurate frame knowledge into PLMs during frame semantic parsing.

Knowledge Probing Semantic Parsing +1

Video Action Recognition with Attentive Semantic Units

no code implementations ICCV 2023 Yifei Chen, Dapeng Chen, Ruijin Liu, Hao Li, Wei Peng

Supervised by the semantics of action labels, recent works adapt the visual branch of VLMs to learn video representations.

Action Recognition Temporal Action Localization +1

Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling

no code implementations CVPR 2023 Yongshuai Huang, Ning Lu, Dapeng Chen, Yibo Li, Zecheng Xie, Shenggao Zhu, Liangcai Gao, Wei Peng

The ablation study also validates that the proposed coordinate sequence decoder and the visual-alignment loss are the keys to the success of our method.

Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model

1 code implementation15 Dec 2022 Wei Peng, Ehsan Adeli, Tomas Bosschieter, Sang Hyun Park, Qingyu Zhao, Kilian M. Pohl

As acquiring MRIs is expensive, neuroscience studies struggle to attain a sufficient number of them for properly training deep learning models.

Anatomy

RBF-MGN:Solving spatiotemporal PDEs with Physics-informed Graph Neural Network

no code implementations6 Dec 2022 Zixue Xiang, Wei Peng, Wen Yao

We introduce GNNs into physics-informed learning to better handle irregular domains with unstructured meshes.

IRRGN: An Implicit Relational Reasoning Graph Network for Multi-turn Response Selection

1 code implementation1 Dec 2022 Jingcheng Deng, Hengwei Dai, Xuewei Guo, Yuanchen Ju, Wei Peng

URR aims to implicitly extract dependencies between utterances, as well as utterances and options, and make reasoning with relational graph convolutional networks.

Relational Reasoning

Data Leakage and Evaluation Issues in Micro-Expression Analysis

1 code implementation21 Nov 2022 Tuomas Varanka, Yante Li, Wei Peng, Guoying Zhao

Micro-expressions have drawn increasing interest lately due to various potential applications.

Micro-Expression Recognition

Using Persuasive Writing Strategies to Explain and Detect Health Misinformation

1 code implementation11 Nov 2022 Danial Kamali, Joseph Romain, Huiyi Liu, Wei Peng, Jingbo Meng, Parisa Kordjamshidi

We evaluate fine-tuning and prompt-engineering techniques with pre-trained language models of the BERT family and the generative large language models of the GPT family using persuasive strategies as an additional source of information.

Language Modelling Misinformation +3

FADO: Feedback-Aware Double COntrolling Network for Emotional Support Conversation

no code implementations1 Nov 2022 Wei Peng, Ziyuan Qin, Yue Hu, Yuqiang Xie, Yunpeng Li

The core module in FADO consists of a dual-level feedback strategy selector and a double control reader.

Response Generation

Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks

1 code implementation19 Oct 2022 Wei Peng, Wen Yao, Weien Zhou, Xiaoya Zhang, Weijie Yao

Physics-informed neural networks (PINNs) have been proposed to solve two main classes of problems: data-driven solutions and data-driven discovery of partial differential equations.

regression

Psychology-guided Controllable Story Generation

no code implementations COLING 2022 Yuqiang Xie, Yue Hu, Yunpeng Li, Guanqun Bi, Luxi Xing, Wei Peng

Inspired by psychology theories, we introduce global psychological state chains, which include the needs and emotions of the protagonists, to help a story generation system create more controllable and well-planned stories.

Story Generation

FNeVR: Neural Volume Rendering for Face Animation

1 code implementation21 Sep 2022 Bohan Zeng, Boyu Liu, Hong Li, Xuhui Liu, Jianzhuang Liu, Dapeng Chen, Wei Peng, Baochang Zhang

In FNeVR, we design a 3D Face Volume Rendering (FVR) module to enhance the facial details for image rendering.

Talking Face Generation

Physics-informed MTA-UNet: Prediction of Thermal Stress and Thermal Deformation of Satellites

no code implementations1 Sep 2022 Zeyu Cao, Wen Yao, Wei Peng, Xiaoya Zhang, Kairui Bao

The rapid analysis of thermal stress and deformation plays a pivotal role in the thermal control measures and optimization of the structural design of satellites.

Multi-Task Learning

Positively transitioned sentiment dialogue corpus for developing emotion-affective open-domain chatbots

no code implementations9 Aug 2022 Weixuan Wang, Wei Peng, Chong Hsuan Huang, Haoran Wang

In this paper, we describe a data enhancement method for developing Emily, an emotion-affective open-domain chatbot.

Chatbot

Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry

no code implementations20 Jul 2022 Yawen Cui, Zitong Yu, Wei Peng, Li Liu

Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by avoiding the overfitting and catastrophic forgetting simultaneously.

Few-Shot Class-Incremental Learning Incremental Learning +2

Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue System

1 code implementation24 Jun 2022 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun

Specifically, CFO-Net designs a feedback memory module, including strategy pool and feedback pool, to obtain emotion-aware strategy representation.

Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data

no code implementations14 May 2022 Xu Liu, Wen Yao, Wei Peng, Weien Zhou

Besides, for inverse PDE problems, problem parameters considered as new output layer weights are unified in a framework with forward PDE problems.

Uncertainty Quantification

RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks

1 code implementation2 May 2022 Wei Peng, Weien Zhou, Xiaoya Zhang, Wen Yao, Zheliang Liu

Learning solutions of partial differential equations (PDEs) with Physics-Informed Neural Networks (PINNs) is an attractive alternative approach to traditional solvers due to its flexibility and ease of incorporating observed data.

Computational Efficiency

Control Globally, Understand Locally: A Global-to-Local Hierarchical Graph Network for Emotional Support Conversation

1 code implementation27 Apr 2022 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Yajing Sun, Yunpeng Li

Emotional support conversation aims at reducing the emotional distress of the help-seeker, which is a new and challenging task.

Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks

no code implementations CVPR 2022 Wei Peng, Li Feng, Guoying Zhao, Fang Liu

While most of these methods focus on designing novel reconstruction networks or new training strategies for a given undersampling pattern, e. g., Cartesian undersampling or Non-Cartesian sampling, to date, there is limited research aiming to learn and optimize k-space sampling strategies using deep neural networks.

Image Reconstruction

Hyperbolic Uncertainty Aware Semantic Segmentation

no code implementations16 Mar 2022 Bike Chen, Wei Peng, Xiaofeng Cao, Juha Röning

Semantic segmentation (SS) aims to classify each pixel into one of the pre-defined classes.

Segmentation Self-Driving Cars +1

A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain

no code implementations15 Mar 2022 Kairui Bao, Wen Yao, Xiaoya Zhang, Wei Peng, Yu Li

Second, a physics-driven CNN surrogate with partial differential equation (PDE) residuals as a loss function is utilized for fast meshing (meshing surrogate); then, we present a data-driven surrogate model based on the multi-level reduced-order method, aiming to learn solutions of temperature field in the above regular computational plane (thermal surrogate).

CLSEG: Contrastive Learning of Story Ending Generation

1 code implementation18 Feb 2022 Yuqiang Xie, Yue Hu, Luxi Xing, Yunpeng Li, Wei Peng, Ping Guo

To address these two issues, we propose a novel Contrastive Learning framework for Story Ending Generation (CLSEG), which has two steps: multi-aspect sampling and story-specific contrastive learning.

Contrastive Learning Text Generation

Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks

1 code implementation18 Jan 2022 Xu Liu, Wei Peng, Zhiqiang Gong, Weien Zhou, Wen Yao

In this work, we develop a physics-informed neural network-based temperature field inversion (PINN-TFI) method to solve the TFI-HSS task and a coefficient matrix condition number based position selection of observations (CMCN-PSO) method to select optima positions of noise observations.

TPRM: A Topic-based Personalized Ranking Model for Web Search

no code implementations13 Aug 2021 Minghui Huang, Wei Peng, Dong Wang

Ranking models have achieved promising results, but it remains challenging to design personalized ranking systems to leverage user profiles and semantic representations between queries and documents.

Document Ranking

A novel meta-learning initialization method for physics-informed neural networks

no code implementations23 Jul 2021 Xu Liu, Xiaoya Zhang, Wei Peng, Weien Zhou, Wen Yao

Inspired by this idea, we propose the new Reptile initialization to sample more tasks from the parameterized PDEs and adapt the penalty term of the loss.

Meta-Learning

IDRLnet: A Physics-Informed Neural Network Library

1 code implementation9 Jul 2021 Wei Peng, Jun Zhang, Weien Zhou, Xiaoyu Zhao, Wen Yao, Xiaoqian Chen

Physics Informed Neural Network (PINN) is a scientific computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs).

Coarse-to-Careful: Seeking Semantic-related Knowledge for Open-domain Commonsense Question Answering

no code implementations4 Jul 2021 Luxi Xing, Yue Hu, Jing Yu, Yuqiang Xie, Wei Peng

It is prevalent to utilize external knowledge to help machine answer questions that need background commonsense, which faces a problem that unlimited knowledge will transmit noisy and misleading information.

Question Answering

Joint Deep Reversible Regression Model and Physics-Informed Unsupervised Learning for Temperature Field Reconstruction

1 code implementation22 Jun 2021 Zhiqiang Gong, Weien Zhou, Jun Zhang, Wei Peng, Wen Yao

To solve this problem, this work develops a novel physics-informed deep reversible regression models for temperature field reconstruction of heat-source systems (TFR-HSS), which can better reconstruct the temperature field with limited monitoring points unsupervisedly.

regression

Coreference Augmentation for Multi-Domain Task-Oriented Dialogue State Tracking

no code implementations16 Jun 2021 Ting Han, Chongxuan Huang, Wei Peng

Dialogue State Tracking (DST), which is the process of inferring user goals by estimating belief states given the dialogue history, plays a critical role in task-oriented dialogue systems.

Dialogue State Tracking Task-Oriented Dialogue Systems

MCR-Net: A Multi-Step Co-Interactive Relation Network for Unanswerable Questions on Machine Reading Comprehension

no code implementations8 Mar 2021 Wei Peng, Yue Hu, Jing Yu, Luxi Xing, Yuqiang Xie, Zihao Zhu, Yajing Sun

Most of the existing systems design a simple classifier to determine answerability implicitly without explicitly modeling mutual interaction and relation between the question and passage, leading to the poor performance for determining the unanswerable questions.

Machine Reading Comprehension Question Answering +2

Hyperbolic Deep Neural Networks: A Survey

2 code implementations12 Jan 2021 Wei Peng, Tuomas Varanka, Abdelrahman Mostafa, Henglin Shi, Guoying Zhao

Recently, there has been a rising surge of momentum for deep representation learning in hyperbolic spaces due to theirhigh capacity of modeling data like knowledge graphs or synonym hierarchies, possessing hierarchical structure.

Knowledge Graphs Representation Learning

Robustness Testing of Language Understanding in Task-Oriented Dialog

2 code implementations ACL 2021 Jiexi Liu, Ryuichi Takanobu, Jiaxin Wen, Dazhen Wan, Hongguang Li, Weiran Nie, Cheng Li, Wei Peng, Minlie Huang

Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.

Data Augmentation Natural Language Understanding

A hybrid quantum-classical neural network with deep residual learning

no code implementations14 Dec 2020 Yanying Liang, Wei Peng, Zhu-Jun Zheng, Olli Silvén, Guoying Zhao

In this paper, a novel hybrid quantum-classical neural network with deep residual learning (Res-HQCNN) is proposed.

Bi-directional CognitiveThinking Network for Machine Reading Comprehension

no code implementations COLING 2020 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Jing Yu, Yajing Sun, Xiangpeng Wei

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory.

Machine Reading Comprehension

Bi-directional Cognitive Thinking Network for Machine Reading Comprehension

no code implementations20 Oct 2020 Wei Peng, Yue Hu, Luxi Xing, Yuqiang Xie, Jing Yu, Yajing Sun, Xiangpeng Wei

We propose a novel Bi-directional Cognitive Knowledge Framework (BCKF) for reading comprehension from the perspective of complementary learning systems theory.

Machine Reading Comprehension

MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation

3 code implementations12 Oct 2020 Ting Han, Ximing Liu, Ryuichi Takanobu, Yixin Lian, Chongxuan Huang, Dazhen Wan, Wei Peng, Minlie Huang

In this paper, we introduce MultiWOZ 2. 3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset.

Dialogue State Tracking Natural Language Understanding +1

2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework

no code implementations10 Aug 2020 Haoyu Chen, Zitong Yu, Xin Liu, Wei Peng, Yoon Lee, Guoying Zhao

To address the problem of training on small datasets for action recognition tasks, most prior works are either based on a large number of training samples or require pre-trained models transferred from other large datasets to tackle overfitting problems.

Action Recognition Optical Flow Estimation

Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition

no code implementations30 Jul 2020 Wei Peng, Jingang Shi, Zhaoqiang Xia, Guoying Zhao

In human action recognition, current works introduce a dynamic graph generation mechanism to better capture the underlying semantic skeleton connections and thus improves the performance.

Action Recognition Anatomy +3

Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition

no code implementations17 Jun 2020 Zhaoqiang Xia, Wei Peng, Huai-Qian Khor, Xiaoyi Feng, Guoying Zhao

In this paper, we analyze the influence of learning complexity, including the input complexity and model complexity, and discover that the lower-resolution input data and shallower-architecture model are helpful to ease the degradation of deep models in composite-database task.

Micro Expression Recognition Micro-Expression Recognition +1

Accelerating Physics-Informed Neural Network Training with Prior Dictionaries

1 code implementation17 Apr 2020 Wei Peng, Weien Zhou, Jun Zhang, Wen Yao

Physics-Informed Neural Networks (PINNs) can be regarded as general-purpose PDE solvers, but it might be slow to train PINNs on particular problems, and there is no theoretical guarantee of corresponding error bounds.

Dictionary-based Data Augmentation for Cross-Domain Neural Machine Translation

no code implementations6 Apr 2020 Wei Peng, Chongxuan Huang, Tian-Hao Li, Yun Chen, Qun Liu

Existing data augmentation approaches for neural machine translation (NMT) have predominantly relied on back-translating in-domain (IND) monolingual corpora.

Data Augmentation Machine Translation +2

Applying Cyclical Learning Rate to Neural Machine Translation

no code implementations6 Apr 2020 Choon Meng Lee, Jianfeng Liu, Wei Peng

In training deep learning networks, the optimizer and related learning rate are often used without much thought or with minimal tuning, even though it is crucial in ensuring a fast convergence to a good quality minimum of the loss function that can also generalize well on the test dataset.

Machine Translation Translation

BLiMP: The Benchmark of Linguistic Minimal Pairs for English

4 code implementations TACL 2020 Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, Samuel R. Bowman

We introduce The Benchmark of Linguistic Minimal Pairs (shortened to BLiMP), a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English.

Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching

1 code implementation11 Nov 2019 Wei Peng, Xiaopeng Hong, Haoyu Chen, Guoying Zhao

Human action recognition from skeleton data, fueled by the Graph Convolutional Network (GCN), has attracted lots of attention, due to its powerful capability of modeling non-Euclidean structure data.

Action Recognition Neural Architecture Search +1

Huawei's NMT Systems for the WMT 2019 Biomedical Translation Task

no code implementations WS 2019 Wei Peng, Jianfeng Liu, Liangyou Li, Qun Liu

This paper describes Huawei{'}s neural machine translation systems for the WMT 2019 biomedical translation shared task.

Domain Adaptation Machine Translation +3

Asymptotic Distributions and Rates of Convergence for Random Forests via Generalized U-statistics

no code implementations25 May 2019 Wei Peng, Tim Coleman, Lucas Mentch

Random forests remain among the most popular off-the-shelf supervised learning algorithms.

Scalable and Efficient Hypothesis Testing with Random Forests

2 code implementations16 Apr 2019 Tim Coleman, Wei Peng, Lucas Mentch

Throughout the last decade, random forests have established themselves as among the most accurate and popular supervised learning methods.

Two-sample testing

An Integrated Autoencoder-Based Filter for Sparse Big Data

no code implementations13 Apr 2019 Baogui Xin, Wei Peng

We propose a novel filter for sparse big data, called an integrated autoencoder (IAE), which utilizes auxiliary information to mitigate data sparsity.

SPMF: A Social Trust and Preference Segmentation-based Matrix Factorization Recommendation Algorithm

no code implementations11 Mar 2019 Wei Peng, Baogui Xin

The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific areas.

Marketing

Training GANs with Centripetal Acceleration

no code implementations24 Feb 2019 Wei Peng, Yu-Hong Dai, HUI ZHANG, Li-Zhi Cheng

Training generative adversarial networks (GANs) often suffers from cyclic behaviors of iterates.

A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework

no code implementations23 Jan 2019 Wei Peng, Xiaopeng Hong, Yingyue Xu, Guoying Zhao

Facial Micro-expression Recognition (MER) distinguishes the underlying emotional states of spontaneous subtle facialexpressions.

Micro Expression Recognition Micro-Expression Recognition +1

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