Search Results for author: Wei Wu

Found 207 papers, 82 papers with code

Task-Oriented Clustering for Dialogues

1 code implementation Findings (EMNLP) 2021 Chenxu Lv, Hengtong Lu, Shuyu Lei, Huixing Jiang, Wei Wu, Caixia Yuan, Xiaojie Wang

A reliable clustering algorithm for task-oriented dialogues can help developer analysis and define dialogue tasks efficiently.

Clustering Representation Learning +1

PlugAT: A Plug and Play Module to Defend against Textual Adversarial Attack

no code implementations COLING 2022 Rui Zheng, Rong Bao, Qin Liu, Tao Gui, Qi Zhang, Xuanjing Huang, Rui Xie, Wei Wu

To reduce the potential side effects of using defense modules, we further propose a novel forgetting restricted adversarial training, which filters out bad adversarial examples that impair the performance of original ones.

Adversarial Attack Domain Adaptation +2

Large-Scale Relation Learning for Question Answering over Knowledge Bases with Pre-trained Language Models

1 code implementation EMNLP 2021 Yuanmeng Yan, Rumei Li, Sirui Wang, Hongzhi Zhang, Zan Daoguang, Fuzheng Zhang, Wei Wu, Weiran Xu

The key challenge of question answering over knowledge bases (KBQA) is the inconsistency between the natural language questions and the reasoning paths in the knowledge base (KB).

Question Answering Relation Extraction +1

Making Parameter-efficient Tuning More Efficient: A Unified Framework for Classification Tasks

1 code implementation COLING 2022 Xin Zhou, Ruotian Ma, Yicheng Zou, Xuanting Chen, Tao Gui, Qi Zhang, Xuanjing Huang, Rui Xie, Wei Wu

Specifically, we re-formulate both token and sentence classification tasks into a unified language modeling task, and map label spaces of different tasks into the same vocabulary space.

Language Modelling Sentence Classification +1

An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism

1 code implementation ACL 2022 Xin Mao, Meirong Ma, Hao Yuan, Jianchao Zhu, ZongYu Wang, Rui Xie, Wei Wu, Man Lan

Entity alignment (EA) aims to discover the equivalent entity pairs between KGs, which is a crucial step for integrating multi-source KGs. For a long time, most researchers have regarded EA as a pure graph representation learning task and focused on improving graph encoders while paying little attention to the decoding process. In this paper, we propose an effective and efficient EA Decoding Algorithm via Third-order Tensor Isomorphism (DATTI). Specifically, we derive two sets of isomorphism equations: (1) Adjacency tensor isomorphism equations and (2) Gramian tensor isomorphism equations. By combining these equations, DATTI could effectively utilize the adjacency and inner correlation isomorphisms of KGs to enhance the decoding process of EA. Extensive experiments on public datasets indicate that our decoding algorithm can deliver significant performance improvements even on the most advanced EA methods, while the extra required time is less than 3 seconds.

Entity Alignment Graph Representation Learning

CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation

1 code implementation ACL 2022 Zichu Fei, Qi Zhang, Tao Gui, Di Liang, Sirui Wang, Wei Wu, Xuanjing Huang

CQG employs a simple method to generate the multi-hop questions that contain key entities in multi-hop reasoning chains, which ensure the complexity and quality of the questions.

Question Generation Question-Generation

Adaptive Resource Allocation for Semantic Communication Networks

no code implementations2 Dec 2023 Lingyi Wang, Wei Wu, Fuhui Zhou, Zhaohui Yang, Zhijin Qin

In order to investigate the performance of semantic communication networks, the quality of service for semantic communication (SC-QoS), including the semantic quantization efficiency (SQE) and transmission latency, is proposed for the first time.


See SIFT in a Rain

no code implementations1 Nov 2023 Wei Wu, Hao Chang, Zhu Li

One is difference of Gaussian (DoG) pyramid recovery network (DPRNet) for SIFT detection, and the other gradients of Gaussian images recovery network (GGIRNet) for SIFT description.

Rain Removal

GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence

no code implementations9 Oct 2023 Zhihua Wen, Zhiliang Tian, Wei Wu, Yuxin Yang, Yanqi Shi, Zhen Huang, Dongsheng Li

Finally, we select the most fitting chains of evidence from the evidence forest and integrate them into the generated story, thereby enhancing the narrative's complexity and credibility.

Retrieval Story Generation

Augmenting transformers with recursively composed multi-grained representations

1 code implementation28 Sep 2023 Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu

More interestingly, the hierarchical structures induced by ReCAT exhibit strong consistency with human-annotated syntactic trees, indicating good interpretability brought by the CIO layers.

Natural Language Inference

Scalable Video Object Segmentation with Simplified Framework

no code implementations ICCV 2023 Qiangqiang Wu, Tianyu Yang, Wei Wu, Antoni Chan

The current popular methods for video object segmentation (VOS) implement feature matching through several hand-crafted modules that separately perform feature extraction and matching.

Semantic Segmentation Video Object Segmentation +1

Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-trained Vision-Language Models

no code implementations ICCV 2023 Kecheng Zheng, Wei Wu, Ruili Feng, Kai Zhu, Jiawei Liu, Deli Zhao, Zheng-Jun Zha, Wei Chen, Yujun Shen

To bring the useful knowledge back into light, we first identify a set of parameters that are important to a given downstream task, then attach a binary mask to each parameter, and finally optimize these masks on the downstream data with the parameters frozen.

Understanding Deep Neural Networks via Linear Separability of Hidden Layers

no code implementations26 Jul 2023 Chao Zhang, Xinyu Chen, Wensheng Li, Lixue Liu, Wei Wu, DaCheng Tao

In this paper, we measure the linear separability of hidden layer outputs to study the characteristics of deep neural networks.

LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs

no code implementations19 Jul 2023 Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T. Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang

We reflect on human and LLMs' different sensitivities to instructions, stress the importance of enabling human-facing safeguards for LLMs, and discuss the potential of training humans and LLMs with complementary skill sets.

Feature Adversarial Distillation for Point Cloud Classification

no code implementations25 Jun 2023 YuXing Lee, Wei Wu

Due to the point cloud's irregular and unordered geometry structure, conventional knowledge distillation technology lost a lot of information when directly used on point cloud tasks.

Classification FAD +4

Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation

1 code implementation17 Jun 2023 Weihao Zeng, Lulu Zhao, Keqing He, Ruotong Geng, Jingang Wang, Wei Wu, Weiran Xu

In this paper, we explore the compositional generalization for multi-attribute controllable dialogue generation where a model can learn from seen attribute values and generalize to unseen combinations.

Dialogue Generation Disentanglement

PreQuant: A Task-agnostic Quantization Approach for Pre-trained Language Models

no code implementations30 May 2023 Zhuocheng Gong, Jiahao Liu, Qifan Wang, Yang Yang, Jingang Wang, Wei Wu, Yunsen Xian, Dongyan Zhao, Rui Yan

While transformer-based pre-trained language models (PLMs) have dominated a number of NLP applications, these models are heavy to deploy and expensive to use.


HUB: Guiding Learned Optimizers with Continuous Prompt Tuning

no code implementations26 May 2023 Gaole Dai, Wei Wu, Ziyu Wang, Jie Fu, Shanghang Zhang, Tiejun Huang

By incorporating hand-designed optimizers as the second component in our hybrid approach, we are able to retain the benefits of learned optimizers while stabilizing the training process and, more importantly, improving testing performance.


RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank

1 code implementation26 May 2023 Jiduan Liu, Jiahao Liu, Qifan Wang, Jingang Wang, Wei Wu, Yunsen Xian, Dongyan Zhao, Kai Chen, Rui Yan

In this paper, we propose a novel approach, RankCSE, for unsupervised sentence representation learning, which incorporates ranking consistency and ranking distillation with contrastive learning into a unified framework.

Contrastive Learning Learning-To-Rank +3

Preference or Intent? Double Disentangled Collaborative Filtering

no code implementations18 May 2023 Chao Wang, HengShu Zhu, Dazhong Shen, Wei Wu, Hui Xiong

In this way, the low-rating items will be treated as positive samples for modeling intents while the negative samples for modeling preferences.

Collaborative Filtering Disentanglement +1

MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videos

1 code implementation CVPR 2023 ZiCheng Zhang, Wei Wu, Wei Sun, Dangyang Tu, Wei Lu, Xiongkuo Min, Ying Chen, Guangtao Zhai

User-generated content (UGC) live videos are often bothered by various distortions during capture procedures and thus exhibit diverse visual qualities.

Video Quality Assessment Visual Question Answering (VQA)

Time-aware Multiway Adaptive Fusion Network for Temporal Knowledge Graph Question Answering

no code implementations24 Feb 2023 Yonghao Liu, Di Liang, Fang Fang, Sirui Wang, Wei Wu, Rui Jiang

For each given question, TMA first extracts the relevant concepts from the KG, and then feeds them into a multiway adaptive module to produce a \emph{temporal-specific} representation of the question.

Graph Question Answering Knowledge Graphs +1

Dual Path Modeling for Semantic Matching by Perceiving Subtle Conflicts

no code implementations24 Feb 2023 Chao Xue, Di Liang, Sirui Wang, Wei Wu, Jing Zhang

To alleviate this problem, we propose a novel Dual Path Modeling Framework to enhance the model's ability to perceive subtle differences in sentence pairs by separately modeling affinity and difference semantics.

Meta-Learning Triplet Network with Adaptive Margins for Few-Shot Named Entity Recognition

1 code implementation14 Feb 2023 Chengcheng Han, Renyu Zhu, Jun Kuang, FengJiao Chen, Xiang Li, Ming Gao, Xuezhi Cao, Wei Wu

We design an improved triplet network to map samples and prototype vectors into a low-dimensional space that is easier to be classified and propose an adaptive margin for each entity type.

few-shot-ner Few-shot NER +5

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion

no code implementations7 Feb 2023 Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He

Specifically, they suffer from two main limitations: 1) existing Graph Convolutional Network (GCN) methods in hyperbolic space rely on tangent space approximation, which would incur approximation error in representation learning, and 2) due to the lack of inner product operation definition in hyperbolic space, existing methods can only measure the plausibility of facts (links) with hyperbolic distance, which is difficult to capture complex data patterns.

Knowledge Graph Completion Representation Learning

RGB-T Multi-Modal Crowd Counting Based on Transformer

1 code implementation8 Jan 2023 Zhengyi Liu, Wei Wu, Yacheng Tan, Guanghui Zhang

To better excavate multi-modal information, we use count-guided multi-modal fusion and modal-guided count enhancement to achieve the impressive performance.

Crowd Counting

Robust Lottery Tickets for Pre-trained Language Models

1 code implementation ACL 2022 Rui Zheng, Rong Bao, Yuhao Zhou, Di Liang, Sirui Wang, Wei Wu, Tao Gui, Qi Zhang, Xuanjing Huang

Recent works on Lottery Ticket Hypothesis have shown that pre-trained language models (PLMs) contain smaller matching subnetworks(winning tickets) which are capable of reaching accuracy comparable to the original models.

Adversarial Robustness

A Curriculum Learning Approach for Multi-domain Text Classification Using Keyword weight Ranking

no code implementations27 Oct 2022 Zilin Yuan, Yinghui Li, Yangning Li, Rui Xie, Wei Wu, Hai-Tao Zheng

We noted that the distinctness of the domain-specific features is different, so in this paper, we propose to use a curriculum learning strategy based on keyword weight ranking to improve the performance of multi-domain text classification models.

text-classification Text Classification

Focus Is What You Need For Chinese Grammatical Error Correction

no code implementations23 Oct 2022 Jingheng Ye, Yinghui Li, Shirong Ma, Rui Xie, Wei Wu, Hai-Tao Zheng

Chinese Grammatical Error Correction (CGEC) aims to automatically detect and correct grammatical errors contained in Chinese text.

Grammatical Error Correction

PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models

no code implementations22 Oct 2022 Yupeng Zhang, Hongzhi Zhang, Sirui Wang, Wei Wu, Zhoujun Li

A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs).

UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning

1 code implementation19 Oct 2022 Yutao Mou, Pei Wang, Keqing He, Yanan Wu, Jingang Wang, Wei Wu, Weiran Xu

Specifically, we design a K-nearest neighbor contrastive learning (KNCL) objective for representation learning and introduce a KNN-based scoring function for OOD detection.

Contrastive Learning Out of Distribution (OOD) Detection +2

Watch the Neighbors: A Unified K-Nearest Neighbor Contrastive Learning Framework for OOD Intent Discovery

1 code implementation17 Oct 2022 Yutao Mou, Keqing He, Pei Wang, Yanan Wu, Jingang Wang, Wei Wu, Weiran Xu

For OOD clustering stage, we propose a KCC method to form compact clusters by mining true hard negative samples, which bridges the gap between clustering and representation learning.

Clustering Contrastive Learning +3

Semi-Supervised Knowledge-Grounded Pre-training for Task-Oriented Dialog Systems

1 code implementation17 Oct 2022 Weihao Zeng, Keqing He, Zechen Wang, Dayuan Fu, Guanting Dong, Ruotong Geng, Pei Wang, Jingang Wang, Chaobo Sun, Wei Wu, Weiran Xu

Recent advances in neural approaches greatly improve task-oriented dialogue (TOD) systems which assist users to accomplish their goals.

Improving Semantic Matching through Dependency-Enhanced Pre-trained Model with Adaptive Fusion

no code implementations16 Oct 2022 Jian Song, Di Liang, Rumei Li, Yuntao Li, Sirui Wang, Minlong Peng, Wei Wu, Yongxin Yu

Transformer-based pre-trained models like BERT have achieved great progress on Semantic Sentence Matching.

XPrompt: Exploring the Extreme of Prompt Tuning

no code implementations10 Oct 2022 Fang Ma, Chen Zhang, Lei Ren, Jingang Wang, Qifan Wang, Wei Wu, Xiaojun Quan, Dawei Song

Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner.

DABERT: Dual Attention Enhanced BERT for Semantic Matching

no code implementations COLING 2022 Sirui Wang, Di Liang, Jian Song, Yuntao Li, Wei Wu

To alleviate this problem, we propose a novel Dual Attention Enhanced BERT (DABERT) to enhance the ability of BERT to capture fine-grained differences in sentence pairs.

From One to Many: Dynamic Cross Attention Networks for LiDAR and Camera Fusion

no code implementations25 Sep 2022 Rui Wan, Shuangjie Xu, Wei Wu, Xiaoyi Zou, Tongyi Cao

The whole fusion architecture named Dynamic Cross Attention Network (DCAN) exploits multi-level image features and adapts to multiple representations of point clouds, which allows DCA to serve as a plug-in fusion module.

Autonomous Driving

One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation

no code implementations20 Sep 2022 Han Hu, Xingwu Zhu, Fuhui Zhou, Wei Wu, Rose Qingyang Hu, Hongbo Zhu

To effectively exploit the benefits enabled by semantic communication, in this paper, we propose a one-to-many semantic communication system.

Transfer Learning

Unified Knowledge Prompt Pre-training for Customer Service Dialogues

no code implementations31 Aug 2022 Keqing He, Jingang Wang, Chaobo Sun, Wei Wu

In this paper, we propose a novel unified knowledge prompt pre-training framework, UFA (\textbf{U}nified Model \textbf{F}or \textbf{A}ll Tasks), for customer service dialogues.

Natural Language Understanding Text Generation

Let Me Check the Examples: Enhancing Demonstration Learning via Explicit Imitation

no code implementations31 Aug 2022 Sirui Wang, Kaiwen Wei, Hongzhi Zhang, Yuntao Li, Wei Wu

Inspired by the human learning process, in this paper, we introduce Imitation DEMOnstration Learning (Imitation-Demo) to strengthen demonstration learning via explicitly imitating human review behaviour, which includes: (1) contrastive learning mechanism to concentrate on the similar demonstrations.

Contrastive Learning

Evaluating Point Cloud from Moving Camera Videos: A No-Reference Metric

1 code implementation30 Aug 2022 ZiCheng Zhang, Wei Sun, Yucheng Zhu, Xiongkuo Min, Wei Wu, Ying Chen, Guangtao Zhai

To tackle the challenge of point cloud quality assessment (PCQA), many PCQA methods have been proposed to evaluate the visual quality levels of point clouds by assessing the rendered static 2D projections.

Image Quality Assessment Point Cloud Quality Assessment +2

Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

1 code implementation16 Aug 2022 Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang

In this work, we present the Knowledge Graph Transformer (kgTransformer) with masked pre-training and fine-tuning strategies.

Long Short-Term Preference Modeling for Continuous-Time Sequential Recommendation

no code implementations1 Aug 2022 Huixuan Chi, Hao Xu, Hao Fu, Mengya Liu, Mengdi Zhang, Yuji Yang, Qinfen Hao, Wei Wu

In particular: 1) existing methods do not explicitly encode and capture the evolution of short-term preference as sequential methods do; 2) simply using last few interactions is not enough for modeling the changing trend.

Sequential Recommendation

Low-Complexity Acoustic Echo Cancellation with Neural Kalman Filtering

1 code implementation23 Jul 2022 Dong Yang, Fei Jiang, Wei Wu, Xuefei Fang, Muyong Cao

The Kalman filter has been adopted in acoustic echo cancellation due to its robustness to double-talk, fast convergence, and good steady-state performance.

Acoustic echo cancellation

HQANN: Efficient and Robust Similarity Search for Hybrid Queries with Structured and Unstructured Constraints

no code implementations16 Jul 2022 Wei Wu, Junlin He, Yu Qiao, Guoheng Fu, Li Liu, Jin Yu

The in-memory approximate nearest neighbor search (ANNS) algorithms have achieved great success for fast high-recall query processing, but are extremely inefficient when handling hybrid queries with unstructured (i. e., feature vectors) and structured (i. e., related attributes) constraints.

Perceptual Quality Assessment for Fine-Grained Compressed Images

no code implementations8 Jun 2022 ZiCheng Zhang, Wei Sun, Wei Wu, Ying Chen, Xiongkuo Min, Guangtao Zhai

Nowadays, the mainstream full-reference (FR) metrics are effective to predict the quality of compressed images at coarse-grained levels (the bit rates differences of compressed images are obvious), however, they may perform poorly for fine-grained compressed images whose bit rates differences are quite subtle.

Image Compression Image Quality Assessment

MiniDisc: Minimal Distillation Schedule for Language Model Compression

no code implementations29 May 2022 Chen Zhang, Yang Yang, Qifan Wang, Jiahao Liu, Jingang Wang, Yunsen Xian, Wei Wu, Dawei Song

In particular, motivated by the finding that the performance of the student is positively correlated to the scale-performance tradeoff of the teacher assistant, MiniDisc is designed with a $\lambda$-tradeoff to measure the optimality of the teacher assistant without trial distillation to the student.

Knowledge Distillation Language Modelling +2

Ensemble Multi-Relational Graph Neural Networks

no code implementations24 May 2022 Yuling Wang, Hao Xu, Yanhua Yu, Mengdi Zhang, Zhenhao Li, Yuji Yang, Wei Wu

This EMR optimization objective is able to derive an iterative updating rule, which can be formalized as an ensemble message passing (EnMP) layer with multi-relations.

Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification

no code implementations18 May 2022 Kai Zhang, Qi Liu, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen

Existing studies in this task attach more attention to the sequence modeling of sentences while largely ignoring the rich domain-invariant semantics embedded in graph structures (i. e., the part-of-speech tags and dependency relations).

Classification Graph Attention +4

Making Pretrained Language Models Good Long-tailed Learners

1 code implementation11 May 2022 Chen Zhang, Lei Ren, Jingang Wang, Wei Wu, Dawei Song

Prompt-tuning has shown appealing performance in few-shot classification by virtue of its capability in effectively exploiting pre-trained knowledge.


Cross Domain Object Detection by Target-Perceived Dual Branch Distillation

1 code implementation CVPR 2022 Mengzhe He, Yali Wang, Jiaxi Wu, Yiru Wang, Hanqing Li, Bo Li, Weihao Gan, Wei Wu, Yu Qiao

It can adaptively enhance source detector to perceive objects in a target image, by leveraging target proposal contexts from iterative cross-attention.

object-detection Object Detection

Locality Sensitive Hashing for Structured Data: A Survey

no code implementations24 Apr 2022 Wei Wu, Bin Li

Data similarity (or distance) computation is a fundamental research topic which fosters a variety of similarity-based machine learning and data mining applications.

GNN-encoder: Learning a Dual-encoder Architecture via Graph Neural Networks for Dense Passage Retrieval

no code implementations18 Apr 2022 Jiduan Liu, Jiahao Liu, Yang Yang, Jingang Wang, Wei Wu, Dongyan Zhao, Rui Yan

To enhance the performance of dense retrieval models without loss of efficiency, we propose a GNN-encoder model in which query (passage) information is fused into passage (query) representations via graph neural networks that are constructed by queries and their top retrieved passages.

Natural Questions Passage Retrieval +2

Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection

no code implementations CVPR 2022 Jiaxi Wu, Jiaxin Chen, Mengzhe He, Yiru Wang, Bo Li, Bingqi Ma, Weihao Gan, Wei Wu, Yali Wang, Di Huang

Specifically, TRKP adopts the teacher-student framework, where the multi-head teacher network is built to extract knowledge from labeled source domains and guide the student network to learn detectors in unlabeled target domain.

Disentanglement Domain Adaptation +2

Learning to Express in Knowledge-Grounded Conversation

no code implementations NAACL 2022 Xueliang Zhao, Tingchen Fu, Chongyang Tao, Wei Wu, Dongyan Zhao, Rui Yan

Grounding dialogue generation by extra knowledge has shown great potentials towards building a system capable of replying with knowledgeable and engaging responses.

Dialogue Generation

Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization

1 code implementation NAACL 2022 Lulu Zhao, Fujia Zheng, Weihao Zeng, Keqing He, Weiran Xu, Huixing Jiang, Wei Wu, Yanan Wu

The most advanced abstractive dialogue summarizers lack generalization ability on new domains and the existing researches for domain adaptation in summarization generally rely on large-scale pre-trainings.

Domain Adaptation

TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization

no code implementations Findings (NAACL) 2022 Ze Yang, Liran Wang, Zhoujin Tian, Wei Wu, Zhoujun Li

Another is that applying the existing pre-trained models to this task is tricky because of the structural dependence within the conversation and its informal expression, etc.

Unsupervised Learning of Accurate Siamese Tracking

1 code implementation CVPR 2022 Qiuhong Shen, Lei Qiao, Jinyang Guo, Peixia Li, Xin Li, Bo Li, Weitao Feng, Weihao Gan, Wei Wu, Wanli Ouyang

As unlimited self-supervision signals can be obtained by tracking a video along a cycle in time, we investigate evolving a Siamese tracker by tracking videos forward-backward.

Visual Object Tracking

Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision

1 code implementation28 Mar 2022 Sijie Cheng, Zhouhong Gu, Bang Liu, Rui Xie, Wei Wu, Yanghua Xiao

Specifically, i) to fully exploit user behavioral information, we extract candidate hyponymy relations that match user interests from query-click concepts; ii) to enhance the semantic information of new concepts and better detect hyponymy relations, we model concepts and relations through both user-generated content and structural information in existing taxonomies and user click logs, by leveraging Pre-trained Language Models and Graph Neural Network combined with Contrastive Learning; iii) to reduce the cost of dataset construction and overcome data skews, we construct a high-quality and balanced training dataset from existing taxonomy with no supervision.

Contrastive Learning Taxonomy Expansion

Data-Driven, Soft Alignment of Functional Data Using Shapes and Landmarks

1 code implementation22 Mar 2022 Xiaoyang Guo, Wei Wu, Anuj Srivastava

Alignment or registration of functions is a fundamental problem in statistical analysis of functions and shapes.

ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generation

no code implementations ICCV 2023 Liang Xu, Ziyang Song, Dongliang Wang, Jing Su, Zhicheng Fang, Chenjing Ding, Weihao Gan, Yichao Yan, Xin Jin, Xiaokang Yang, Wenjun Zeng, Wei Wu

We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions.

Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking

1 code implementation10 Mar 2022 BoYu Chen, Peixia Li, Lei Bai, Lei Qiao, Qiuhong Shen, Bo Li, Weihao Gan, Wei Wu, Wanli Ouyang

Exploiting a general-purpose neural architecture to replace hand-wired designs or inductive biases has recently drawn extensive interest.

Visual Object Tracking

InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NER

1 code implementation8 Mar 2022 LiWen Wang, Rumei Li, Yang Yan, Yuanmeng Yan, Sirui Wang, Wei Wu, Weiran Xu

Recently, prompt-based methods have achieved significant performance in few-shot learning scenarios by bridging the gap between language model pre-training and fine-tuning for downstream tasks.

Entity Typing Few-Shot Learning +4

Graph Neural Network-Based Scheduling for Multi-UAV-Enabled Communications in D2D Networks

no code implementations15 Feb 2022 Pei Li, Lingyi Wang, Wei Wu, Fuhui Zhou, Baoyun Wang, Qihui Wu

In this paper, we propose a novel graph neural networks (GNN) based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.


Learning Video Representations of Human Motion From Synthetic Data

no code implementations CVPR 2022 Xi Guo, Wei Wu, Dongliang Wang, Jing Su, Haisheng Su, Weihao Gan, Jian Huang, Qin Yang

In this paper, we take an early step towards video representation learning of human actions with the help of largescale synthetic videos, particularly for human motion representation enhancement.

Action Recognition Contrastive Learning +2

Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQL

1 code implementation16 Dec 2021 Yuntao Li, Hanchu Zhang, Yutian Li, Sirui Wang, Wei Wu, Yan Zhang

Conversational text-to-SQL aims at converting multi-turn natural language queries into their corresponding SQL (Structured Query Language) representations.

Natural Language Queries Semantic Parsing +1

VIRT: Improving Representation-based Models for Text Matching through Virtual Interaction

no code implementations8 Dec 2021 Dan Li, Yang Yang, Hongyin Tang, Jingang Wang, Tong Xu, Wei Wu, Enhong Chen

With the booming of pre-trained transformers, representation-based models based on Siamese transformer encoders have become mainstream techniques for efficient text matching.

Text Matching

Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection

1 code implementation7 Dec 2021 Shoubin Yu, Zhongyin Zhao, Haoshu Fang, Andong Deng, Haisheng Su, Dongliang Wang, Weihao Gan, Cewu Lu, Wei Wu

Different from pixel-based anomaly detection methods, pose-based methods utilize highly-structured skeleton data, which decreases the computational burden and also avoids the negative impact of background noise.

Anomaly Detection In Surveillance Videos Optical Flow Estimation +1

Calibrated Feature Decomposition for Generalizable Person Re-Identification

1 code implementation27 Nov 2021 Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha

The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.

Domain Generalization Generalizable Person Re-identification

TODSum: Task-Oriented Dialogue Summarization with State Tracking

no code implementations25 Oct 2021 Lulu Zhao, Fujia Zheng, Keqing He, Weihao Zeng, Yuejie Lei, Huixing Jiang, Wei Wu, Weiran Xu, Jun Guo, Fanyu Meng

Previous dialogue summarization datasets mainly focus on open-domain chitchat dialogues, while summarization datasets for the broadly used task-oriented dialogue haven't been explored yet.

Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation

no code implementations16 Sep 2021 Zihao Zhao, Jiawei Chen, Sheng Zhou, Xiangnan He, Xuezhi Cao, Fuzheng Zhang, Wei Wu

To sufficiently exploit such important information for recommendation, it is essential to disentangle the benign popularity bias caused by item quality from the harmful popularity bias caused by conformity.

Recommendation Systems

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

2 code implementations22 Aug 2021 Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks.

Disentanglement Graph Attention +1

Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based Dialogues

1 code implementation ACM Transactions on Information Systems 2021 Ruijian Xu, Chongyang Tao, Jiazhan Feng, Wei Wu, Rui Yan, Dongyan Zhao

To tackle these challenges, we propose a representation[K]-interaction[L]-matching framework that explores multiple types of deep interactive representations to build context-response matching models for response selection.

Conversational Response Selection Retrieval

The impact of model risk on dynamic portfolio selection under multi-period mean-standard-deviation criterion

no code implementations5 Aug 2021 Spiridon Penev, Pavel V. Shevchenko, Wei Wu

In the worst case scenario, the optimal robust strategy can be obtained in a semi-analytical form as a solution of a system of nonlinear equations.

Transferable Knowledge-Based Multi-Granularity Aggregation Network for Temporal Action Localization: Submission to ActivityNet Challenge 2021

no code implementations27 Jul 2021 Haisheng Su, Peiqin Zhuang, Yukun Li, Dongliang Wang, Weihao Gan, Wei Wu, Yu Qiao

This technical report presents an overview of our solution used in the submission to 2021 HACS Temporal Action Localization Challenge on both Supervised Learning Track and Weakly-Supervised Learning Track.

Transfer Learning Weakly-supervised Learning +2

TSI: Temporal Saliency Integration for Video Action Recognition

no code implementations2 Jun 2021 Haisheng Su, Jinyuan Feng, Dongliang Wang, Weihao Gan, Wei Wu, Yu Qiao

Specifically, SME aims to highlight the motion-sensitive area through local-global motion modeling, where the saliency alignment and pyramidal feature difference are conducted successively between neighboring frames to capture motion dynamics with less noises caused by misaligned background.

Action Recognition Temporal Action Localization

A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks

no code implementations31 May 2021 Hao Zhang, Fuhui Zhou, Qihui Wu, Wei Wu, Rose Qingyang Hu

Moreover, a novel loss function that combines the center loss and the cross entropy loss is exploited to learn both discriminative and separable features in order to further improve the classification performance.

Classification Face Recognition

Improving Document Representations by Generating Pseudo Query Embeddings for Dense Retrieval

no code implementations ACL 2021 Hongyin Tang, Xingwu Sun, Beihong Jin, Jingang Wang, Fuzheng Zhang, Wei Wu

Recently, the retrieval models based on dense representations have been gradually applied in the first stage of the document retrieval tasks, showing better performance than traditional sparse vector space models.

Clustering Retrieval

Temporal Context Aggregation Network for Temporal Action Proposal Refinement

1 code implementation CVPR 2021 Zhiwu Qing, Haisheng Su, Weihao Gan, Dongliang Wang, Wei Wu, Xiang Wang, Yu Qiao, Junjie Yan, Changxin Gao, Nong Sang

In this paper, we propose Temporal Context Aggregation Network (TCANet) to generate high-quality action proposals through "local and global" temporal context aggregation and complementary as well as progressive boundary refinement.

Action Detection Retrieval +2

Incorporating Convolution Designs into Visual Transformers

3 code implementations ICCV 2021 Kun Yuan, Shaopeng Guo, Ziwei Liu, Aojun Zhou, Fengwei Yu, Wei Wu

Motivated by the success of Transformers in natural language processing (NLP) tasks, there emerge some attempts (e. g., ViT and DeiT) to apply Transformers to the vision domain.

Image Classification

ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction

1 code implementation NAACL 2021 Jiahao Bu, Lei Ren, Shuang Zheng, Yang Yang, Jingang Wang, Fuzheng Zhang, Wei Wu

Aspect category sentiment analysis (ACSA) and review rating prediction (RP) are two essential tasks to detect the fine-to-coarse sentiment polarities.

Sentiment Analysis

Learning Statistical Texture for Semantic Segmentation

1 code implementation CVPR 2021 Lanyun Zhu, Deyi Ji, Shiping Zhu, Weihao Gan, Wei Wu, Junjie Yan

In this paper, we fully take advantages of the low-level texture features and propose a novel Statistical Texture Learning Network (STLNet) for semantic segmentation.

Quantization Segmentation +1

BaPipe: Exploration of Balanced Pipeline Parallelism for DNN Training

no code implementations23 Dec 2020 Letian Zhao, Rui Xu, Tianqi Wang, Teng Tian, Xiaotian Wang, Wei Wu, Chio-in Ieong, Xi Jin

The size of deep neural networks (DNNs) grows rapidly as the complexity of the machine learning algorithm increases.

Improving EEG Decoding via Clustering-based Multi-task Feature Learning

no code implementations12 Dec 2020 Yu Zhang, Tao Zhou, Wei Wu, Hua Xie, Hongru Zhu, Guoxu Zhou, Andrzej Cichocki

With the encoded label matrix, we devise a novel multi-task learning algorithm by exploiting the subclass relationship to jointly optimize the EEG pattern features from the uncovered subclasses.

Clustering EEG +2

Context-Aware Graph Convolution Network for Target Re-identification

no code implementations8 Dec 2020 Deyi Ji, Haoran Wang, Hanzhe Hu, Weihao Gan, Wei Wu, Junjie Yan

Most existing re-identification methods focus on learning robust and discriminative features with deep convolution networks.

Vehicle Re-Identification

Social Media Study of Public Opinions on Potential COVID-19 Vaccines: Informing Dissent, Disparities, and Dissemination

no code implementations3 Dec 2020 Hanjia Lyu, Wei Wu, Junda Wang, Viet Duong, Xiyang Zhang, Jiebo Luo

People who have the worst personal pandemic experience are more likely to hold the anti-vaccine opinion.

Social and Information Networks

Are Pre-trained Language Models Knowledgeable to Ground Open Domain Dialogues?

no code implementations19 Nov 2020 Yufan Zhao, Wei Wu, Can Xu

We study knowledge-grounded dialogue generation with pre-trained language models.

Dialogue Generation

Less is More: Data-Efficient Complex Question Answering over Knowledge Bases

1 code implementation29 Oct 2020 Yuncheng Hua, Yuan-Fang Li, Guilin Qi, Wei Wu, Jingyao Zhang, Daiqing Qi

Our framework consists of a neural generator and a symbolic executor that, respectively, transforms a natural-language question into a sequence of primitive actions, and executes them over the knowledge base to compute the answer.

Multi-hop Question Answering Question Answering

StyleDGPT: Stylized Response Generation with Pre-trained Language Models

1 code implementation Findings of the Association for Computational Linguistics 2020 Ze Yang, Wei Wu, Can Xu, Xinnian Liang, Jiaqi Bai, Liran Wang, Wei Wang, Zhoujun Li

Generating responses following a desired style has great potentials to extend applications of open-domain dialogue systems, yet is refrained by lacking of parallel data for training.

Response Generation

SAMOT: Switcher-Aware Multi-Object Tracking and Still Another MOT Measure

no code implementations22 Sep 2020 Weitao Feng, Zhihao Hu, Baopu Li, Weihao Gan, Wei Wu, Wanli Ouyang

Besides, we propose a new MOT evaluation measure, Still Another IDF score (SAIDF), aiming to focus more on identity issues. This new measure may overcome some problems of the previous measures and provide a better insight for identity issues in MOT.

Multi-Object Tracking

Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition

no code implementations15 Sep 2020 Haisheng Su, Jing Su, Dongliang Wang, Weihao Gan, Wei Wu, Mengmeng Wang, Junjie Yan, Yu Qiao

Second, the parameter frequency distribution is further adopted to guide the student network to learn the appearance modeling process from the teacher.

Action Recognition Knowledge Distillation +1

BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation

1 code implementation15 Sep 2020 Haisheng Su, Weihao Gan, Wei Wu, Yu Qiao, Junjie Yan

In this paper, we present BSN++, a new framework which exploits complementary boundary regressor and relation modeling for temporal proposal generation.

Temporal Action Proposal Generation

Zero-Resource Knowledge-Grounded Dialogue Generation

1 code implementation NeurIPS 2020 Linxiao Li, Can Xu, Wei Wu, Yufan Zhao, Xueliang Zhao, Chongyang Tao

While neural conversation models have shown great potentials towards generating informative and engaging responses via introducing external knowledge, learning such a model often requires knowledge-grounded dialogues that are difficult to obtain.

Dialogue Generation

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

no code implementations20 Jul 2020 Haisheng Su, Jinyuan Feng, Hao Shao, Zhenyu Jiang, Manyuan Zhang, Wei Wu, Yu Liu, Hongsheng Li, Junjie Yan

Specifically, in order to generate high-quality proposals, we consider several factors including the video feature encoder, the proposal generator, the proposal-proposal relations, the scale imbalance, and ensemble strategy.

Temporal Action Localization

Class-wise Dynamic Graph Convolution for Semantic Segmentation

no code implementations ECCV 2020 Hanzhe Hu, Deyi Ji, Weihao Gan, Shuai Bai, Wei Wu, Junjie Yan

Specifically, the CDGC module takes the coarse segmentation result as class mask to extract node features for graph construction and performs dynamic graph convolutions on the constructed graph to learn the feature aggregation and weight allocation.

graph construction Segmentation +1

CorefQA: Coreference Resolution as Query-based Span Prediction

1 code implementation ACL 2020 Wei Wu, Fei Wang, Arianna Yuan, Fei Wu, Jiwei Li

In this paper, we present CorefQA, an accurate and extensible approach for the coreference resolution task.

Ranked #2 on Coreference Resolution on CoNLL 2012 (using extra training data)

coreference-resolution Data Augmentation +1

Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning

no code implementations ICLR 2021 Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang, Daxin Jiang

In this paper, we formalize the music-conditioned dance generation as a sequence-to-sequence learning problem and devise a novel seq2seq architecture to efficiently process long sequences of music features and capture the fine-grained correspondence between music and dance.

Motion Synthesis Pose Estimation

Deep learning to estimate the physical proportion of infected region of lung for COVID-19 pneumonia with CT image set

no code implementations9 Jun 2020 Wei Wu, Yu Shi, Xukun Li, Yukun Zhou, Peng Du, Shuangzhi Lv, Tingbo Liang, Jifang Sheng

For the segmented masks of intact lung and infected regions, the best method could achieve 0. 972 and 0. 757 measure in mean Dice similarity coefficient on our test benchmark.

Computed Tomography (CT)

Hierarchical Feature Embedding for Attribute Recognition

no code implementations CVPR 2020 Jie Yang, Jiarou Fan, Yiru Wang, Yige Wang, Weihao Gan, Lin Liu, Wei Wu

Attribute recognition is a crucial but challenging task due to viewpoint changes, illumination variations and appearance diversities, etc.

Scope Head for Accurate Localization in Object Detection

no code implementations11 May 2020 Geng Zhan, Dan Xu, Guo Lu, Wei Wu, Chunhua Shen, Wanli Ouyang

Existing anchor-based and anchor-free object detectors in multi-stage or one-stage pipelines have achieved very promising detection performance.

object-detection Object Detection +1

Estimation of the Laser Frequency Nosie Spectrum by Continuous Dynamical Decoupling

no code implementations8 May 2020 Manchao Zhang, Yi Xie, Jie Zhang, Weichen Wang, Chunwang Wu, Ting Chen, Wei Wu, Pingxing Chen

Decoherence induced by the laser frequency noise is one of the most important obstacles in the quantum information processing.

Quantum Physics

Open Domain Dialogue Generation with Latent Images

no code implementations4 Apr 2020 Ze Yang, Wei Wu, Huang Hu, Can Xu, Wei Wang, Zhoujun Li

Thus, we propose learning a response generation model with both image-grounded dialogues and textual dialogues by assuming that the visual scene information at the time of a conversation can be represented by an image, and trying to recover the latent images of the textual dialogues through text-to-image generation techniques.

Dialogue Generation Response Generation

Towards information-rich, logical text generation with knowledge-enhanced neural models

no code implementations2 Mar 2020 Hao Wang, Bin Guo, Wei Wu, Zhiwen Yu

Text generation system has made massive promising progress contributed by deep learning techniques and has been widely applied in our life.

Text Generation

Low-Resource Knowledge-Grounded Dialogue Generation

no code implementations ICLR 2020 Xueliang Zhao, Wei Wu, Chongyang Tao, Can Xu, Dongyan Zhao, Rui Yan

In such a low-resource setting, we devise a disentangled response decoder in order to isolate parameters that depend on knowledge-grounded dialogues from the entire generation model.

Dialogue Generation Response Generation

Deep Learning System to Screen Coronavirus Disease 2019 Pneumonia

no code implementations21 Feb 2020 Xiaowei Xu, Xiangao Jiang, Chunlian Ma, Peng Du, Xukun Li, Shuangzhi Lv, Liang Yu, Yanfei Chen, Junwei Su, Guanjing Lang, Yongtao Li, Hong Zhao, Kaijin Xu, Lingxiang Ruan, Wei Wu

We found that the real time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab has a relatively low positive rate in the early stage to determine COVID-19 (named by the World Health Organization).

Computed Tomography (CT) COVID-19 Diagnosis

Description Based Text Classification with Reinforcement Learning

no code implementations ICML 2020 Duo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li

We observe significant performance boosts over strong baselines on a wide range of text classification tasks including single-label classification, multi-label classification and multi-aspect sentiment analysis.

General Classification Multi-Label Classification +6

Computation Reallocation for Object Detection

no code implementations ICLR 2020 Feng Liang, Chen Lin, Ronghao Guo, Ming Sun, Wei Wu, Junjie Yan, Wanli Ouyang

However, classification allocation pattern is usually adopted directly to object detector, which is proved to be sub-optimal.

Instance Segmentation Neural Architecture Search +3

Coreference Resolution as Query-based Span Prediction

1 code implementation5 Nov 2019 Wei Wu, Fei Wang, Arianna Yuan, Fei Wu, Jiwei Li

In this paper, we present an accurate and extensible approach for the coreference resolution task.

coreference-resolution Data Augmentation +1

Improving One-shot NAS by Suppressing the Posterior Fading

no code implementations CVPR 2020 Xiang Li, Chen Lin, Chuming Li, Ming Sun, Wei Wu, Junjie Yan, Wanli Ouyang

In this paper, we analyse existing weight sharing one-shot NAS approaches from a Bayesian point of view and identify the posterior fading problem, which compromises the effectiveness of shared weights.

Neural Architecture Search object-detection +2

A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis

no code implementations5 Oct 2019 Wei Wu, Xukun Li, Peng Du, Guanjing Lang, Min Xu, Kaijin Xu, Lanjuan Li

The best model was selected to annotate the spatial location of lesions and classify them into miliary, infiltrative, caseous, tuberculoma and cavitary types simultaneously. Then the Noisy-Or Bayesian function was used to generate an overall infection probability. Finally, a quantitative diagnostic report was exported. The results showed that the recall and precision rates, from the perspective of a single lesion region of PTB, were 85. 9% and 89. 2% respectively.

Computed Tomography (CT) Decision Making +1

Low-Resource Response Generation with Template Prior

1 code implementation IJCNLP 2019 Ze Yang, Wei Wu, Jian Yang, Can Xu, Zhoujun Li

Since the paired data now is no longer enough to train a neural generation model, we consider leveraging the large scale of unpaired data that are much easier to obtain, and propose response generation with both paired and unpaired data.

Response Generation

Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach

no code implementations25 Sep 2019 Seojin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric Xing

Briefness and comprehensiveness are necessary in order to provide a large amount of information concisely when explaining a black-box decision system.

BIG-bench Machine Learning Interpretable Machine Learning

Conditional Text Generation for Harmonious Human-Machine Interaction

no code implementations8 Sep 2019 Bin Guo, Hao Wang, Yasan Ding, Wei Wu, Shaoyang Hao, Yueqi Sun, Zhiwen Yu

In recent years, with the development of deep learning, text generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily communication.

Conditional Text Generation

Myopic robust index tracking with Bregman divergence

no code implementations21 Aug 2019 Spiridon Penev, Pavel Shevchenko, Wei Wu

Typically, a quadratic function is used to define the tracking error of a portfolio and the look back approach is applied to solve the index tracking problem.


Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance

no code implementations15 Aug 2019 Elliott Slaughter, Wei Wu, Yuankun Fu, Legend Brandenburg, Nicolai Garcia, Wilhem Kautz, Emily Marx, Kaleb S. Morris, Wonchan Lee, Qinglei Cao, George Bosilca, Seema Mirchandaney, Sean Treichler, Patrick McCormick, Alex Aiken

We present Task Bench, a parameterized benchmark designed to explore the performance of parallel and distributed programming systems under a variety of application scenarios.

Distributed, Parallel, and Cluster Computing

Towards Comprehensive Description Generation from Factual Attribute-value Tables

no code implementations ACL 2019 Tianyu Liu, Fuli Luo, Pengcheng Yang, Wei Wu, Baobao Chang, Zhifang Sui

To relieve these problems, we first propose force attention (FA) method to encourage the generator to pay more attention to the uncovered attributes to avoid potential key attributes missing.


A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots

no code implementations11 Jun 2019 Xueliang Zhao, Chongyang Tao, Wei Wu, Can Xu, Dongyan Zhao, Rui Yan

We present a document-grounded matching network (DGMN) for response selection that can power a knowledge-aware retrieval-based chatbot system.

Chatbot Retrieval

DSReg: Using Distant Supervision as a Regularizer

no code implementations ICLR 2020 Yuxian Meng, Muyu Li, Xiaoya Li, Wei Wu, Jiwei Li

In this paper, we aim at tackling a general issue in NLP tasks where some of the negative examples are highly similar to the positive examples, i. e., hard-negative examples.

Multi-Task Learning Reading Comprehension +2

AM-LFS: AutoML for Loss Function Search

1 code implementation ICCV 2019 Chuming Li, Yuan Xin, Chen Lin, Minghao Guo, Wei Wu, Wanli Ouyang, Junjie Yan

The key contribution of this work is the design of search space which can guarantee the generalization and transferability on different vision tasks by including a bunch of existing prevailing loss functions in a unified formulation.