b'Guoyin Wang'

research

∙ 08/21/2023

Instruction Tuning for Large Language Models: A Survey

This paper surveys research works in the quickly advancing field of inst...

0 Shengyu Zhang, et al. ∙

research

∙ 06/16/2023

Pushing the Limits of ChatGPT on NLP Tasks

Despite the success of ChatGPT, its performances on most NLP tasks are s...

0 Xiaofei Sun, et al. ∙

research

∙ 05/23/2023

TaDSE: Template-aware Dialogue Sentence Embeddings

Learning high quality sentence embeddings from dialogues has drawn incre...

0 Minsik Oh, et al. ∙

research

∙ 05/15/2023

Text Classification via Large Language Models

Despite the remarkable success of large-scale Language Models (LLMs) suc...

0 Xiaofei Sun, et al. ∙

research

∙ 05/09/2023

Towards Building the Federated GPT: Federated Instruction Tuning

While “instruction-tuned" generative large language models (LLMs) have d...

0 Jianyi Zhang, et al. ∙

research

∙ 04/21/2023

Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method

Human cognition has a “large-scale first” cognitive mechanism, therefore...

0 Shuyin Xia, et al. ∙

research

∙ 04/20/2023

GPT-NER: Named Entity Recognition via Large Language Models

Despite the fact that large-scale Language Models (LLM) have achieved SO...

0 Shuhe Wang, et al. ∙

research

∙ 03/18/2023

Granular-ball Optimization Algorithm

The existing intelligent optimization algorithms are designed based on t...

0 Shuyin Xia, et al. ∙

research

∙ 03/09/2023

Open World Classification with Adaptive Negative Samples

Open world classification is a task in natural language processing with ...

0 Ke Bai, et al. ∙

research

∙ 03/07/2023

Research on Efficient Fuzzy Clustering Method Based on Local Fuzzy Granular balls

In recent years, the problem of fuzzy clustering has been widely concern...

0 Jiang Xie, et al. ∙

research

∙ 03/02/2023

GBMST: An Efficient Minimum Spanning Tree Clustering Based on Granular-Ball Computing

Most of the existing clustering methods are based on a single granularit...

0 Jiang Xie, et al. ∙

research

∙ 02/13/2023

PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialogue

Identifying relevant Persona or Knowledge for conversational systems is ...

0 Minsik Oh, et al. ∙

research

∙ 12/30/2022

A novel cluster internal evaluation index based on hyper-balls

It is crucial to evaluate the quality and determine the optimal number o...

0 Jiang Xie, et al. ∙

research

∙ 12/05/2022

GNN-SL: Sequence Labeling Based on Nearest Examples via GNN

To better handle long-tail cases in the sequence labeling (SL) task, in ...

0 Shuhe Wang, et al. ∙

research

∙ 10/06/2022

GBSVM: Granular-ball Support Vector Machine

GBSVM (Granular-ball Support Vector Machine) is an important attempt to ...

0 Shuyin Xia, et al. ∙

research

∙ 08/17/2022

Semi-supervised Learning with Deterministic Labeling and Large Margin Projection

The centrality and diversity of the labeled data are very influential to...

0 Ji Xu, et al. ∙

research

∙ 07/28/2022

Learning Personalized Representations using Graph Convolutional Network

Generating representations that precisely reflect customers' behavior is...

15 Hongyu Shen, et al. ∙

research

∙ 07/26/2022

Advanced Conditional Variational Autoencoders (A-CVAE): Towards interpreting open-domain conversation generation via disentangling latent feature representation

Currently end-to-end deep learning based open-domain dialogue systems re...

0 Ye Wang, et al. ∙

research

∙ 05/07/2022

Number Entity Recognition

Numbers are essential components of text, like any other word tokens, fr...

0 Dhanasekar Sundararaman, et al. ∙

research

∙ 03/31/2022

kNN-NER: Named Entity Recognition with Nearest Neighbor Search

Inspired by recent advances in retrieval augmented methods in NLP <cit.>...

0 Shuhe Wang, et al. ∙

research

∙ 03/17/2022

One-Stage Deep Edge Detection Based on Dense-Scale Feature Fusion and Pixel-Level Imbalance Learning

Edge detection, a basic task in the field of computer vision, is an impo...

0 Dawei Dai, et al. ∙

research

∙ 01/13/2022

Multi-granularity Association Learning Framework for on-the-fly Fine-Grained Sketch-based Image Retrieval

Fine-grained sketch-based image retrieval (FG-SBIR) addresses the proble...

0 Dawei Dai, et al. ∙

research

∙ 01/12/2022

An Efficient and Adaptive Granular-ball Generation Method in Classification Problem

Granular-ball computing is an efficient, robust, and scalable learning m...

0 Shuyin Xia, et al. ∙

research

∙ 12/29/2021

An Efficient and Accurate Rough Set for Feature Selection, Classification and Knowledge Representation

This paper present a strong data mining method based on rough set, which...

0 Shuyin Xia, et al. ∙

research

∙ 12/15/2021

Faster Nearest Neighbor Machine Translation

kNN based neural machine translation (kNN-MT) has achieved state-of-the-...

0 Shuhe Wang, et al. ∙

research

∙ 11/03/2021

Rethinking the Image Feature Biases Exhibited by Deep CNN Models

In recent years, convolutional neural networks (CNNs) have been applied ...

4 Dawei Dai, et al. ∙

research

∙ 09/25/2021

Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding

A large-scale conversational agent can suffer from understanding user ut...

0 Joo-Kyung Kim, et al. ∙

research

∙ 06/10/2021

AUGNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation

Natural Language Generation (NLG) is a key component in a task-oriented ...

0 Xinnuo Xu, et al. ∙

research

∙ 12/03/2020

D-Unet: A Dual-encoder U-Net for Image Splicing Forgery Detection and Localization

Recently, many detection methods based on convolutional neural networks ...

11 Xiuli Bi, et al. ∙

research

∙ 10/31/2020

LRA: an accelerated rough set framework based on local redundancy of attribute for feature selection

In this paper, we propose and prove the theorem regarding the stability ...

0 Shuyin Xia, et al. ∙

research

∙ 10/12/2020

Improving Text Generation with Student-Forcing Optimal Transport

Neural language models are often trained with maximum likelihood estimat...

2 Guoyin Wang, et al. ∙

research

∙ 08/14/2020

Weakly supervised cross-domain alignment with optimal transport

Cross-domain alignment between image objects and text sequences is key t...

9 Siyang Yuan, et al. ∙

research

∙ 05/04/2020

Improving Adversarial Text Generation by Modeling the Distant Future

Auto-regressive text generation models usually focus on local fluency, a...

0 Ruiyi Zhang, et al. ∙

research

∙ 05/02/2020

Ball k-means

This paper presents a novel accelerated exact k-means algorithm called t...

0 Shuyin Xia, et al. ∙

research

∙ 05/01/2020

POINTER: Constrained Text Generation via Insertion-based Generative Pre-training

Large-scale pre-trained language models, such as BERT and GPT-2, have ac...

5 Yizhe Zhang, et al. ∙

research

∙ 11/20/2019

Graph-Driven Generative Models for Heterogeneous Multi-Task Learning

We propose a novel graph-driven generative model, that unifies multiple ...

0 Wenlin Wang, et al. ∙

research

∙ 11/10/2019

Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding

Attention-based models have shown significant improvement over tradition...

0 Dhanasekar Sundararaman, et al. ∙

research

∙ 10/20/2019

An Optimal Transport Framework for Zero-Shot Learning

We present an optimal transport (OT) framework for generalized zero-shot...

0 Wenlin Wang, et al. ∙

research

∙ 10/09/2019

Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods

We investigate time-dependent data analysis from the perspective of recu...

0 Kevin J Liang, et al. ∙

research

∙ 09/30/2019

Improving Textual Network Learning with Variational Homophilic Embeddings

The performance of many network learning applications crucially hinges o...

0 Wenlin Wang, et al. ∙

research

∙ 06/07/2019

Learning Word Embeddings with Domain Awareness

Word embeddings are traditionally trained on a large corpus in an unsupe...

0 Guoyin Wang, et al. ∙

research

∙ 06/05/2019

Improving Textual Network Embedding with Global Attention via Optimal Transport

Constituting highly informative network embeddings is an important tool ...

0 Liqun Chen, et al. ∙

research

∙ 05/30/2019

Discriminative Clustering for Robust Unsupervised Domain Adaptation

Unsupervised domain adaptation seeks to learn an invariant and discrimin...

0 Rui Wang, et al. ∙

research

∙ 03/17/2019

Topic-Guided Variational Autoencoders for Text Generation

We propose a topic-guided variational autoencoder (TGVAE) model for text...

0 Wenlin Wang, et al. ∙

research

∙ 01/03/2019

Adversarial Learning of a Sampler Based on an Unnormalized Distribution

We investigate adversarial learning in the case when only an unnormalize...

14 Chunyuan Li, et al. ∙

research

∙ 12/30/2018

Mining Maximal Dynamic Spatial Co-Location Patterns

A spatial co-location pattern represents a subset of spatial features wh...

0 Jiangli Duan, et al. ∙

research

∙ 11/27/2018

Generative Adversarial Network Training is a Continual Learning Problem

Generative Adversarial Networks (GANs) have proven to be a powerful fram...

22 Kevin J Liang, et al. ∙

research

∙ 11/02/2018

Sequence Generation with Guider Network

Sequence generation with reinforcement learning (RL) has received signif...

0 Ruiyi Zhang, et al. ∙

research

∙ 06/08/2018

JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets

A new generative adversarial network is developed for joint distribution...

0 Yunchen Pu, et al. ∙

research

∙ 05/24/2018

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

Many deep learning architectures have been proposed to model the composi...

0 Dinghan Shen, et al. ∙

Guoyin Wang

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