b'Jindong Wang'

research

∙ 08/23/2023

From Instructions to Intrinsic Human Values – A Survey of Alignment Goals for Big Models

Big models, exemplified by Large Language Models (LLMs), are models typi...

0 Jing Yao, et al. ∙

research

∙ 08/15/2023

Exponentially-fitted finite elements for H( curl) and H( div) convection-diffusion problems

This paper presents a novel approach to the construction of the lowest o...

0 Jindong Wang, et al. ∙

research

∙ 08/04/2023

Frustratingly Easy Model Generalization by Dummy Risk Minimization

Empirical risk minimization (ERM) is a fundamental machine learning para...

0 Juncheng Wang, et al. ∙

research

∙ 08/04/2023

DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization

Time series remains one of the most challenging modalities in machine le...

0 Wang Lu, et al. ∙

research

∙ 07/14/2023

EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus

Large language models (LLMs) have achieved significant performance in ma...

0 Cheng Li, et al. ∙

research

∙ 07/06/2023

A Survey on Evaluation of Large Language Models

Large language models (LLMs) are gaining increasing popularity in both a...

0 Yupeng Chang, et al. ∙

research

∙ 06/08/2023

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Instruction tuning large language models (LLMs) remains a challenging ta...

0 Yidong Wang, et al. ∙

research

∙ 06/07/2023

PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

The increasing reliance on Large Language Models (LLMs) across academia ...

0 Kaijie Zhu, et al. ∙

research

∙ 05/31/2023

A hybridizable discontinuous Galerkin method for magnetic advection-diffusion problems

We propose and analyze a hybridizable discontinuous Galerkin (HDG) metho...

0 Jindong Wang, et al. ∙

research

∙ 05/23/2023

Out-of-Distribution Generalization in Text Classification: Past, Present, and Future

Machine learning (ML) systems in natural language processing (NLP) face ...

0 Linyi Yang, et al. ∙

research

∙ 04/04/2023

Exploring Vision-Language Models for Imbalanced Learning

Vision-Language models (VLMs) that use contrastive language-image pre-tr...

0 Yidong Wang, et al. ∙

research

∙ 02/27/2023

FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning

Federated learning (FL) has emerged as a new paradigm for privacy-preser...

0 Wang Lu, et al. ∙

research

∙ 02/22/2023

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

ChatGPT is a recent chatbot service released by OpenAI and is receiving ...

0 Jindong Wang, et al. ∙

research

∙ 01/26/2023

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

The critical challenge of Semi-Supervised Learning (SSL) is how to effec...

0 Hao Chen, et al. ∙

research

∙ 11/20/2022

An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning

Semi-supervised learning (SSL) has shown great promise in leveraging unl...

0 Hao Chen, et al. ∙

research

∙ 11/15/2022

GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective

Pre-trained language models (PLMs) are known to improve the generalizati...

0 Linyi Yang, et al. ∙

research

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

research

∙ 09/15/2022

Generalized Representations Learning for Time Series Classification

Time series classification is an important problem in real world. Due to...

0 Wang Lu, et al. ∙

research

∙ 09/01/2022

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

The distribution shifts between training and test data typically undermi...

0 Wang Lu, et al. ∙

research

∙ 08/17/2022

Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction

Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentim...

0 Yidong Wang, et al. ∙

research

∙ 08/15/2022

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets

While parameter efficient tuning (PET) methods have shown great potentia...

0 Hao Chen, et al. ∙

research

∙ 08/12/2022

USB: A Unified Semi-supervised Learning Benchmark

Semi-supervised learning (SSL) improves model generalization by leveragi...

0 Yidong Wang, et al. ∙

research

∙ 08/03/2022

Equivariant Disentangled Transformation for Domain Generalization under Combination Shift

Machine learning systems may encounter unexpected problems when the data...

0 Yivan Zhang, et al. ∙

research

∙ 08/02/2022

Discontinuous Galerkin methods for magnetic advection-diffusion problems

We devise and analyze a class of the primal discontinuous Galerkin metho...

0 Jindong Wang, et al. ∙

research

∙ 07/25/2022

Domain-invariant Feature Exploration for Domain Generalization

Deep learning has achieved great success in the past few years. However,...

0 Wang Lu, et al. ∙

research

∙ 07/21/2022

Domain Generalization for Activity Recognition via Adaptive Feature Fusion

Human activity recognition requires the efforts to build a generalizable...

0 Xin Qin, et al. ∙

research

∙ 06/26/2022

Memory-Guided Multi-View Multi-Domain Fake News Detection

The wide spread of fake news is increasingly threatening both individual...

0 Yongchun Zhu, et al. ∙

research

∙ 06/20/2022

Boosting Cross-Domain Speech Recognition with Self-Supervision

The cross-domain performance of automatic speech recognition (ASR) could...

0 Han Zhu, et al. ∙

research

∙ 06/18/2022

Decoupled Federated Learning for ASR with Non-IID Data

Automatic speech recognition (ASR) with federated learning (FL) makes it...

0 Han Zhu, et al. ∙

research

∙ 06/17/2022

MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare

Federated learning has attracted increasing attention to building models...

0 Yiqiang Chen, et al. ∙

research

∙ 06/14/2022

Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition

It is expensive and time-consuming to collect sufficient labeled data to...

0 Wang Lu, et al. ∙

research

∙ 05/15/2022

FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Pseudo labeling and consistency regularization approaches with confidenc...

0 Yidong Wang, et al. ∙

research

∙ 01/04/2022

Multi-Representation Adaptation Network for Cross-domain Image Classification

In image classification, it is often expensive and time-consuming to acq...

0 Yongchun Zhu, et al. ∙

research

∙ 01/03/2022

Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection

Unsupervised anomaly detection aims to build models to effectively detec...

0 Yuxin Zhang, et al. ∙

research

∙ 12/14/2021

Margin Calibration for Long-Tailed Visual Recognition

The long-tailed class distribution in visual recognition tasks poses gre...

0 Yidong Wang, et al. ∙

research

∙ 12/01/2021

Federated Learning with Adaptive Batchnorm for Personalized Healthcare

There is a growing interest in applying machine learning techniques for ...

0 Yiqiang Chen, et al. ∙

research

∙ 10/15/2021

FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling

The recently proposed FixMatch achieved state-of-the-art results on most...

0 Bowen Zhang, et al. ∙

research

∙ 10/09/2021

Wav2vec-S: Semi-Supervised Pre-Training for Speech Recognition

Self-supervised pre-training has dramatically improved the performance o...

0 Han Zhu, et al. ∙

research

∙ 08/10/2021

AdaRNN: Adaptive Learning and Forecasting of Time Series

Time series has wide applications in the real world and is known to be d...

0 Yuntao Du, et al. ∙

research

∙ 07/27/2021

Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals

Nowadays, multi-sensor technologies are applied in many fields, e.g., He...

17 Yuxin Zhang, et al. ∙

research

∙ 06/02/2021

FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare

The success of machine learning applications often needs a large quantit...

0 Yiqiang Chen, et al. ∙

research

∙ 05/18/2021

Exploiting Adapters for Cross-lingual Low-resource Speech Recognition

Cross-lingual speech adaptation aims to solve the problem of leveraging ...

0 Wenxin Hou, et al. ∙

research

∙ 04/15/2021

Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching

End-to-end automatic speech recognition (ASR) can achieve promising perf...

0 Wenxin Hou, et al. ∙

research

∙ 03/02/2021

Generalizing to Unseen Domains: A Survey on Domain Generalization

Domain generalization (DG), i.e., out-of-distribution generalization, ha...

0 Jindong Wang, et al. ∙

research

∙ 02/25/2021

MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition

In this paper, we propose MixSpeech, a simple yet effective data augment...

14 Linghui Meng, et al. ∙

research

∙ 12/01/2020

Improving the Transferability of Adversarial Examples with the Adam Optimizer

Convolutional neural networks have outperformed humans in image recognit...

0 Heng Yin, et al. ∙

research

∙ 11/03/2020

Learning Causal Semantic Representation for Out-of-Distribution Prediction

Conventional supervised learning methods, especially deep ones, are foun...

1 Chang Liu, et al. ∙

research

∙ 07/17/2020

Learning to Match Distributions for Domain Adaptation

When the training and test data are from different distributions, domain...

11 Chaohui Yu, et al. ∙

research

∙ 09/18/2019

Transfer Learning with Dynamic Adversarial Adaptation Network

The recent advances in deep transfer learning reveal that adversarial le...

0 Chaohui Yu, et al. ∙

research

∙ 09/17/2019

Transfer Learning with Dynamic Distribution Adaptation

Transfer learning aims to learn robust classifiers for the target domain...

7 Jindong Wang, et al. ∙

Jindong Wang

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