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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...
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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...
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08/04/2023
Frustratingly Easy Model Generalization by Dummy Risk Minimization
Empirical risk minimization (ERM) is a fundamental machine learning para...
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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...
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07/14/2023
EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus
Large language models (LLMs) have achieved significant performance in ma...
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07/06/2023
A Survey on Evaluation of Large Language Models
Large language models (LLMs) are gaining increasing popularity in both a...
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06/08/2023
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Instruction tuning large language models (LLMs) remains a challenging ta...
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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 ...
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05/31/2023
A hybridizable discontinuous Galerkin method for magnetic advection-diffusion problems
We propose and analyze a hybridizable discontinuous Galerkin (HDG) metho...
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05/23/2023
Out-of-Distribution Generalization in Text Classification: Past, Present, and Future
Machine learning (ML) systems in natural language processing (NLP) face ...
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04/04/2023
Exploring Vision-Language Models for Imbalanced Learning
Vision-Language models (VLMs) that use contrastive language-image pre-tr...
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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...
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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 ...
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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...
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11/20/2022
An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning
Semi-supervised learning (SSL) has shown great promise in leveraging unl...
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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...
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11/07/2022
FIXED: Frustratingly Easy Domain Generalization with Mixup
Domain generalization (DG) aims to learn a generalizable model from mult...
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09/15/2022
Generalized Representations Learning for Time Series Classification
Time series classification is an important problem in real world. Due to...
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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...
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08/17/2022
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction
Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentim...
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08/15/2022
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets
While parameter efficient tuning (PET) methods have shown great potentia...
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08/12/2022
USB: A Unified Semi-supervised Learning Benchmark
Semi-supervised learning (SSL) improves model generalization by leveragi...
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08/03/2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift
Machine learning systems may encounter unexpected problems when the data...
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08/02/2022
Discontinuous Galerkin methods for magnetic advection-diffusion problems
We devise and analyze a class of the primal discontinuous Galerkin metho...
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07/25/2022
Domain-invariant Feature Exploration for Domain Generalization
Deep learning has achieved great success in the past few years. However,...
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07/21/2022
Domain Generalization for Activity Recognition via Adaptive Feature Fusion
Human activity recognition requires the efforts to build a generalizable...
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06/26/2022
Memory-Guided Multi-View Multi-Domain Fake News Detection
The wide spread of fake news is increasingly threatening both individual...
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06/20/2022
Boosting Cross-Domain Speech Recognition with Self-Supervision
The cross-domain performance of automatic speech recognition (ASR) could...
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06/18/2022
Decoupled Federated Learning for ASR with Non-IID Data
Automatic speech recognition (ASR) with federated learning (FL) makes it...
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06/17/2022
MetaFed: Federated Learning among Federations with Cyclic Knowledge Distillation for Personalized Healthcare
Federated learning has attracted increasing attention to building models...
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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...
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05/15/2022
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Pseudo labeling and consistency regularization approaches with confidenc...
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01/04/2022
Multi-Representation Adaptation Network for Cross-domain Image Classification
In image classification, it is often expensive and time-consuming to acq...
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01/03/2022
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection
Unsupervised anomaly detection aims to build models to effectively detec...
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12/14/2021
Margin Calibration for Long-Tailed Visual Recognition
The long-tailed class distribution in visual recognition tasks poses gre...
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12/01/2021
Federated Learning with Adaptive Batchnorm for Personalized Healthcare
There is a growing interest in applying machine learning techniques for ...
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10/15/2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
The recently proposed FixMatch achieved state-of-the-art results on most...
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10/09/2021
Wav2vec-S: Semi-Supervised Pre-Training for Speech Recognition
Self-supervised pre-training has dramatically improved the performance o...
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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...
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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...
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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...
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05/18/2021
Exploiting Adapters for Cross-lingual Low-resource Speech Recognition
Cross-lingual speech adaptation aims to solve the problem of leveraging ...
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04/15/2021
Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching
End-to-end automatic speech recognition (ASR) can achieve promising perf...
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03/02/2021
Generalizing to Unseen Domains: A Survey on Domain Generalization
Domain generalization (DG), i.e., out-of-distribution generalization, ha...
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02/25/2021
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition
In this paper, we propose MixSpeech, a simple yet effective data augment...
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12/01/2020
Improving the Transferability of Adversarial Examples with the Adam Optimizer
Convolutional neural networks have outperformed humans in image recognit...
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11/03/2020
Learning Causal Semantic Representation for Out-of-Distribution Prediction
Conventional supervised learning methods, especially deep ones, are foun...
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07/17/2020
Learning to Match Distributions for Domain Adaptation
When the training and test data are from different distributions, domain...
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09/18/2019
Transfer Learning with Dynamic Adversarial Adaptation Network
The recent advances in deep transfer learning reveal that adversarial le...
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09/17/2019
