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08/11/2023
Self-Alignment with Instruction Backtranslation
We present a scalable method to build a high quality instruction followi...
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08/08/2023
Shepherd: A Critic for Language Model Generation
As large language models improve, there is increasing interest in techni...
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05/19/2023
OPT-R: Exploring the Role of Explanations in Finetuning and Prompting for Reasoning Skills of Large Language Models
In this paper, we conduct a thorough investigation into the reasoning ca...
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05/18/2023
LIMA: Less Is More for Alignment
Large language models are trained in two stages: (1) unsupervised pretra...
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05/08/2023
Blockchained Federated Learning for Internet of Things: A Comprehensive Survey
The demand for intelligent industries and smart services based on big da...
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12/22/2022
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization
Recent work has shown that fine-tuning large pre-trained language models...
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12/16/2022
ALERT: Adapting Language Models to Reasoning Tasks
Current large language models can perform reasonably well on complex tas...
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08/08/2022
Dataset Obfuscation: Its Applications to and Impacts on Edge Machine Learning
Obfuscating a dataset by adding random noises to protect the privacy of ...
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07/18/2022
STT: Soft Template Tuning for Few-Shot Adaptation
Prompt tuning has been an extremely effective tool to adapt a pre-traine...
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03/14/2022
Efficient Language Modeling with Sparse all-MLP
All-MLP architectures have attracted increasing interest as an alternati...
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09/25/2021
Constructing Regression Dataset from Code Evolution History
Bug datasets consisting of real-world bugs are important artifacts for r...
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01/02/2021
SDA: Improving Text Generation with Self Data Augmentation
Data augmentation has been widely used to improve deep neural networks i...
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12/02/2020
ReMP: Rectified Metric Propagation for Few-Shot Learning
Few-shot learning features the capability of generalizing from a few exa...
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07/04/2020
Structure-Aware Human-Action Generation
Generating long-range skeleton-based human actions has been a challengin...
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04/22/2020
Discretized Bottleneck in VAE: Posterior-Collapse-Free Sequence-to-Sequence Learning
Variational autoencoders (VAEs) are important tools in end-to-end repres...
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04/05/2020
Feature Quantization Improves GAN Training
The instability in GAN training has been a long-standing problem despite...
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12/21/2019
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Human-motion generation is a long-standing challenging task due to the r...
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09/26/2019
SIMEX Estimation in Parametric Modal Regression with Measurement Error
For a class of parametric modal regression models with measurement error...
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03/18/2019
Generating Adversarial Examples With Conditional Generative Adversarial Net
Recently, deep neural networks have significant progress and successful ...
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01/16/2019