Chengyue Gong | DeepAI

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∙ 05/04/2023

AutoML-GPT: Automatic Machine Learning with GPT

AI tasks encompass a wide range of domains and fields. While numerous AI...

0 Shujian Zhang, et al. ∙

∙ 12/04/2022

Fast Point Cloud Generation with Straight Flows

Diffusion models have emerged as a powerful tool for point cloud generat...

0 Lemeng Wu, et al. ∙

∙ 11/02/2022

Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models

Retriever-reader models achieve competitive performance across many diff...

0 Shujian Zhang, et al. ∙

∙ 09/07/2022

Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

We present rectified flow, a surprisingly simple approach to learning (n...

2 Xingchao Liu, et al. ∙

∙ 09/02/2022

Diffusion-based Molecule Generation with Informative Prior Bridges

AI-based molecule generation provides a promising approach to a large ar...

11 Lemeng Wu, et al. ∙

∙ 05/10/2022

ALLSH: Active Learning Guided by Local Sensitivity and Hardness

Active learning, which effectively collects informative unlabeled data f...

0 Shujian Zhang, et al. ∙

∙ 02/16/2022

How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity

Although traditional optimization methods focus on finding a single opti...

3 Chengyue Gong, et al. ∙

∙ 12/02/2021

FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization

Generating images from natural language instructions is an intriguing ye...

3 Xingchao Liu, et al. ∙

∙ 09/09/2021

Learning with Different Amounts of Annotation: From Zero to Many Labels

Training NLP systems typically assumes access to annotated data that has...

0 Shujian Zhang, et al. ∙

∙ 06/02/2021

Knowing More About Questions Can Help: Improving Calibration in Question Answering

We study calibration in question answering, estimating whether model cor...

0 Shujian Zhang, et al. ∙

∙ 04/26/2021

Improve Vision Transformers Training by Suppressing Over-smoothing

Introducing the transformer structure into computer vision tasks holds t...

4 Chengyue Gong, et al. ∙

∙ 02/16/2021

AlphaNet: Improved Training of Supernet with Alpha-Divergence

Weight-sharing neural architecture search (NAS) is an effective techniqu...

3 Dilin Wang, et al. ∙

∙ 02/13/2021

Capturing Label Distribution: A Case Study in NLI

We study estimating inherent human disagreement (annotation label distri...

0 Shujian Zhang, et al. ∙

∙ 11/23/2020

AlphaMatch: Improving Consistency for Semi-supervised Learning with Alpha-divergence

Semi-supervised learning (SSL) is a key approach toward more data-effici...

12 Chengyue Gong, et al. ∙

∙ 11/23/2020

KeepAugment: A Simple Information-Preserving Data Augmentation Approach

Data augmentation (DA) is an essential technique for training state-of-t...

22 Chengyue Gong, et al. ∙

∙ 11/18/2020

AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling

Neural architecture search (NAS) has shown great promise designing state...

0 Dilin Wang, et al. ∙

∙ 05/29/2020

SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions

State-of-the-art NLP models can often be fooled by human-unaware transfo...

0 Mao Ye, et al. ∙

∙ 03/03/2020

Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection

Recent empirical works show that large deep neural networks are often hi...

0 Mao Ye, et al. ∙

∙ 02/21/2020

Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework

Randomized classifiers have been shown to provide a promising approach f...

0 Dinghuai Zhang, et al. ∙

∙ 02/20/2020

MaxUp: A Simple Way to Improve Generalization of Neural Network Training

We propose MaxUp, an embarrassingly simple, highly effective technique f...

0 Chengyue Gong, et al. ∙

∙ 06/10/2019

Improving Neural Language Modeling via Adversarial Training

Recently, substantial progress has been made in language modeling by usi...

0 Dilin Wang, et al. ∙

∙ 12/12/2018

Sentence-wise Smooth Regularization for Sequence to Sequence Learning

Maximum-likelihood estimation (MLE) is widely used in sequence to sequen...

0 Chengyue Gong, et al. ∙

∙ 09/18/2018

FRAGE: Frequency-Agnostic Word Representation

Continuous word representation (aka word embedding) is a basic building ...

0 Chengyue Gong, et al. ∙

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