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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...
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12/04/2022
Fast Point Cloud Generation with Straight Flows
Diffusion models have emerged as a powerful tool for point cloud generat...
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11/02/2022
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models
Retriever-reader models achieve competitive performance across many diff...
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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...
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09/02/2022
Diffusion-based Molecule Generation with Informative Prior Bridges
AI-based molecule generation provides a promising approach to a large ar...
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05/10/2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
Active learning, which effectively collects informative unlabeled data f...
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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...
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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...
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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...
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06/02/2021
Knowing More About Questions Can Help: Improving Calibration in Question Answering
We study calibration in question answering, estimating whether model cor...
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04/26/2021
Improve Vision Transformers Training by Suppressing Over-smoothing
Introducing the transformer structure into computer vision tasks holds t...
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02/16/2021
AlphaNet: Improved Training of Supernet with Alpha-Divergence
Weight-sharing neural architecture search (NAS) is an effective techniqu...
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02/13/2021
Capturing Label Distribution: A Case Study in NLI
We study estimating inherent human disagreement (annotation label distri...
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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...
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11/23/2020
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Data augmentation (DA) is an essential technique for training state-of-t...
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11/18/2020
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
Neural architecture search (NAS) has shown great promise designing state...
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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...
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03/03/2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
Recent empirical works show that large deep neural networks are often hi...
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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...
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02/20/2020
MaxUp: A Simple Way to Improve Generalization of Neural Network Training
We propose MaxUp, an embarrassingly simple, highly effective technique f...
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06/10/2019
Improving Neural Language Modeling via Adversarial Training
Recently, substantial progress has been made in language modeling by usi...
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12/12/2018
Sentence-wise Smooth Regularization for Sequence to Sequence Learning
Maximum-likelihood estimation (MLE) is widely used in sequence to sequen...
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09/18/2018