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09/01/2023
Long-Term Memorability On Advertisements
Marketers spend billions of dollars on advertisements but to what end? A...
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09/01/2023
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
Shannon, in his seminal paper introducing information theory, divided th...
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06/13/2023
Learning Unnormalized Statistical Models via Compositional Optimization
Learning unnormalized statistical models (e.g., energy-based models) is ...
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05/31/2023
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels
Learning from noisy labels is an important and long-standing problem in ...
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05/16/2023
A Video Is Worth 4096 Tokens: Verbalize Story Videos To Understand Them In Zero Shot
Multimedia content, such as advertisements and story videos, exhibit a r...
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03/24/2023
Prompt Tuning based Adapter for Vision-Language Model Adaption
Large pre-trained vision-language (VL) models have shown significant pro...
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03/10/2023
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning
Contrastive loss has been increasingly used in learning representations ...
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12/09/2022
AUC Maximization for Low-Resource Named Entity Recognition
Current work in named entity recognition (NER) uses either cross entropy...
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11/24/2022
Shifted Diffusion for Text-to-image Generation
We present Corgi, a novel method for text-to-image generation. Corgi is ...
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11/11/2022
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios
Domain adaptation is an effective solution to data scarcity in low-resou...
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10/25/2022
Lafite2: Few-shot Text-to-Image Generation
Text-to-image generation models have progressed considerably in recent y...
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09/30/2022
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction
Due to limited communication capacities of edge devices, most existing f...
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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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12/07/2021
A Generic Approach for Enhancing GANs by Regularized Latent Optimization
With the rapidly growing model complexity and data volume, training deep...
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11/27/2021
LAFITE: Towards Language-Free Training for Text-to-Image Generation
One of the major challenges in training text-to-image generation models ...
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11/17/2021
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees
Automated Scoring (AS), the natural language processing task of scoring ...
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09/25/2021
MINIMAL: Mining Models for Data Free Universal Adversarial Triggers
It is well known that natural language models are vulnerable to adversar...
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09/24/2021
AES Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses
Deep-learning based Automatic Essay Scoring (AES) systems are being acti...
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08/30/2021
Speaker-Conditioned Hierarchical Modeling for Automated Speech Scoring
Automatic Speech Scoring (ASS) is the computer-assisted evaluation of a ...
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05/27/2021
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval
With the need of fast retrieval speed and small memory footprint, docume...
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05/13/2021
Unsupervised Hashing with Contrastive Information Bottleneck
Many unsupervised hashing methods are implicitly established on the idea...
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05/10/2021
Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels
Learning high-dimensional distributions is an important yet challenging ...
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04/27/2021
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Federated learning has emerged as an important distributed learning para...
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02/07/2021
Meta-Learning with Neural Tangent Kernels
Model Agnostic Meta-Learning (MAML) has emerged as a standard framework ...
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01/04/2021
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation
We investigate large-scale latent variable models (LVMs) for neural stor...
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01/04/2021
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events
Large-scale pretrained language models have shown thrilling generation c...
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01/02/2021
What all do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structure
In recent times, BERT based transformer models have become an inseparabl...
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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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12/27/2020
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring Mechanism
Significant progress has been made in deep-learning based Automatic Essa...
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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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12/01/2020
Unpaired Image-to-Image Translation via Latent Energy Transport
Image-to-image translation aims to preserve source contents while transl...
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11/01/2020
MixKD: Towards Efficient Distillation of Large-scale Language Models
Large-scale language models have recently demonstrated impressive empiri...
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10/05/2020
Learning Manifold Implicitly via Explicit Heat-Kernel Learning
Manifold learning is a fundamental problem in machine learning with nume...
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09/20/2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
The neural attention mechanism plays an important role in many natural l...
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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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06/16/2020
Generative Semantic Hashing Enhanced via Boltzmann Machines
Generative semantic hashing is a promising technique for large-scale inf...
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05/16/2020
Graph Neural Networks with Composite Kernels
Learning on graph structured data has drawn increasing interest in recen...
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05/14/2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition
Skeleton-based action recognition has attracted increasing attention due...
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05/04/2020
Reward Constrained Interactive Recommendation with Natural Language Feedback
Text-based interactive recommendation provides richer user feedback and ...
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05/04/2020
Improving Adversarial Text Generation by Modeling the Distant Future
Auto-regressive text generation models usually focus on local fluency, a...
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05/03/2020
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Text generation from a knowledge base aims to translate knowledge triple...
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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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04/21/2020
Decomposed Adversarial Learned Inference
Effective inference for a generative adversarial model remains an import...
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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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01/20/2020
Nested-Wasserstein Self-Imitation Learning for Sequence Generation
Reinforcement learning (RL) has been widely studied for improving sequen...
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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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12/02/2019
KernelNet: A Data-Dependent Kernel Parameterization for Deep Generative Modeling
Learning with kernels is an often resorted tool in modern machine learni...
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11/25/2019
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution
The traditional super-resolution methods that aim to minimize the mean s...
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08/30/2019
Implicit Deep Latent Variable Models for Text Generation
Deep latent variable models (LVM) such as variational auto-encoder (VAE)...
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08/29/2019
