research
∙
06/21/2023
Continual Learners are Incremental Model Generalizers
Motivated by the efficiency and rapid convergence of pre-trained models ...
share
research
∙
06/20/2023
Progressive Neural Representation for Sequential Video Compilation
Neural Implicit Representations (NIR) have gained significant attention ...
research
∙
06/08/2023
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
Recent neural architecture search (NAS) frameworks have been successful ...
research
∙
06/07/2023
Phrase Retrieval for Open-Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning
Open-Domain Conversational Question Answering (ODConvQA) aims at answeri...
research
∙
05/30/2023
Context-Preserving Two-Stage Video Domain Translation for Portrait Stylization
Portrait stylization, which translates a real human face image into an a...
research
∙
05/30/2023
Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation
Language models have achieved impressive performances on dialogue genera...
research
∙
05/28/2023
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks
Large Language Models (LLMs) have shown promising performance in knowled...
research
∙
05/26/2023
Meta-prediction Model for Distillation-Aware NAS on Unseen Datasets
Distillation-aware Neural Architecture Search (DaNAS) aims to search for...
research
∙
05/26/2023
DiffusionNAG: Task-guided Neural Architecture Generation with Diffusion Models
Neural Architecture Search (NAS) has emerged as a powerful technique for...
research
∙
05/26/2023
A Study on Knowledge Distillation from Weak Teacher for Scaling Up Pre-trained Language Models
Distillation from Weak Teacher (DWT) is a method of transferring knowled...
research
∙
05/26/2023
Set-based Neural Network Encoding
We propose an approach to neural network weight encoding for generalizat...
research
∙
05/23/2023
ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models
Emotional Text-To-Speech (TTS) is an important task in the development o...
research
∙
05/21/2023
Direct Fact Retrieval from Knowledge Graphs without Entity Linking
There has been a surge of interest in utilizing Knowledge Graphs (KGs) f...
research
∙
04/04/2023
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models
Token-based masked generative models are gaining popularity for their fa...
research
∙
03/27/2023
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation
In this paper, we introduce a novel learning scheme named weakly semi-su...
research
∙
03/27/2023
Forget-free Continual Learning with Soft-Winning SubNetworks
Inspired by Regularized Lottery Ticket Hypothesis (RLTH), which states t...
research
∙
02/10/2023
Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement
Conversational Question Answering (ConvQA) models aim at answering a que...
research
∙
02/07/2023
Graph Generation with Destination-Driven Diffusion Mixture
Generation of graphs is a major challenge for real-world tasks that requ...
research
∙
11/19/2022
Efficient Video Representation Learning via Masked Video Modeling with Motion-centric Token Selection
Self-supervised Video Representation Learning (VRL) aims to learn transf...
research
∙
11/17/2022
Any-speaker Adaptive Text-To-Speech Synthesis with Diffusion Models
There has been a significant progress in Text-To-Speech (TTS) synthesis ...
research
∙
10/19/2022
Few-shot Transferable Robust Representation Learning via Bilevel Attacks
Existing adversarial learning methods for enhancing the robustness of de...
research
∙
10/19/2022
Targeted Adversarial Self-Supervised Learning
Recently, unsupervised adversarial training (AT) has been extensively st...
research
∙
10/19/2022
Language Detoxification with Attribute-Discriminative Latent Space
Transformer-based Language Models (LMs) achieve remarkable performances ...
research
∙
10/05/2022
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
Masked image modeling (MIM) has become a popular strategy for self-super...
research
∙
09/15/2022
On the Soft-Subnetwork for Few-shot Class Incremental Learning
Inspired by Regularized Lottery Ticket Hypothesis (RLTH), which hypothes...
research
∙
08/26/2022
Universal Mini-Batch Consistency for Set Encoding Functions
Previous works have established solid foundations for neural set functio...
research
∙
08/23/2022
StyleTalker: One-shot Style-based Audio-driven Talking Head Video Generation
We propose StyleTalker, a novel audio-driven talking head generation mod...
research
∙
08/23/2022
Object Detection in Aerial Images with Uncertainty-Aware Graph Network
In this work, we propose a novel uncertainty-aware object detection fram...
research
∙
08/21/2022
Dataset Condensation with Latent Space Knowledge Factorization and Sharing
In this paper, we introduce a novel approach for systematically solving ...
research
∙
07/04/2022
BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation
Neural network quantization aims to transform high-precision weights and...
research
∙
06/21/2022
Personalized Subgraph Federated Learning
In real-world scenarios, subgraphs of a larger global graph may be distr...
research
∙
06/20/2022
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation
Real-time video segmentation is a crucial task for many real-world appli...
research
∙
05/20/2022
Set-based Meta-Interpolation for Few-Task Meta-Learning
Meta-learning approaches enable machine learning systems to adapt to new...
research
∙
04/25/2022
Skill-based Meta-Reinforcement Learning
While deep reinforcement learning methods have shown impressive results ...
research
∙
04/22/2022
KALA: Knowledge-Augmented Language Model Adaptation
Pre-trained language models (PLMs) have achieved remarkable success on v...
research
∙
03/15/2022
Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation
Dense retrieval models, which aim at retrieving the most relevant docume...
research
∙
02/23/2022
Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
In practical federated learning scenarios, the participating devices may...
research
∙
02/07/2022
Graph Self-supervised Learning with Accurate Discrepancy Learning
Self-supervised learning of graph neural networks (GNNs) aims to learn a...
research
∙
02/05/2022
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Generating graph-structured data requires learning the underlying distri...
research
∙
02/01/2022
Factorized-FL: Agnostic Personalized Federated Learning with Kernel Factorization Similarity Matching
In real-world federated learning scenarios, participants could have thei...
research
∙
12/21/2021
MPViT: Multi-Path Vision Transformer for Dense Prediction
Dense computer vision tasks such as object detection and segmentation re...
research
∙
12/16/2021
Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing
The Mixup scheme suggests mixing a pair of samples to create an augmente...
research
∙
11/22/2021
DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing
Many applications that utilize sensors in mobile devices and apply machi...
research
∙
10/13/2021
Rethinking the Representational Continuity: Towards Unsupervised Continual Learning
Continual learning (CL) aims to learn a sequence of tasks without forget...
research
∙
10/12/2021
Meta Learning Low Rank Covariance Factors for Energy-Based Deterministic Uncertainty
Numerous recent works utilize bi-Lipschitz regularization of neural netw...
research
∙
10/06/2021
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning
Multilingual models jointly pretrained on multiple languages have achiev...
research
∙
10/06/2021
Online Hyperparameter Meta-Learning with Hypergradient Distillation
Many gradient-based meta-learning methods assume a set of parameters tha...
research
∙
10/04/2021
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Recently, utilizing reinforcement learning (RL) to generate molecules wi...
research
∙
09/05/2021
Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss
Network quantization, which aims to reduce the bit-lengths of the networ...
research
∙
07/02/2021