research
∙
05/24/2023
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts
The explosive growth of language models and their applications have led ...
share
research
∙
04/18/2023
Token Imbalance Adaptation for Radiology Report Generation
Imbalanced token distributions naturally exist in text documents, leadin...
research
∙
04/11/2023
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference
We propose Conditional Adapter (CoDA), a parameter-efficient transfer le...
research
∙
10/21/2022
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Knowledge distillation is one of the primary methods of transferring kno...
research
∙
10/20/2022
Large Language Models Can Self-Improve
Large Language Models (LLMs) have achieved excellent performances in var...
research
∙
05/26/2022
Unsupervised Reinforcement Adaptation for Class-Imbalanced Text Classification
Class imbalance naturally exists when train and test models in different...
research
∙
03/24/2022
Token Dropping for Efficient BERT Pretraining
Transformer-based models generally allocate the same amount of computati...
research
∙
02/24/2022
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance
In this paper, we study contrastive learning from an optimization perspe...
research
∙
12/09/2020
GRP: A Gumbel-based Rating Prediction Framework for Imbalanced Recommendation
Rating prediction is a core problem in recommender systems to quantify u...
research
∙
12/08/2020
TADO: Time-varying Attention with Dual-Optimizer Model
The review-based recommender systems are commonly utilized to measure us...
research
∙
06/12/2020
Generalized Multi-Relational Graph Convolution Network
Graph Convolutional Networks (GCNs) have received increasing attention i...
research
∙
11/17/2019
Graph-Revised Convolutional Network
Graph Convolutional Networks (GCNs) have received increasing attention i...
research
∙
10/16/2019
Active Learning for Graph Neural Networks via Node Feature Propagation
Graph Neural Networks (GNNs) for prediction tasks like node classificati...
research
∙
12/06/2018
StoryGAN: A Sequential Conditional GAN for Story Visualization
In this work we propose a new task called Story Visualization. Given a m...
research
∙
11/19/2018
Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning
Training task-completion dialogue agents with reinforcement learning usu...
research
∙
09/10/2018
Unsupervised Cross-lingual Transfer of Word Embedding Spaces
Cross-lingual transfer of word embeddings aims to establish the semantic...
research
∙
09/01/2018
Contextual Encoding for Translation Quality Estimation
The task of word-level quality estimation (QE) consists of taking a sour...
research
∙
05/06/2017
Analogical Inference for Multi-Relational Embeddings
Large-scale multi-relational embedding refers to the task of learning th...
research
∙
05/25/2016
Review Networks for Caption Generation
We propose a novel extension of the encoder-decoder framework, called a ...
research
∙
12/08/2014