4 citations · 8 across the 6 of their papers we have counts for
6 papers
RF: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference
Hao Wang, Yixin Cao, Yangguang Li +3
Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothe…
A Mixture of Surprises for Unsupervised Reinforcement Learning
Andrew Zhao, Matthieu Gaetan Lin, Yangguang Li +2
Unsupervised reinforcement learning aims at learning a generalist policy in a reward-free manner for fast adaptation to downstream tasks. Most of the existing methods propose to pr…
Neighbor Regularized Bayesian Optimization for Hyperparameter Optimization
Lei Cui, Yangguang Li, Xin Lu +2
Bayesian Optimization (BO) is a common solution to search optimal hyperparameters based on sample observations of a machine learning model. Existing BO algorithms could converge sl…
Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision
Yufeng Cui, Lichen Zhao, Feng Liang +2
Contrastive Language-Image Pretraining (CLIP) has emerged as a novel paradigm to learn visual models from language supervision. While researchers continue to push the frontier of C…
SNCSE: Contrastive Learning for Unsupervised Sentence Embedding with Soft Negative Samples
Hao Wang, Yangguang Li, Zhen Huang +3
Unsupervised sentence embedding aims to obtain the most appropriate embedding for a sentence to reflect its semantic. Contrastive learning has been attracting developing attention.…
RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training
Luya Wang, Feng Liang, Yangguang Li +3
Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability. However, the dominant method, contrastive…