Co-occurring keywords · papers mentioning both
Papers
Unsupervised Object-Level Representation Learning from Scene Images
NeurIPS 2021
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning
NeurIPS 2021
Adversarially Robust Representations with Smooth Encoders
ICLR 2020
An Empirical Study of the Downstream Reliability of Pre-Trained Word Embeddings
COLING 2020
A Simple and Effective Usage of Word Clusters for CBOW Model
AACL 2020
Guiding Attention for Self-Supervised Learning with Transformers
EMNLP 2020
How Useful Is Self-Supervised Pretraining for Visual Tasks?
CVPR 2020
Large Product Key Memory for Pretrained Language Models
EMNLP 2020
Learning to Evaluate Perception Models Using Planner-Centric Metrics
CVPR 2020
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models
EMNLP 2020
MeDAL: Medical Abbreviation Disambiguation Dataset for Natural Language Understanding Pretraining
EMNLP 2020
Optimizing Word Segmentation for Downstream Task
EMNLP 2020
QuASE: Question-Answer Driven Sentence Encoding
ACL 2020
Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging
MLHC 2020
The Impact of De-identification on Downstream Named Entity Recognition in Clinical Text
EMNLP 2020
Towards Debiasing Sentence Representations
ACL 2020
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
ICML 2020
Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering
EMNLP 2019
An Evaluation of Language-Agnostic Inner-Attention-Based Representations in Machine Translation
ACL 2019
BioReddit: Word Embeddings for User-Generated Biomedical NLP
EMNLP 2019
Empirical Linguistic Study of Sentence Embeddings
ACL 2019
How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions
ACL 2019
Learning deep representations by mutual information estimation and maximization
ICLR 2019
Learning to Sample
CVPR 2019
Machine Translation for Machines: the Sentiment Classification Use Case
EMNLP 2019