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conftrace_

downstream task

207 papers

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