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Masked Language Modeling

Papers

Showing 226–250 of 475 papers

TitleStatusHype
How does the pre-training objective affect what large language models learn about linguistic properties?—0
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks—0
ImageBERT: Cross-modal Pre-training with Large-scale Weak-supervised Image-Text Data—0
Image BERT Pre-training with Online Tokenizer—0
Improving BERT with Hybrid Pooling Network and Drop Mask—0
Improving Low-Resource Morphological Inflection via Self-Supervised Objectives—0
Improving the Reusability of Pre-trained Language Models in Real-world Applications—0
In-Context Learning can distort the relationship between sequence likelihoods and biological fitness—0
Investigating Masking-based Data Generation in Language Models—0
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction—0
"Is Whole Word Masking Always Better for Chinese BERT?": Probing on Chinese Grammatical Error Correction—0
“Is Whole Word Masking Always Better for Chinese BERT?”: Probing on Chinese Grammatical Error Correction—0
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling—0
Joint unsupervised and supervised learning for context-aware language identification—0
Joint Unsupervised and Supervised Training for Multilingual ASR—0
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering—0
Knowing Where to Focus: Attention-Guided Alignment for Text-based Person Search—0
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification—0
Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget—0
KUL@SMM4H’22: Template Augmented Adaptive Pre-training for Tweet Classification—0
LakotaBERT: A Transformer-based Model for Low Resource Lakota Language—0
LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model—0
Larger-Scale Transformers for Multilingual Masked Language Modeling—0
LayoutMask: Enhance Text-Layout Interaction in Multi-modal Pre-training for Document Understanding—0
Enhancing Continual Learning with Global Prototypes: Counteracting Negative Representation Drift—0
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