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Found 10 papers, 4 papers with code
OCHADAI at SMM4H-2021 Task 5: Classifying self-reporting tweets on potential cases of COVID-19 by ensembling pre-trained language models
Since the outbreak of coronavirus at the end of 2019, there have been numerous studies on coro- navirus in the NLP arena.
Targeted Adversarial Training for Natural Language Understanding
We present a simple yet effective Targeted Adversarial Training (TAT) algorithm to improve adversarial training for natural language understanding.
Posterior Differential Regularization with f-divergence for Improving Model Robustness
Theoretically, we provide a connection of two recent methods, Jacobian Regularization and Virtual Adversarial Training, under this framework.
Adversarial Training for Commonsense Inference
We propose an AdversariaL training algorithm for commonsense InferenCE (ALICE).
Lexical Simplification with the Deep Structured Similarity Model
We explore the application of a Deep Structured Similarity Model (DSSM) to ranking in lexical simplification.
Collocation or Free Combination? --- Applying Machine Translation Techniques to identify collocations in Japanese
This work presents an initial investigation on how to distinguish collocations from free combinations.
