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Found 7 papers, 1 papers with code
To Burst or Not to Burst: Generating and Quantifying Improbable Text
While large language models (LLMs) are extremely capable at text generation, their outputs are still distinguishable from human-authored text.
Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages
We adopt cross-lingual embeddings constructed using different methods to extract features of the tweets, including a few state-of-the-art contextual embeddings such as BERT, RoBERTa and XLM-R. We train classifiers of different architectures on the extracted features.
Scalable Cross-lingual Treebank Synthesis for Improved Production Dependency Parsers
We present scalable Universal Dependency (UD) treebank synthesis techniques that exploit advances in language representation modeling which leverage vast amounts of unlabeled general-purpose multilingual text.
Answer Span Correction in Machine Reading Comprehension
Answer validation in machine reading comprehension (MRC) consists of verifying an extracted answer against an input context and question pair.
Multi-Stage Pre-training for Low-Resource Domain Adaptation
Transfer learning techniques are particularly useful in NLP tasks where a sizable amount of high-quality annotated data is difficult to obtain.
Predictive Linguistic Features of Schizophrenia
As such, we examine the writings of schizophrenia patients analyzing their syntax, semantics and pragmatics.
Topic Modeling for Classification of Clinical Reports
We demonstrate new classifiers based on this topic modeling representation of the reports.
