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Cluster Analysis of Online Mental Health Discourse using Topic-Infused Deep Contextualized Representations
With mental health as a problem domain in NLP, the bulk of contemporary literature revolves around building better mental illness prediction models.
Intent-conditioned and Non-toxic Counterspeech Generation using Multi-Task Instruction Tuning with RLAIF
Counterspeech, defined as a response to mitigate online hate speech, is increasingly used as a non-censorial solution.
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills.
Combining Context-Free and Contextualized Representations for Arabic Sarcasm Detection and Sentiment Identification
The proposed system achieves a F1-sarcastic score of 0. 62 and a F-PN score of 0. 715 for the sarcasm and sentiment detection tasks, respectively.
An Attention Ensemble Approach for Efficient Text Classification of Indian Languages
Experimental results show that the proposed model outperforms various baseline machine learning and deep learning models in the given task, giving the best validation accuracy of 89. 57\% and f1-score of 0. 8875.
