5 papers
Nek Minit: Harnessing Pragmatic Metacognitive Prompting for Explainable Sarcasm Detection of Australian and Indian English
Ishmanbir Singh, Dipankar Srirag, Aditya Joshi
Sarcasm is a challenge to sentiment analysis because of the incongruity between stated and implied sentiment. The challenge is exacerbated when the implication may be relevant to a…
TRACE: Textual Relevance Augmentation and Contextual Encoding for Multimodal Hate Detection
Girish A. Koushik, Helen Treharne, Aditya Joshi +1
Social media memes are a challenging domain for hate detection because they intertwine visual and textual cues into culturally nuanced messages. To tackle these challenges, we intr…
BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English
Dipankar Srirag, Aditya Joshi, Jordan Painter +1
Despite large language models (LLMs) being known to exhibit bias against non-standard language varieties, there are no known labelled datasets for sentiment analysis of English. To…
Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English
Dipankar Srirag, Jordan Painter, Aditya Joshi +1
Existing benchmarks often fail to account for linguistic diversity, like language variants of English. In this paper, we share our experiences from our ongoing project of building…
Connecting Ideas in 'Lower-Resource' Scenarios: NLP for National Varieties, Creoles and Other Low-resource Scenarios
Aditya Joshi, Diptesh Kanojia, Heather Lent +2
Despite excellent results on benchmarks over a small subset of languages, large language models struggle to process text from languages situated in `lower-resource' scenarios such…