9 papers
BARRAC: Adaptation of an English Aspect-based Sentiment Analysis Approach for Classification Tasks in Arabic Dialects
Ali Almutairi, Gelareh Mohammadi, Imran Razzak +1
With the rapid growth of Arabic NLP, several models, datasets and benchmarks have been reported. This paper asks whether approaches developed for majority languages like English ca…
DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation
Jordan Painter, Dipankar Srirag, Adarsh Kappiyath +3
Large language models increasingly understand dialectal English, yet still produce only standard, US-leaning English, leaving dialectal generation, the harder half of the problem,…
Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR
Debajyoti Mazumder, Divyansh Pathak, Prashant Kodali +3
Large language models often exhibit a substantial gap between their performance in English and in lower-resourced languages on equivalent knowledge queries---a cross-lingual consis…
Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages
Ali Almutairi, Abdullah Alsuhaibani, Shoaib Jameel +3
Training deep learning networks with minimal supervision has gained significant research attention due to its potential to reduce reliance on extensive labelled data. While self-tr…
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…