Papers by Dipankar Srirag

2 papers
BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English (2025.findings-acl)

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Challenge: despite large language models showing bias against non-mainstream varieties, there are no labeled datasets for sentiment analysis of English.
Approach: They propose a benchmark for sentiment and sarcasm classification for three varieties of English . they manually annotate the datasets with sentiment and the sarcasmatic labels .
Outcome: The proposed benchmark is based on a web-based content from Google Place reviews and Reddit comments.
Predicting the Target Word of Game-playing Conversations using a Low-Rank Dialect Adapter for Decoder Models (2025.naacl-short)

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Challenge: Existing work proposes dialect adaptation for encoder models or encoder-decoder models.
Approach: They propose to use MD-3 to combine task adapters and dialect adapters to decoder models using a masked word game-playing conversation.
Outcome: The proposed architecture outperforms baselines on Indian English and Nigerian English on a masked conversation with two models.

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