Select Publications
Preprints
, 2025, Nek Minit: Harnessing Pragmatic Metacognitive Prompting for Explainable Sarcasm Detection of Australian and Indian English, http://dx.doi.org/10.48550/arxiv.2505.15095
, 2025, LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models, https://arxiv.org/abs/2510.23011v1
, 2025, Spectraformer: A Unified Random Feature Framework for Transformer, http://dx.doi.org/10.48550/arxiv.2405.15310
, 2025, What am I missing here?: Evaluating Large Language Models for Masked Sentence Prediction, https://arxiv.org/abs/2508.07702v1
, 2025, A Survey of Classification Tasks and Approaches for Legal Contracts, http://dx.doi.org/10.48550/arxiv.2507.21108
, 2025, BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English, http://dx.doi.org/10.48550/arxiv.2412.04726
, 2025, A Survey on Multimodal Music Emotion Recognition, https://arxiv.org/abs/2504.18799v1
, 2025, Predicting the Target Word of Game-playing Conversations using a Low-Rank Dialect Adapter for Decoder Models, http://dx.doi.org/10.48550/arxiv.2409.00358
, 2025, RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles, http://dx.doi.org/10.48550/arxiv.2501.11440
, 2024, Evaluating Dialect Robustness of Language Models via Conversation Understanding, http://dx.doi.org/10.48550/arxiv.2405.05688
, 2024, Comparison of Multilingual and Bilingual Models for Satirical News Detection of Arabic and English, http://dx.doi.org/10.48550/arxiv.2411.10730
, 2024, Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English, http://dx.doi.org/10.48550/arxiv.2410.11216
, 2024, "Is Hate Lost in Translation?": Evaluation of Multilingual LGBTQIA+ Hate Speech Detection, https://arxiv.org/abs/2410.11230v2
, 2024, Connecting Ideas in 'Lower-Resource' Scenarios: NLP for National Varieties, Creoles and Other Low-resource Scenarios, https://arxiv.org/abs/2409.12683v1
, 2024, AuditNet: A Conversational AI-based Security Assistant [DEMO], http://dx.doi.org/10.48550/arxiv.2407.14116
, 2024, BAMBINO-LM: (Bilingual-)Human-Inspired Continual Pretraining of BabyLM, https://arxiv.org/abs/2406.11418v2
, 2024, Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy, https://arxiv.org/abs/2405.09854v2
, 2024, Natural Language Processing for Dialects of a Language: A Survey, https://arxiv.org/abs/2401.05632v4
, 2024, Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages, https://arxiv.org/abs/2401.03677v1
, 2023, Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance, http://dx.doi.org/10.48550/arxiv.2311.01472
, 2023, Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection, https://arxiv.org/abs/2310.18906v1
, 2023, Evaluation of large language models using an Indian language LGBTI+ lexicon, https://arxiv.org/abs/2310.17787v1
, 2019, A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics, http://dx.doi.org/10.48550/arxiv.1906.05468
, 2019, Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection, https://arxiv.org/abs/1906.05466v2
, 2019, Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective, http://dx.doi.org/10.48550/arxiv.1903.05801
, 2018, Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning Models, https://arxiv.org/abs/1811.05145v1
, 2017, Expect the unexpected: Harnessing Sentence Completion for Sarcasm Detection, https://arxiv.org/abs/1707.06151v1
, 2016, `Who would have thought of that!': A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm Detection, https://arxiv.org/abs/1611.04326v2
, 2016, Automatic Identification of Sarcasm Target: An Introductory Approach, https://arxiv.org/abs/1610.07091v2
, 2016, A Computational Approach to Automatic Prediction of Drunk Texting, https://arxiv.org/abs/1610.00879v1
, 2016, Are Word Embedding-based Features Useful for Sarcasm Detection?, https://arxiv.org/abs/1610.00883v1
, 2016, Automatic Sarcasm Detection: A Survey, https://arxiv.org/abs/1602.03426v2