ORCID as entered in ROS
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2024, BAMBINO-LM: (Bilingual-)Human-Inspired Continual Pretraining of BabyLM, , http://arxiv.org/abs/2406.11418v2
,2024, Spectraformer: A Unified Random Feature Framework for Transformer, , http://arxiv.org/abs/2405.15310v2
,2024, Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy, , http://arxiv.org/abs/2405.09854v2
,2024, Evaluating Dialect Robustness of Language Models via Conversation Understanding, , http://arxiv.org/abs/2405.05688v1
,2024, Natural Language Processing for Dialects of a Language: A Survey, , http://arxiv.org/abs/2401.05632v2
,2024, Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages, , http://arxiv.org/abs/2401.03677v1
,2023, Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance, , http://arxiv.org/abs/2311.01472v1
,2023, Stacking the Odds: Transformer-Based Ensemble for AI-Generated Text Detection, , http://arxiv.org/abs/2310.18906v1
,2023, Evaluation of large language models using an Indian language LGBTI+ lexicon, , http://arxiv.org/abs/2310.17787v1
,2019, Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection, , http://arxiv.org/abs/1906.05466v2
,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, Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective, , http://arxiv.org/abs/1903.05801v1
,2018, Hate Speech Detection from Code-mixed Hindi-English Tweets Using Deep Learning Models, , http://arxiv.org/abs/1811.05145v1
,2017, Expect the unexpected: Harnessing Sentence Completion for Sarcasm Detection, , http://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, , http://arxiv.org/abs/1611.04326v2
,2016, Automatic Identification of Sarcasm Target: An Introductory Approach, , http://arxiv.org/abs/1610.07091v2
,2016, A Computational Approach to Automatic Prediction of Drunk Texting, , http://arxiv.org/abs/1610.00879v1
,2016, Are Word Embedding-based Features Useful for Sarcasm Detection?, , http://arxiv.org/abs/1610.00883v1
,2016, Automatic Sarcasm Detection: A Survey, , http://arxiv.org/abs/1602.03426v2
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