Raksha Sharma — accepted AI-conference papers

2025

Power doesn’t reside in size: A Low Parameter Hybrid Language Model (HLM) for Sentiment Analysis in Code-mixed data

Pavan Sai Balaga, Nagasamudram Karthik, Challa Vishwanath, Raksha Sharma, Rudra Murthy, Ashish Mittal

EMNLP 2025

Code-mixed text—where multiple languages are used within the same utterance—is increasingly common in both spoken and written communication. However, it presents significant challenges for machine learning models due to the interplay of distinct grammatical structures, effectively forming a hybrid l

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2023

Late Fusion of Transformers for Sentiment Analysis of Code-Switched Data

Gagan Sharma, R Chinmay, Raksha Sharma

EMNLP 2023short findings

Code-switching is a common phenomenon in multilingual communities and is often used on social media. However, sentiment analysis of code-switched data is a challenging yet less explored area of research. This paper aims to develop a sentiment analysis system for code-switched data. In this paper, we…

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