Papers by Chinmay Sharma

2 papers
Late Fusion of Transformers for Sentiment Analysis of Code-Switched Data (2023.findings-emnlp)

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Challenge: Code-switching is a common phenomenon in multilingual communities . however, sentiment analysis of code-switch data is elusive and unexplored .
Approach: They propose to combine two transformers using logits of their output and feed them to a neural network for sentiment analysis.
Outcome: The proposed system achieves an F1 score of 73.66% for English-Hi and 61.24% for English . it outperforms the best model reported for the GLUECoS benchmark dataset.
Search Query Spell Correction with Weak Supervision in E-commerce (2023.acl-industry)

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Challenge: Misspelled search queries can lead to empty or irrelevant products . only 29% of the population in india is proficient in english .
Approach: They propose to group spell errors into error classes and then leverage a Transformer model for contextual spell correction.
Outcome: The proposed model improves on tough spell mistakes without human intervention without human input.

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