2 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
When Does a Classifier Help an LLM? Classifier-Guided Prompting and Hybrid Classifier-LLM Models for Credit-Default Prediction
Rishi Datta, Lavanya Prahallad
Credit-default prediction is an important task in financial decision making. Traditional methods use fitted classifiers such as logistic regression and random forests on tabular fe…
Prompt-Based Clarity Evaluation and Topic Detection in Political Question Answering
Lavanya Prahallad, Sai Utkarsh Choudarypally, Pragna Prahallad +1
Automatic evaluation of large language model (LLM) responses requires not only factual correctness but also clarity, particularly in political question-answering. While recent data…
Analyzing Biases in Political Dialogue: Tagging U.S. Presidential Debates with an Extended DAMSL Framework
Lavanya Prahallad, Radhika Mamidi
We present a critical discourse analysis of the 2024 U.S. presidential debates, examining Donald Trump's rhetorical strategies in his interactions with Joe Biden and Kamala Harris.…
Enhancing Granular Sentiment Classification with Chain-of-Thought Prompting in Large Language Models
Vihaan Miriyala, Smrithi Bukkapatnam, Lavanya Prahallad
We explore the use of Chain-of-Thought (CoT) prompting with large language models (LLMs) to improve the accuracy of granular sentiment categorization in app store reviews. Traditio…
Significance of Chain of Thought in Gender Bias Mitigation for English-Dravidian Machine Translation
Lavanya Prahallad, Radhika Mamidi
Gender bias in machine translation (MT) sys- tems poses a significant challenge to achieving accurate and inclusive translations. This paper examines gender bias in machine transla…