6 papers
Intelligibility of Speech in Noise: Investigating Contribution of Magnitude and Phase Spectra
Bhanu Teja Nellore, Sudarsana Reddy Kadiri, Rohit Kumar +2
It is well known that intelligibility of speech reduces in the presence of ambient noise. However, studies show that all sounds are not affected uniformly (or equally) and that vow…
No Universal Courtesy: A Cross-Linguistic, Multi-Model Study of Politeness Effects on LLMs Using the PLUM Corpus
Hitesh Mehta, Arjit Saxena, Garima Chhikara +1
This paper explores the response of Large Language Models (LLMs) to user prompts with different degrees of politeness and impoliteness. The Politeness Theory by Brown and Levinson…
KGHaluBench: A Knowledge Graph-Based Hallucination Benchmark for Evaluating the Breadth and Depth of LLM Knowledge
Alex Robertson, Huizhi Liang, Mahbub Gani +2
Large Language Models (LLMs) possess a remarkable capacity to generate persuasive and intelligible language. However, coherence does not equate to truthfulness, as the responses of…
Smarter AI Through Prompt Engineering: Insights and Case Studies from Data Science Application
Snehasish Paul, Rohit Kumar, Laxman Das
The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for an…
UNITYAI-GUARD: Pioneering Toxicity Detection Across Low-Resource Indian Languages
Himanshu Beniwal, Reddybathuni Venkat, Rohit Kumar +7
This work introduces UnityAI-Guard, a framework for binary toxicity classification targeting low-resource Indian languages. While existing systems predominantly cater to high-resou…
Ensemble based approach to quantifying uncertainty of LLM based classifications
Srijith Rajamohan, Ahmed Salhin, Josh Frazier +3
The output of Large Language Models (LLMs) are a function of the internal model's parameters and the input provided into the context window. The hypothesis presented here is that u…