1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Understanding Tone-Dependent Inference Cost in Large Language Models
Akhil Kumar, Om Dobariya
We examine how prompt tone affects both accuracy of the LLM answers and inference cost as reflected in output-token consumption. Experiments were performed to understand the trade-…
cs.AI2025
Evaluation of LLMs for Process Model Analysis and Optimization
Akhil Kumar, Jianliang Leon Zhao, Om Dobariya
In this paper, we report our experience with several LLMs for their ability to understand a process model in an interactive, conversational style, find syntactical and logical erro…
cs.CL2025★ 1 cited
Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
Om Dobariya, Akhil Kumar
The wording of natural language prompts has been shown to influence the performance of large language models (LLMs), yet the role of politeness and tone remains underexplored. In t…