5 papers
SectEval: Evaluating the Latent Sectarian Preferences of Large Language Models
Aditya Maheshwari, Amit Gajkeshwar, Kaushal Sharma +1
As Large Language Models (LLMs) becomes a popular source for religious knowledge, it is important to know if it treats different groups fairly. This study is the first to measure h…
IndicParam: Benchmark to evaluate LLMs on low-resource Indic Languages
Ayush Maheshwari, Kaushal Sharma, Vivek Patel +1
While large language models excel on high-resource multilingual tasks, low- and extremely low-resource Indic languages remain severely under-evaluated. We present IndicParam, a hum…
ParamBench: A Graduate-Level Benchmark for Evaluating LLM Understanding on Indic Subjects
Ayush Maheshwari, Kaushal Sharma, Vivek Patel +1
Large language models have been widely evaluated on tasks such as comprehension, summarization, code generation, etc. However, their performance on graduate-level, culturally groun…
Modelling and prediction of the wildfire data using fractional Poisson process
Sudeep R. Bapat, Aditya Maheshwari
Modelling wildfire events has been studied in the literature using the Poisson process, which essentially assumes the independence of wildfire events. In this paper, we use the fra…
Tempered Fractional Hawkes Process and Its Generalization
Neha Gupta, Aditya Maheshwari
Hawkes process (HP) is a point process with a conditionally dependent intensity function. This paper defines the tempered fractional Hawkes process (TFHP) by time-changing the HP w…