19 citations · 42 across the 11 of their papers we have counts for
11 papers
Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation
Anshul Bagaria, Sowmya S Sundaram, Gokul S Krishnan +1
LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candidate responses with respect to a…
KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability
Krithi Shailya, Ananya Lakshmi Ravi, Venkatanathan K. V. +4
Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In clinical workflows, chest X-ray…
Toward Total Recall: Enhancing FAIRness through AI-Driven Metadata Standardization
Sowmya S Sundaram, Rafael S. Gonçalves, Mark A Musen
Scientific metadata often suffer from incompleteness, inconsistency, and formatting errors, which hinder effective discovery and reuse of the associated datasets. We present a meth…
Ensuring Adherence to Standards in Experiment-Related Metadata Entered Via Spreadsheets
Martin J. O'Connor, Josef Hardi, Marcos Martínez-Romero +5
Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated to…
Can a Hallucinating Model help in Reducing Human "Hallucination"?
Sowmya S Sundaram, Balaji Alwar
The prevalence of unwarranted beliefs, spanning pseudoscience, logical fallacies, and conspiracy theories, presents substantial societal hurdles and the risk of disseminating misin…
Use of a Structured Knowledge Base Enhances Metadata Curation by Large Language Models
Sowmya S. Sundaram, Benjamin Solomon, Avani Khatri +3
Metadata play a crucial role in ensuring the findability, accessibility, interoperability, and reusability of datasets. This paper investigates the potential of large language mode…
GeneMask: Fast Pretraining of Gene Sequences to Enable Few-Shot Learning
Soumyadeep Roy, Jonas Wallat, Sowmya S Sundaram +2
Large-scale language models such as DNABert and LOGO aim to learn optimal gene representations and are trained on the entire Human Reference Genome. However, standard tokenization…
Making Metadata More FAIR Using Large Language Models
Sowmya S. Sundaram, Mark A. Musen
With the global increase in experimental data artifacts, harnessing them in a unified fashion leads to a major stumbling block - bad metadata. To bridge this gap, this work present…
Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers
Sowmya S Sundaram, Sairam Gurajada, Marco Fisichella +2
From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP). It is a challenging…
FiSH: Fair Spatial Hotspots
Deepak P, Sowmya S Sundaram
Pervasiveness of tracking devices and enhanced availability of spatially located data has deepened interest in using them for various policy interventions, through computational da…
Fairness in Clustering with Multiple Sensitive Attributes
Savitha Sam Abraham, Deepak P, Sowmya S Sundaram
A clustering may be considered as fair on pre-specified sensitive attributes if the proportions of sensitive attribute groups in each cluster reflect that in the dataset. In this p…