activity
20192026
most citedImproving Early Sepsis Prediction with Multi Modal Learning

6 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

DQA: Diagnostic Question Answering for IT Support

Vishaal Kapoor, Mariam Dundua, Sarthak Ahuja +6

Enterprise IT support interactions are fundamentally diagnostic: effective resolution requires iterative evidence gathering from ambiguous user reports to identify an underlying ro…

cs.AI2026

VIGIL: Towards Edge-Extended Agentic AI for Enterprise IT Support

Sarthak Ahuja, Neda Kordjazi, Evren Yortucboylu +7

Enterprise IT support is constrained by heterogeneous devices, evolving policies, and long-tail failure modes that are difficult to resolve centrally. We present VIGIL, an edge-ext…

cs.CL2024

PPLqa: An Unsupervised Information-Theoretic Quality Metric for Comparing Generative Large Language Models

Gerald Friedland, Xin Huang, Yueying Cui +3

We propose PPLqa, an easy to compute, language independent, information-theoretic metric to measure the quality of responses of generative Large Language Models (LLMs) in an unsupe…

cs.CL20216 cited

Improving Early Sepsis Prediction with Multi Modal Learning

Fred Qin, Vivek Madan, Ujjwal Ratan +4

Sepsis is a life-threatening disease with high morbidity, mortality and healthcare costs. The early prediction and administration of antibiotics and intravenous fluids is considere…

math.NT2019

Almost-Primes Represented by Quadratic Polynomials

Vishaal Kapoor

In his paper Almost-Primes Represented by Quadratic Polynomials, Iwaniec proved that the polynomial n^2 + 1 takes on values with at most two prime factors (counted with multiplicit…