most citedEvaluating LLMs for Visualization Generation and Understanding

6 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Benchmarking Deep Learning Models for Anomaly Detection in Real-World Cloud Telemetry

Sumit Dhyani, Sougata Mukherjea

Modern cloud platforms generate high-dimensional, noisy telemetry from thousands of microservices. Unlike classical anomaly detection benchmarks, cloud anomalies are short-lived, i…

cs.DC2026

Optimizing Cloud Deployment: Blending of IaaS and FaaS for Microservice Architecture

Nikhil Kapoor, Sougata Mukherjea

The rapid evolution of cloud computing has resulted in the adoption of hybrid deployments that blend Infrastructure-as-a-Service (IaaS) and Function-as-a-Service (FaaS) service mod…

cs.AI2025★ 1 cited

InteractiveGNNExplainer: A Visual Analytics Framework for Multi-Faceted Understanding and Probing of Graph Neural Network Predictions

TC Singh, Sougata Mukherjea

Graph Neural Networks (GNNs) excel in graph-based learning tasks, but their complex, non-linear operations often render them as opaque "black boxes". This opacity hinders user trus…

cs.HC2025★ 6 cited

Evaluating LLMs for Visualization Generation and Understanding

Saadiq Rauf Khan, Vinit Chandak, Sougata Mukherjea

Information Visualization has been utilized to gain insights from complex data. In recent times, Large Language models (LLMs) have performed very well in many tasks. In this paper,…

cs.SE2025

Evaluating LLMs for Visualization Tasks

Saadiq Rauf Khan, Vinit Chandak, Sougata Mukherjea

Information Visualization has been utilized to gain insights from complex data. In recent times, Large Language Models (LLMs) have performed very well in many tasks. In this paper,…