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20212026
most citedA Systematic Review of Digital Twin-Driven Predictive Maintenance in Industrial Engineering: Taxonomy, Architectural Elements, and Future Research Directions

2 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

ARREST: Adversarial Resilient Regulation Enhancing Safety and Truth in Large Language Models

Sharanya Dasgupta, Arkaprabha Basu, Sujoy Nath +1

Human cognition, driven by complex neurochemical processes, oscillates between imagination and reality and learns to self-correct whenever such subtle drifts lead to hallucinations…

cs.CL2025

HalluShift++: Bridging Language and Vision through Internal Representation Shifts for Hierarchical Hallucinations in MLLMs

Sujoy Nath, Arkaprabha Basu, Sharanya Dasgupta +1

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language understanding tasks. While these models often produce linguistically coherent…

cs.AI20252 cited

A Systematic Review of Digital Twin-Driven Predictive Maintenance in Industrial Engineering: Taxonomy, Architectural Elements, and Future Research Directions

Leila Ismail, Abdelmoneim Abdelmoti, Arkaprabha Basu +2

With the increasing complexity of industrial systems, there is a pressing need for predictive maintenance to avoid costly downtime and disastrous outcomes that could be life-threat…

cs.CV2025

Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision

Arkaprabha Basu

Modern digitised approaches have dramatically changed the preservation and restoration of cultural treasures, integrating computer scientists into multidisciplinary projects with e…

cs.CL2025

HalluShift: Measuring Distribution Shifts towards Hallucination Detection in LLMs

Sharanya Dasgupta, Sujoy Nath, Arkaprabha Basu +2

Large Language Models (LLMs) have recently garnered widespread attention due to their adeptness at generating innovative responses to the given prompts across a multitude of domain…

stat.ML2024

On Robust Cross Domain Alignment

Anish Chakrabarty, Arkaprabha Basu, Swagatam Das

The Gromov-Wasserstein (GW) distance is an effective measure of alignment between distributions supported on distinct ambient spaces. Calculating essentially the mutual departure f…