most citedGuardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM)

18 citations

5 papers

cs.SE2026

Building an Open AIBOM Standard in the Wild

Gopi Krishnan Rajbahadur, Keheliya Gallaba, Elyas Rashno +4

Modern software engineering increasingly relies on open, community-driven standards, yet how such standards are created in fast-evolving domains like AI-powered systems remains und…

cs.DC20264 cited

Push Down Optimization for Distributed Multi Cloud Data Integration

Ravi Kiran Kodali, Vinoth Punniyamoorthy, Akash Kumar Agarwal +5

Enterprises increasingly adopt multi cloud architectures to take advantage of diverse database engines, regional availability, and cost models. In these environments, ETL pipelines…

cs.AI20265 cited

Cognitive Platform Engineering for Autonomous Cloud Operations

Vinoth Punniyamoorthy, Nitin Saksena, Srivenkateswara Reddy Sankiti +4

Modern DevOps practices have accelerated software delivery through automation, CI/CD pipelines, and observability tooling,but these approaches struggle to keep pace with the scale…

cs.CR202618 cited

Guardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM)

Anjanava Biswas, Wrick Talukdar

The AI era has ushered in Large Language Models (LLM) to the technological forefront, which has been much of the talk in 2023, and is likely to remain as such for many years to com…

cs.CR20263 cited

AI-Powered Algorithms for the Prevention and Detection of Computer Malware Infections

Rakesh Keshava, Sathish Kuppan Pandurangan, M. Sakthivanitha +3

The rise in frequency and complexity of malware attacks are viewed as a major threat to modern digital infrastructure, which means that traditional signature-based detection method…