8 citations · 13 across the 8 of their papers we have counts for
8 papers
Shadow Unlearning: A Neuro-Semantic Approach to Fidelity-Preserving Faceless Forgetting in LLMs
Dinesh Srivasthav P, Ashok Urlana, Rahul Mishra +2
Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Right to be Forgotten'. However, many ex…
Agent Ideate: A Framework for Product Idea Generation from Patents Using Agentic AI
Gopichand Kanumolu, Ashok Urlana, Charaka Vinayak Kumar +1
Patents contain rich technical knowledge that can inspire innovative product ideas, yet accessing and interpreting this information remains a challenge. This work explores the use…
Cyber for AI at SemEval-2025 Task 4: Forgotten but Not Lost: The Balancing Act of Selective Unlearning in Large Language Models
Dinesh Srivasthav P, Bala Mallikarjunarao Garlapati
Large Language Models (LLMs) face significant challenges in maintaining privacy, ethics, and compliance, when sensitive or obsolete data must be selectively removed. Retraining the…
No LLM is Free From Bias: A Comprehensive Study of Bias Evaluation in Large Language Models
Charaka Vinayak Kumar, Ashok Urlana, Gopichand Kanumolu +2
Advancements in Large Language Models (LLMs) have increased the performance of different natural language understanding as well as generation tasks. Although LLMs have breached the…
HalluCounter: Reference-free LLM Hallucination Detection in the Wild!
Ashok Urlana, Gopichand Kanumolu, Charaka Vinayak Kumar +2
Response consistency-based, reference-free hallucination detection (RFHD) methods do not depend on internal model states, such as generation probabilities or gradients, which Grey-…
No Size Fits All: The Perils and Pitfalls of Leveraging LLMs Vary with Company Size
Ashok Urlana, Charaka Vinayak Kumar, Bala Mallikarjunarao Garlapati +2
Large language models (LLMs) are playing a pivotal role in deploying strategic use cases across a range of organizations, from large pan-continental companies to emerging startups.…
TrustAI at SemEval-2024 Task 8: A Comprehensive Analysis of Multi-domain Machine Generated Text Detection Techniques
Ashok Urlana, Aditya Saibewar, Bala Mallikarjunarao Garlapati +3
The Large Language Models (LLMs) exhibit remarkable ability to generate fluent content across a wide spectrum of user queries. However, this capability has raised concerns regardin…
LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey
Ashok Urlana, Charaka Vinayak Kumar, Ajeet Kumar Singh +3
Large language models (LLMs) have become the secret ingredient driving numerous industrial applications, showcasing their remarkable versatility across a diverse spectrum of tasks.…