4 papers · 1 filter
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-…
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.…
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…