most citedA Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

123 citations · 158 across the 8 of their papers we have counts for

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8 papers

cs.CL20241 cited

FACTOID: FACtual enTailment fOr hallucInation Detection

Vipula Rawte, S. M Towhidul Islam Tonmoy, Krishnav Rajbangshi +4

The widespread adoption of Large Language Models (LLMs) has facilitated numerous benefits. However, hallucination is a significant concern. In response, Retrieval Augmented Generat…

cs.CL20241 cited

"Sorry, Come Again?" Prompting -- Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing

Vipula Rawte, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +4

Hallucination has emerged as the most vulnerable aspect of contemporary Large Language Models (LLMs). In this paper, we introduce the Sorry, Come Again (SCA) prompting, aimed to av…

cs.CL20246 cited

The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey

Saurav Pawar, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +3

The advent of Large Language Models (LLMs) represents a notable breakthrough in Natural Language Processing (NLP), contributing to substantial progress in both text comprehension a…

cs.CL2024123 cited

A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain +4

As Large Language Models (LLMs) continue to advance in their ability to write human-like text, a key challenge remains around their tendency to hallucinate generating content that…

cs.CL2023

Counter Turing Test CT^2: AI-Generated Text Detection is Not as Easy as You May Think -- Introducing AI Detectability Index

Megha Chakraborty, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +9

With the rise of prolific ChatGPT, the risk and consequences of AI-generated text has increased alarmingly. To address the inevitable question of ownership attribution for AI-gener…

cs.AI202311 cited

The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

Vipula Rawte, Swagata Chakraborty, Agnibh Pathak +5

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has paralle…