Search Results for author: S. M Towhidul Islam Tonmoy

Found 9 papers, 1 papers with code

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

no code implementations15 Jan 2024 Saurav Pawar, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Aman Chadha, Amitava Das

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

Reading Comprehension

A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

1 code implementation2 Jan 2024 S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, Amitava Das

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 appears factual but is ungrounded.

Hallucination Retrieval +1

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

no code implementations8 Oct 2023 Megha Chakraborty, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Krish Sharma, Niyar R Barman, Chandan Gupta, Shreya Gautam, Tanay Kumar, Vinija Jain, Aman Chadha, Amit P. Sheth, Amitava Das

Given this cynosural spotlight on generative AI, AI-generated text detection (AGTD) has emerged as a topic that has already received immediate attention in research, with some initial methods having been proposed, soon followed by emergence of techniques to bypass detection.

Text Detection

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

no code implementations8 Oct 2023 Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S. M Towhidul Islam Tonmoy, Aman Chadha, Amit P. Sheth, Amitava Das

Finally, to establish a method for quantifying and to offer a comparative spectrum that allows us to evaluate and rank LLMs based on their vulnerability to producing hallucinations, we propose Hallucination Vulnerability Index (HVI).

Hallucination

FACTIFY-5WQA: 5W Aspect-based Fact Verification through Question Answering

no code implementations7 May 2023 Anku Rani, S. M Towhidul Islam Tonmoy, Dwip Dalal, Shreya Gautam, Megha Chakraborty, Aman Chadha, Amit Sheth, Amitava Das

Finally, we report a baseline QA system to automatically locate those answers from evidence documents, which can serve as a baseline for future research in the field.

Fact Checking Fact Verification +3

OOG- Optuna Optimized GAN Sampling Technique for Tabular Imbalanced Malware Data

no code implementations25 Nov 2022 S. M Towhidul Islam Tonmoy, S. M Mehedi Zaman

Cyberspace occupies a large portion of people's life in the age of modern technology, and while there are those who utilize it for good, there are also those who do not.

Generative Adversarial Network

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