1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
LLMs Plagiarize: Ensuring Responsible Sourcing of Large Language Model Training Data Through Knowledge Graph Comparison
Devam Mondal, Carlo Lipizzi
In light of recent legal allegations brought by publishers, newspapers, and other creators of copyrighted corpora against large language model developers who use their copyrighted…
q-bio.GN2024★ 1 cited
SeqMate: A Novel Large Language Model Pipeline for Automating RNA Sequencing
Devam Mondal, Atharva Inamdar
RNA sequencing techniques, like bulk RNA-seq and Single Cell (sc) RNA-seq, are critical tools for the biologist looking to analyze the genetic activity/transcriptome of a tissue or…
cs.CL2024
Reducing Large Language Model Bias with Emphasis on 'Restricted Industries': Automated Dataset Augmentation and Prejudice Quantification
Devam Mondal, Carlo Lipizzi
Despite the growing capabilities of large language models, there exists concerns about the biases they develop. In this paper, we propose a novel, automated mechanism for debiasing…