5 papers
Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models
Gaurav Negi, Atul Kr. Ojha, Omnia Zayed +1
We propose a scalable method for constructing a temporal opinion knowledge base with large language models (LLMs) as automated annotators. Despite the demonstrated utility of time-…
Evaluating Text Style Transfer Evaluation: Are There Any Reliable Metrics?
Sourabrata Mukherjee, Atul Kr. Ojha, John P. McCrae +1
Text style transfer (TST) is the task of transforming a text to reflect a particular style while preserving its original content. Evaluating TST outputs is a multidimensional chall…
Are Large Language Models Actually Good at Text Style Transfer?
Sourabrata Mukherjee, Atul Kr. Ojha, Ondřej Dušek
We analyze the performance of large language models (LLMs) on Text Style Transfer (TST), specifically focusing on sentiment transfer and text detoxification across three languages:…
Multilingual Text Style Transfer: Datasets & Models for Indian Languages
Sourabrata Mukherjee, Atul Kr. Ojha, Akanksha Bansal +3
Text style transfer (TST) involves altering the linguistic style of a text while preserving its core content. This paper focuses on sentiment transfer, a popular TST subtask, acros…
Text Detoxification as Style Transfer in English and Hindi
Sourabrata Mukherjee, Akanksha Bansal, Atul Kr. Ojha +2
This paper focuses on text detoxification, i.e., automatically converting toxic text into non-toxic text. This task contributes to safer and more respectful online communication an…