most citedComputational Politeness in Natural Language Processing: A Survey

25 citations · 30 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2024

From Hallucinations to Facts: Enhancing Language Models with Curated Knowledge Graphs

Ratnesh Kumar Joshi, Sagnik Sengupta, Asif Ekbal

Hallucination, a persistent challenge plaguing language models, undermines their efficacy and trustworthiness in various natural language processing endeavors by generating respons…

cs.CL2024

Strategic Prompting for Conversational Tasks: A Comparative Analysis of Large Language Models Across Diverse Conversational Tasks

Ratnesh Kumar Joshi, Priyanshu Priya, Vishesh Desai +6

Given the advancements in conversational artificial intelligence, the evaluation and assessment of Large Language Models (LLMs) play a crucial role in ensuring optimal performance…

cs.CL20241 cited

A Unified Multi-Task Learning Architecture for Hate Detection Leveraging User-Based Information

Prashant Kapil, Asif Ekbal

Hate speech, offensive language, aggression, racism, sexism, and other abusive language are common phenomena in social media. There is a need for Artificial Intelligence(AI)based i…

cs.CL2024

A Case Study on Context-Aware Neural Machine Translation with Multi-Task Learning

Ramakrishna Appicharla, Baban Gain, Santanu Pal +2

In document-level neural machine translation (DocNMT), multi-encoder approaches are common in encoding context and source sentences. Recent studies \cite{li-etal-2020-multi-encoder…

cs.CL202425 cited

Computational Politeness in Natural Language Processing: A Survey

Priyanshu Priya, Mauajama Firdaus, Asif Ekbal

Computational approach to politeness is the task of automatically predicting and generating politeness in text. This is a pivotal task for conversational analysis, given the ubiqui…

cs.CL2023

When Reviewers Lock Horn: Finding Disagreement in Scientific Peer Reviews

Sandeep Kumar, Tirthankar Ghosal, Asif Ekbal

To this date, the efficacy of the scientific publishing enterprise fundamentally rests on the strength of the peer review process. The journal editor or the conference chair primar…