Search Results for author: Lokesh Madasu

Found 4 papers, 3 papers with code

TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu

1 code implementation • 17 Apr 2024 • Gopichand Kanumolu, Lokesh Madasu, Nirmal Surange, Manish Shrivastava

We further demonstrate the impact of this work by fine-tuning various headline generation models using TeClass dataset.

Paper
Code

SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 14 Languages

2 code implementations • 13 Feb 2024 • Nedjma Ousidhoum, Shamsuddeen Hassan Muhammad, Mohamed Abdalla, Idris Abdulmumin, Ibrahim Said Ahmad, Sanchit Ahuja, Alham Fikri Aji, Vladimir Araujo, Abinew Ali Ayele, Pavan Baswani, Meriem Beloucif, Chris Biemann, Sofia Bourhim, Christine de Kock, Genet Shanko Dekebo, Oumaima Hourrane, Gopichand Kanumolu, Lokesh Madasu, Samuel Rutunda, Manish Shrivastava, Thamar Solorio, Nirmal Surange, Hailegnaw Getaneh Tilaye, Krishnapriya Vishnubhotla, Genta Winata, Seid Muhie Yimam, Saif M. Mohammad

Exploring and quantifying semantic relatedness is central to representing language.

Paper
Code

Unsupervised Approach to Evaluate Sentence-Level Fluency: Do We Really Need Reference?

no code implementations • 3 Dec 2023 • Gopichand Kanumolu, Lokesh Madasu, Pavan Baswani, Ananya Mukherjee, Manish Shrivastava

Our code and human-annotated benchmark test-set for fluency is available at https://github. com/AnanyaCoder/TextFluencyForIndicLanaguges.

Sentence Text Generation +1

Paper
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Mukhyansh: A Headline Generation Dataset for Indic Languages

1 code implementation • 29 Nov 2023 • Lokesh Madasu, Gopichand Kanumolu, Nirmal Surange, Manish Shrivastava

The task of headline generation within the realm of Natural Language Processing (NLP) holds immense significance, as it strives to distill the true essence of textual content into concise and attention-grabbing summaries.

Headline Generation

Paper
Code

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