Language Model Pretraining and Transfer Learning for Very Low Resource Languages

no code implementations • WMT (EMNLP) 2021 • Jyotsana Khatri, Rudra Murthy, Pushpak Bhattacharyya

This paper describes our submission for the shared task on Unsupervised MT and Very Low Resource Supervised MT at WMT 2021.

Language Modelling Transfer Learning +1

Airavata: Introducing Hindi Instruction-tuned LLM

1 code implementation • 26 Jan 2024 • Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain, Aswanth Kumar M, Mohammed Safi Ur Rahman Khan, Diptesh Kanojia, Ratish Puduppully, Mitesh M. Khapra, Raj Dabre, Rudra Murthy, Anoop Kunchukuttan

We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi.

PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities

no code implementations • 13 Jan 2024 • Settaluri Lakshmi Sravanthi, Meet Doshi, Tankala Pavan Kalyan, Rudra Murthy, Pushpak Bhattacharyya, Raj Dabre

To demonstrate this fact, we release a Pragmatics Understanding Benchmark (PUB) dataset consisting of fourteen tasks in four pragmatics phenomena, namely, Implicature, Presupposition, Reference, and Deixis.

Instruction Following Multiple-choice

StarCoder: may the source be with you!

4 code implementations • 9 May 2023 • Raymond Li, Loubna Ben allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy, Jason Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries

The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15. 5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention.

8k Code Generation

HiNER: A Large Hindi Named Entity Recognition Dataset

1 code implementation • LREC 2022 • Rudra Murthy, Pallab Bhattacharjee, Rahul Sharnagat, Jyotsana Khatri, Diptesh Kanojia, Pushpak Bhattacharyya

We use different language models to perform the sequence labelling task for NER and show the efficacy of our data by performing a comparative evaluation with models trained on another dataset available for the Hindi NER task.

named-entity-recognition Named Entity Recognition +2

Cognitively Aided Zero-Shot Automatic Essay Grading

no code implementations • ICON 2020 • Sandeep Mathias, Rudra Murthy, Diptesh Kanojia, Pushpak Bhattacharyya

Automatic essay grading (AEG) is a process in which machines assign a grade to an essay written in response to a topic, called the prompt.

Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing

no code implementations • Findings of the Association for Computational Linguistics 2020 • Girishkumar Ponkiya, Rudra Murthy, Pushpak Bhattacharyya, Girish Palshikar

Our approach uses templates to prepare the input sequence for the language model.

Language Modelling Machine Translation +2

Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour

1 code implementation • Asian Chapter of the Association for Computational Linguistics 2020 • Sandeep Mathias, Rudra Murthy, Diptesh Kanojia, Abhijit Mishra, Pushpak Bhattacharyya

To demonstrate the efficacy of this multi-task learning based approach to automatic essay grading, we collect gaze behaviour for 48 essays across 4 essay sets, and learn gaze behaviour for the rest of the essays, numbering over 7000 essays.

Multi-Task Learning Named Entity Recognition (NER) +1

Judicious Selection of Training Data in Assisting Language for Multilingual Neural NER

1 code implementation • ACL 2018 • Rudra Murthy, Anoop Kunchukuttan, Pushpak Bhattacharyya

Multilingual learning for Neural Named Entity Recognition (NNER) involves jointly training a neural network for multiple languages.

Domain Adaptation Machine Translation +4