1 code implementation • 17 May 2023 • Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
We present a large language model fine-tuned on a diverse collection of task-specific instructions for text editing (a total of 82K instructions).
1 code implementation • ACL 2022 • Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, Dongyeop Kang
Writing is, by nature, a strategic, adaptive, and more importantly, an iterative process.
1 code implementation • In2Writing (ACL) 2022 • Wanyu Du, Zae Myung Kim, Vipul Raheja, Dhruv Kumar, Dongyeop Kang
Examining and evaluating the capability of large language models for making continuous revisions and collaborating with human writers is a critical step towards building effective writing assistants.
1 code implementation • 2 Dec 2022 • Zae Myung Kim, Wanyu Du, Vipul Raheja, Dhruv Kumar, Dongyeop Kang
Leveraging datasets from other related text editing NLP tasks, combined with the specification of editable spans, leads our system to more accurately model the process of iterative text refinement, as evidenced by empirical results and human evaluations.
1 code implementation • ACL 2020 • Dhruv Kumar, Lili Mou, Lukasz Golab, Olga Vechtomova
We present a novel iterative, edit-based approach to unsupervised sentence simplification.
Ranked #5 on Text Simplification on Newsela
1 code implementation • ACL 2021 • Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi, Keyi Tang, Chenyang Huang, Jackie Chi Kit Cheung, Simon J. D. Prince, Yanshuai Cao
This work shows that this does not always need to be the case: with proper initialization and optimization, the benefits of very deep transformers can carry over to challenging tasks with small datasets, including Text-to-SQL semantic parsing and logical reading comprehension.
1 code implementation • WS 2019 • Dhruv Kumar, Robin Cohen, Lukasz Golab
We propose an attention-based neural network approach to detect abusive speech in online social networks.
1 code implementation • 15 Nov 2023 • Jierui Li, Vipul Raheja, Dhruv Kumar
In recent times, large language models (LLMs) have shown impressive performance on various document-level tasks such as document classification, summarization, and question-answering.
1 code implementation • Findings (ACL) 2022 • Mohammad Dehghan, Dhruv Kumar, Lukasz Golab
We propose GRS: an unsupervised approach to sentence simplification that combines text generation and text revision.
1 code implementation • 16 Oct 2019 • Rishav Raj Agarwal, Dhruv Kumar, Lukasz Golab, Srinivasan Keshav
The data management challenge we address is to ensure high throughput and low latency of endorsing data access requests and granting or revoking consent.
Distributed, Parallel, and Cluster Computing
1 code implementation • 7 Feb 2024 • Bashar Alhafni, Vivek Kulkarni, Dhruv Kumar, Vipul Raheja
As the text generation capabilities of large language models become increasingly prominent, recent studies have focused on controlling particular aspects of the generated text to make it more personalized.
1 code implementation • 26 Feb 2024 • Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni, Bashar Alhafni, Dhruv Kumar
We introduce mEdIT, a multi-lingual extension to CoEdIT -- the recent state-of-the-art text editing models for writing assistance.
no code implementations • NLP4MusA 2020 • Olga Vechtomova, Gaurav Sahu, Dhruv Kumar
We present a system for generating novel lyrics lines conditioned on music audio.
no code implementations • ACL (GEM) 2021 • Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, Pawan Sasanka Ammanamanchi, Aremu Anuoluwapo, Antoine Bosselut, Khyathi Raghavi Chandu, Miruna Clinciu, Dipanjan Das, Kaustubh D. Dhole, Wanyu Du, Esin Durmus, Ondřej Dušek, Chris Emezue, Varun Gangal, Cristina Garbacea, Tatsunori Hashimoto, Yufang Hou, Yacine Jernite, Harsh Jhamtani, Yangfeng Ji, Shailza Jolly, Mihir Kale, Dhruv Kumar, Faisal Ladhak, Aman Madaan, Mounica Maddela, Khyati Mahajan, Saad Mahamood, Bodhisattwa Prasad Majumder, Pedro Henrique Martins, Angelina McMillan-Major, Simon Mille, Emiel van Miltenburg, Moin Nadeem, Shashi Narayan, Vitaly Nikolaev, Rubungo Andre Niyongabo, Salomey Osei, Ankur Parikh, Laura Perez-Beltrachini, Niranjan Ramesh Rao, Vikas Raunak, Juan Diego Rodriguez, Sashank Santhanam, João Sedoc, Thibault Sellam, Samira Shaikh, Anastasia Shimorina, Marco Antonio Sobrevilla Cabezudo, Hendrik Strobelt, Nishant Subramani, Wei Xu, Diyi Yang, Akhila Yerukola, Jiawei Zhou
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on Extreme Summarization on GEM-XSum
Abstractive Text Summarization Cross-Lingual Abstractive Summarization +5
no code implementations • 3 Jun 2021 • Olga Vechtomova, Gaurav Sahu, Dhruv Kumar
We describe a real-time system that receives a live audio stream from a jam session and generates lyric lines that are congruent with the live music being played.
no code implementations • 28 Apr 2023 • Ishika Joshi, Ritvik Budhiraja, Harshal Dev, Jahnvi Kadia, M. Osama Ataullah, Sayan Mitra, Dhruv Kumar, Harshal D. Akolekar
ChatGPT is an AI language model developed by OpenAI that can understand and generate human-like text.
no code implementations • 19 Sep 2023 • Ishika Joshi, Ritvik Budhiraja, Pranav Deepak Tanna, Lovenya Jain, Mihika Deshpande, Arjun Srivastava, Srinivas Rallapalli, Harshal D Akolekar, Jagat Sesh Challa, Dhruv Kumar
The rise in popularity of Large Language Models (LLMs) has prompted discussions in academic circles, with students exploring LLM-based tools for coursework inquiries and instructors exploring them for teaching and research.
no code implementations • 24 Oct 2023 • Dhruv Kumar, Vipul Raheja, Alice Kaiser-Schatzlein, Robyn Perry, Apurva Joshi, Justin Hugues-Nuger, Samuel Lou, Navid Chowdhury
We present Speakerly, a new real-time voice-based writing assistance system that helps users with text composition across various use cases such as emails, instant messages, and notes.
no code implementations • 16 Nov 2023 • Ishika Joshi, Ritvik Budhiraja, Harshal D Akolekar, Jagat Sesh Challa, Dhruv Kumar
However, our research also highlights various challenges that must be resolved for long-term acceptance of ChatGPT amongst students.
no code implementations • 12 Dec 2023 • Anishka, Atharva Mehta, Nipun Gupta, Aarav Balachandran, Dhruv Kumar, Pankaj Jalote
The TA functions which we focus on include (1) grading student code submissions, and (2) providing feedback to undergraduate students in an introductory programming course.
no code implementations • 17 Dec 2023 • Shreya Bhatia, Tarushi Gandhi, Dhruv Kumar, Pankaj Jalote
This research aims to experimentally investigate the effectiveness of LLMs, specifically exemplified by ChatGPT, for generating unit test scripts for Python programs, and how the generated test cases compare with those generated by an existing unit test generator (Pynguin).
no code implementations • 16 Dec 2023 • Shubhang Shekhar Dvivedi, Vyshnav Vijay, Sai Leela Rahul Pujari, Shoumik Lodh, Dhruv Kumar
The paper evaluates models such as GPT-3. 5, GPT-4, Bard, Llama2, and Starchat on various parameters like Accuracy, Completeness, Relevance, Understandability, Readability and Time Taken for different levels of code documentation.
no code implementations • 22 Jan 2024 • Vibhor Agarwal, Madhav Krishan Garg, Sahiti Dharmavaram, Dhruv Kumar
This study evaluates the effectiveness of various large language models (LLMs) in performing tasks common among undergraduate computer science students.