TarGEN: Targeted Data Generation with Large Language Models

1 code implementation • 27 Oct 2023 • Himanshu Gupta, Kevin Scaria, Ujjwala Anantheswaran, Shreyas Verma, Mihir Parmar, Saurabh Arjun Sawant, Chitta Baral, Swaroop Mishra

Finally, when pre-finetuned on our synthetic SuperGLUE dataset, T5-3B yields impressive results on the OpenLLM leaderboard, surpassing the model trained on the Self-Instruct dataset by 4. 14% points.

Instruction Tuned Models are Quick Learners

1 code implementation • 17 May 2023 • Himanshu Gupta, Saurabh Arjun Sawant, Swaroop Mishra, Mutsumi Nakamura, Arindam Mitra, Santosh Mashetty, Chitta Baral

In the MTL setting, an instruction tuned model trained on only 6% of downstream training data achieve SOTA, while using 100% of the training data results in a 3. 69% points improvement (ROUGE-L 74. 68) over the previous SOTA.

In-Context Learning Multi-Task Learning +1

InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis

1 code implementation • 16 Feb 2023 • Kevin Scaria, Himanshu Gupta, Siddharth Goyal, Saurabh Arjun Sawant, Swaroop Mishra, Chitta Baral

We introduce InstructABSA, an instruction learning paradigm for Aspect-Based Sentiment Analysis (ABSA) subtasks.

Aspect-Based Sentiment Analysis Aspect Extraction +2

"John is 50 years old, can his son be 65?" Evaluating NLP Models' Understanding of Feasibility

1 code implementation • 14 Oct 2022 • Himanshu Gupta, Neeraj Varshney, Swaroop Mishra, Kuntal Kumar Pal, Saurabh Arjun Sawant, Kevin Scaria, Siddharth Goyal, Chitta Baral

We show that even state-of-the-art models such as GPT-3, GPT-2, and T5 struggle to answer the feasibility questions correctly.

Binary Classification Question Answering