ABEX: Data Augmentation for Low-Resource NLU via Expanding Abstract Descriptions

1 code implementation • 6 Jun 2024 • Sreyan Ghosh, Utkarsh Tyagi, Sonal Kumar, C. K. Evuru, S Ramaneswaran, S Sakshi, Dinesh Manocha

We present ABEX, a novel and effective generative data augmentation methodology for low-resource Natural Language Understanding (NLU) tasks.

Do Vision-Language Models Understand Compound Nouns?

1 code implementation • 30 Mar 2024 • Sonal Kumar, Sreyan Ghosh, S Sakshi, Utkarsh Tyagi, Dinesh Manocha

We curate Compun, a novel benchmark with 400 unique and commonly used CNs, to evaluate the effectiveness of VLMs in interpreting CNs.

Image Retrieval Language Modelling +2

DALE: Generative Data Augmentation for Low-Resource Legal NLP

1 code implementation • 24 Oct 2023 • Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar, S Ramaneswaran, S Sakshi, Utkarsh Tyagi, Dinesh Manocha

We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP.

Data Augmentation Decoder +3

M-MELD: A Multilingual Multi-Party Dataset for Emotion Recognition in Conversations

1 code implementation • 31 Mar 2022 • Sreyan Ghosh, S Ramaneswaran, Utkarsh Tyagi, Harshvardhan Srivastava, Samden Lepcha, S Sakshi, Dinesh Manocha

Expression of emotions is a crucial part of daily human communication.

Emotion Recognition

DeToxy: A Large-Scale Multimodal Dataset for Toxicity Classification in Spoken Utterances

1 code implementation • 14 Oct 2021 • Sreyan Ghosh, Samden Lepcha, S Sakshi, Rajiv Ratn Shah, S. Umesh

We believe that our dataset would act as a benchmark for the relatively new and un-explored Spoken Language Processing task of detecting toxicity from spoken utterances and boost further research in this space.