publications

2023

1. BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

   BigScience Workshop,  :, Teven Le Scao, and 391 more authors

   2023

2022

1. AnEMIC: A Framework for Benchmarking ICD Coding Models

   Juyong Kim, Abheesht Sharma, Suhas Shanbhogue, and 2 more authors

   In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Dec 2022

   Abs

   Diagnostic coding, or ICD coding, is the task of assigning diagnosis codes defined by the ICD (International Classification of Diseases) standard to patient visits based on clinical notes. The current process of manual ICD coding is time-consuming and often error-prone, which suggests the need for automatic ICD coding. However, despite the long history of automatic ICD coding, there have been no standardized frameworks for benchmarking ICD coding models.We open-source an easy-to-use tool named \textitAnEMIC, which provides a streamlined pipeline for preprocessing, training, and evaluating for automatic ICD coding. We correct errors in preprocessing by existing works, and provide key models and weights trained on the correctly preprocessed datasets. We also provide an interactive demo performing real-time inference from custom inputs, and visualizations drawn from explainable AI to analyze the models. We hope the framework helps move the research of ICD coding forward and helps professionals explore the potential of ICD coding. The framework and the associated code are available here.

2. Superpixel-Based Knowledge Infusion in Deep Neural Networks for Image Classification

   Gunjan Chhablani, Abheesht Sharma, Harshit Pandey, and 1 more author

   In Proceedings of the 2022 ACM Southeast Conference, Dec 2022

   Abs

   Superpixels are higher-order perceptual groups of pixels in an image, often carrying much more information than the raw pixels. There is an inherent relational structure to the relationship among different superpixels of an image such as adjacent superpixels are neighbours of each other. Our interest here is to treat these relative positions of various superpixels as relational information of an image. This relational information can convey higher-order spatial information about the image, such as the relationship between superpixels representing two eyes in an image of a cat. That is, the two eyes are placed adjacent to each other in a straight line or the mouth is below the nose. Our motive in this paper is to assist computer vision models, specifically those based on Deep Neural Networks (DNNs), by incorporating this higher-order information from superpixels. We construct a hybrid model that leverages (a) Convolutional Neural Network (CNN) to deal with spatial information in an image and (b) Graph Neural Network (GNN) to deal with relational superpixel information in the image. The proposed model is learned using a generic hybrid loss function. Our experiments are extensive, and we evaluate the predictive performance of our proposed hybrid vision model on seven different image classification datasets from a variety of domains such as digit and object recognition, biometrics, medical imaging. The results demonstrate that the relational superpixel information processed by a GNN can improve the performance of a standard CNN-based vision system.

3. PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

   Stephen Bach, Victor Sanh, Zheng Xin Yong, and 24 more authors

   In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, May 2022

2021

1. Multitask Prompted Training Enables Zero-Shot Task Generalization

   Victor Sanh, Albert Webson, Colin Raffel, and 38 more authors

   CoRR, May 2021
2. DRIFT: A Toolkit for Diachronic Analysis of Scientific Literature

   Abheesht Sharma, Gunjan Chhablani, Harshit Pandey, and 1 more author

   In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Nov 2021
3. NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques

   Gunjan Chhablani, Abheesht Sharma, Harshit Pandey, and 2 more authors

   In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), Aug 2021
4. LRG at SemEval-2021 Task 4: Improving Reading Comprehension with Abstract Words using Augmentation, Linguistic Features and Voting

   Abheesht Sharma, Harshit Pandey, Gunjan Chhablani, and 2 more authors

   In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), Aug 2021
5. LRG at TREC 2020: Document Ranking with XLNet-Based Models

   Abheesht Sharma, and Harshit Pandey

   Aug 2021

2020

1. A Novel 3D-Unet Deep Learning Framework Based on High-Dimensional Bilateral Grid for Edge Consistent Single Image Depth Estimation

   Mansi Sharma, Abheesht Sharma, Kadvekar Rohit Tushar, and 1 more author

   In 2020 International Conference on 3D Immersion (IC3D), Aug 2020