activity
20192025
most citedA Benchmark and Dataset for Post-OCR text correction in Sanskrit

2 citations · 3 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2025

ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification

Yashwanth M., Vaibhav Singh, Ayush Maheshwari +2

We propose ARISE, a framework that iteratively induces rules and generates synthetic data for text classification. We combine synthetic data generation and automatic rule induction…

cs.CV2023

EIGEN: Expert-Informed Joint Learning Aggregation for High-Fidelity Information Extraction from Document Images

Abhishek Singh, Venkatapathy Subramanian, Ayush Maheshwari +3

Information Extraction (IE) from document images is challenging due to the high variability of layout formats. Deep models such as LayoutLM and BROS have been proposed to address t…

cs.CL20222 cited

A Benchmark and Dataset for Post-OCR text correction in Sanskrit

Ayush Maheshwari, Nikhil Singh, Amrith Krishna +1

Sanskrit is a classical language with about 30 million extant manuscripts fit for digitisation, available in written, printed or scannedimage forms. However, it is still considered…

cs.CL2021

Rule Augmented Unsupervised Constituency Parsing

Atul Sahay, Anshul Nasery, Ayush Maheshwari +2

Recently, unsupervised parsing of syntactic trees has gained considerable attention. A prototypical approach to such unsupervised parsing employs reinforcement learning and auto-en…

cs.CL2021

Unsupervised Learning of Explainable Parse Trees for Improved Generalisation

Atul Sahay, Ayush Maheshwari, Ritesh Kumar +3

Recursive neural networks (RvNN) have been shown useful for learning sentence representations and helped achieve competitive performance on several natural language inference tasks…

cs.LG20211 cited

Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label Classification

Soumya Chatterjee, Ayush Maheshwari, Ganesh Ramakrishnan +1

We consider the problem of multi-label classification where the labels lie in a hierarchy. However, unlike most existing works in hierarchical multi-label classification, we do not…