2 citations · 4 across the 4 of their papers we have counts for
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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…
A Little Pretraining Goes a Long Way: A Case Study on Dependency Parsing Task for Low-resource Morphologically Rich Languages
Jivnesh Sandhan, Amrith Krishna, Ashim Gupta +2
Neural dependency parsing has achieved remarkable performance for many domains and languages. The bottleneck of massive labeled data limits the effectiveness of these approaches fo…
Evaluating Neural Morphological Taggers for Sanskrit
Ashim Gupta, Amrith Krishna, Pawan Goyal +1
Neural sequence labelling approaches have achieved state of the art results in morphological tagging. We evaluate the efficacy of four standard sequence labelling models on Sanskri…
Neural Approaches for Data Driven Dependency Parsing in Sanskrit
Amrith Krishna, Ashim Gupta, Deepak Garasangi +3
Data-driven approaches for dependency parsing have been of great interest in Natural Language Processing for the past couple of decades. However, Sanskrit still lacks a robust pure…