Ayush M
ayushbits
AI Research@NVIDIA. Prev: Completed PhD from CSE@IITB. Passionate about Machine Learning.
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This repository contains scripts and guides presented during multiple LLM development sessions by me.
Source code and dataset for the paper 'Saamayik: A Benchmark and Dataset for English-Sanskrit Translation'
Source and Data of our EMNLP Paper 'A Benchmark and Dataset for Post-OCR text correction in Sanskrit'
Source code of our ACL 2022 paper 'Learning to robustly aggregate labeling functions for semi-supervised data programming'
This repository contains source code of our ACL 2021 paper **Data Programming using Semi-Supervision and Subset Selection**
Benchmark to evaluate graduate level understanding of LLMs for Indian context in Hindi.
Repositories
30This repository contains scripts and guides presented during multiple LLM development sessions by me.
No description provided.
Source code and dataset for the paper 'Saamayik: A Benchmark and Dataset for English-Sanskrit Translation'
No description provided.
Benchmark to evaluate graduate level understanding of LLMs for Indian context in Hindi.
No description provided.
Co-founder at https://templesofindia.org
Source and Data of our EMNLP Paper 'A Benchmark and Dataset for Post-OCR text correction in Sanskrit'
Dictdis working on fairseq v0.12
Source code of our ACL 2022 paper 'Learning to robustly aggregate labeling functions for semi-supervised data programming'
No description provided.
No description provided.
A curated list of programmatic weak supervision papers and resources
This repository contains source code of our ACL 2021 paper **Data Programming using Semi-Supervision and Subset Selection**
No description provided.
Official style files for papers submitted to venues of the Association for Computational Linguistics
Code for graph representation learning by integrating content and structure information
SPEAR: Semi suPErvised dAta progRamming
No description provided.
LexPredict ContraxSuite
Summarize Massive Datasets using Submodular Optimization
A system for quickly generating training data with weak supervision
LexNLP by LexPredict
DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
Code of our paper "Representation Learning on Graphs by Integrating Content and Structure Information" https://ieeexplore.ieee.org/document/8711221/
Code for paper "Hierarchical Text Classification with Reinforced Label Assignment" EMNLP 2019
A Tutorial about Programming for Natural Language Processing
Simple Open-Source CMS for designers
JSPrintSetup Firefox addon