Search Results for author:
Found 13 papers, 5 papers with code
Automated curriculum generation for Policy Gradients from Demonstrations
In this paper, we present a technique that improves the process of training an agent (using RL) for instruction following.
Unsung Challenges of Building and Deploying Language Technologies for Low Resource Language Communities
In this paper, we examine and analyze the challenges associated with developing and introducing language technologies to low-resource language communities.
GLUECoS : An Evaluation Benchmark for Code-Switched NLP
We present results on all these tasks using cross-lingual word embedding models and multilingual models.
Code-mixed parse trees and how to find them
In this paper, we explore the methods of obtaining parse trees of code-mixed sentences and analyse the obtained trees.
GLUECoS: An Evaluation Benchmark for Code-Switched NLP
We present results on all these tasks using cross-lingual word embedding models and multilingual models.
MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too
In this paper, we present our system for the SemEval 2020 task on code-mixed sentiment analysis.
GCM: A Toolkit for Generating Synthetic Code-mixed Text
Code-mixing is common in multilingual communities around the world, and processing it is challenging due to the lack of labeled and unlabeled data.
Predicting the Performance of Multilingual NLP Models
Recent advancements in NLP have given us models like mBERT and XLMR that can serve over 100 languages.
CALCS 2021 Shared Task: Machine Translation for Code-Switched Data
For the unsupervised setting, we provide the following language pairs: English and Spanish-English (Eng-Spanglish), and English and Modern Standard Arabic-Egyptian Arabic (Eng-MSAEA) in both directions.
TyDiP: A Dataset for Politeness Classification in Nine Typologically Diverse Languages
We study politeness phenomena in nine typologically diverse languages.
Textless Low-Resource Speech-to-Speech Translation With Unit Language Models
We train and evaluate our models for English-to-German, German-to-English and Marathi-to-English translation on three different domains (European Parliament, Common Voice, and All India Radio) with single-speaker synthesized speech data.
Counterfactually Probing Language Identity in Multilingual Models
We use one such technique, AlterRep, a method of counterfactual probing, to explore the internal structure of multilingual models (mBERT and XLM-R).
BERTologiCoMix: How does Code-Mixing interact with Multilingual BERT?
Models such as mBERT and XLMR have shown success in solving Code-Mixed NLP tasks even though they were not exposed to such text during pretraining.
