Partha Talukdar

research

∙ 09/19/2023

Multimodal Modeling For Spoken Language Identification

Spoken language identification refers to the task of automatically predi...

0 Shikhar Bharadwaj, et al. ∙

research

∙ 06/07/2023

Label Aware Speech Representation Learning For Language Identification

Speech representation learning approaches for non-semantic tasks such as...

0 Shikhar Vashishth, et al. ∙

research

∙ 05/19/2023

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages

Data scarcity is a crucial issue for the development of highly multiling...

0 Sebastian Ruder, et al. ∙

research

∙ 03/22/2023

Salient Span Masking for Temporal Understanding

Salient Span Masking (SSM) has shown itself to be an effective strategy ...

0 Jeremy R. Cole, et al. ∙

research

∙ 11/21/2022

Cultural Re-contextualization of Fairness Research in Language Technologies in India

Recent research has revealed undesirable biases in NLP data and models. ...

0 Shaily Bhatt, et al. ∙

research

∙ 11/14/2022

UGIF: UI Grounded Instruction Following

New smartphone users have difficulty engaging with it and often use only...

0 Sagar Gubbi Venkatesh, et al. ∙

research

∙ 10/13/2022

Bootstrapping Multilingual Semantic Parsers using Large Language Models

Despite cross-lingual generalization demonstrated by pre-trained multili...

0 Abhijeet Awasthi, et al. ∙

research

∙ 10/12/2022

TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs

Recent years have witnessed much interest in temporal reasoning over kno...

0 Aditya Sharma, et al. ∙

research

∙ 09/25/2022

Re-contextualizing Fairness in NLP: The Case of India

Recent research has revealed undesirable biases in NLP data and models. ...

1 Shaily Bhatt, et al. ∙

research

∙ 09/14/2022

Parameter-Efficient Finetuning for Robust Continual Multilingual Learning

NLU systems deployed in the real world are expected to be regularly upda...

0 Kartikeya Badola, et al. ∙

research

∙ 05/25/2022

Evaluating Inclusivity, Equity, and Accessibility of NLP Technology: A Case Study for Indian Languages

In order for NLP technology to be widely applicable and useful, it needs...

0 Simran Khanuja, et al. ∙

research

∙ 03/03/2022

Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages

Pre-trained multilingual language models such as mBERT and XLM-R have de...

0 Vaidehi Patil, et al. ∙

research

∙ 10/27/2021

When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer

While recent work on multilingual language models has demonstrated their...

0 Ameet Deshpande, et al. ∙

research

∙ 10/14/2021

Few-shot Controllable Style Transfer for Low-Resource Settings: A Study in Indian Languages

Style transfer is the task of rewriting an input sentence into a target ...

0 Kalpesh Krishna, et al. ∙

research

∙ 09/29/2021

Multilingual Fact Linking

Knowledge-intensive NLP tasks can benefit from linking natural language ...

0 Keshav Kolluru, et al. ∙

research

∙ 06/07/2021

Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study

Recent research in multilingual language models (LM) has demonstrated th...

0 Yash Khemchandani, et al. ∙

research

∙ 06/05/2021

MergeDistill: Merging Pre-trained Language Models using Distillation

Pre-trained multilingual language models (LMs) have achieved state-of-th...

0 Simran Khanuja, et al. ∙

research

∙ 06/03/2021

Reordering Examples Helps during Priming-based Few-Shot Learning

The ability to learn from limited data, or few-shot learning, is a desir...

0 Sawan Kumar, et al. ∙

research

∙ 06/03/2021

Question Answering Over Temporal Knowledge Graphs

Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs...

0 Apoorv Saxena, et al. ∙

research

∙ 03/19/2021

MuRIL: Multilingual Representations for Indian Languages

India is a multilingual society with 1369 rationalized languages and dia...

0 Simran Khanuja, et al. ∙

research

∙ 12/26/2020

Spatial Reasoning from Natural Language Instructions for Robot Manipulation

Robots that can manipulate objects in unstructured environments and coll...

0 Sagar Gubbi Venkatesh, et al. ∙

research

∙ 05/25/2020

NILE : Natural Language Inference with Faithful Natural Language Explanations

The recent growth in the popularity and success of deep learning models ...

0 Sawan Kumar, et al. ∙

research

∙ 05/18/2020

Syntax-guided Controlled Generation of Paraphrases

Given a sentence (e.g., "I like mangoes") and a constraint (e.g., sentim...

0 Ashutosh Kumar, et al. ∙

research

∙ 11/18/2019

Improving Document Classification with Multi-Sense Embeddings

Efficient representation of text documents is an important building bloc...

0 Vivek Gupta, et al. ∙

research

∙ 11/10/2019

A Re-evaluation of Knowledge Graph Completion Methods

Knowledge Graph Completion (KGC) aims at automatically predicting missin...

1 Zhiqing Sun, et al. ∙

research

∙ 11/08/2019

Composition-based Multi-Relational Graph Convolutional Networks

Graph Convolutional Networks (GCNs) have recently been shown to be quite...

0 Shikhar Vashishth, et al. ∙

research

∙ 11/01/2019

InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

Most existing knowledge graphs suffer from incompleteness, which can be ...

30 Shikhar Vashishth, et al. ∙

research

∙ 06/27/2019

Relating Simple Sentence Representations in Deep Neural Networks and the Brain

What is the relationship between sentence representations learned by dee...

0 Sharmistha Jat, et al. ∙

research

∙ 02/01/2019

Dating Documents using Graph Convolution Networks

Document date is essential for many important tasks, such as document re...

0 Shikhar Vashishth, et al. ∙

research

∙ 02/01/2019

CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Information

Open Information Extraction (OpenIE) methods extract (noun phrase, relat...

0 Shikhar Vashishth, et al. ∙

research

∙ 01/24/2019

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning

Predicting properties of nodes in a graph is an important problem with a...

0 Shikhar Vashishth, et al. ∙

research

∙ 01/21/2019

AD3: Attentive Deep Document Dater

Knowledge of the creation date of documents facilitates several tasks su...

0 Swayambhu Nath Ray, et al. ∙

research

∙ 12/11/2018

RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

Distantly-supervised Relation Extraction (RE) methods train an extractor...

0 Shikhar Vashishth, et al. ∙

research

∙ 11/14/2018

MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction

Developing accurate, transferable and computationally inexpensive machin...

12 Soumya Sanyal, et al. ∙

research

∙ 09/12/2018

Graph Convolutional Networks based Word Embeddings

Recently, word embeddings have been widely adopted across several NLP ap...

0 Shikhar Vashishth, et al. ∙

research

∙ 09/07/2018

HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification

Graph-based semi-supervised learning (SSL) is an important learning prob...

0 Naganand Yadati, et al. ∙

research

∙ 05/29/2018

Lovasz Convolutional Networks

Semi-supervised learning on graph structured data has received significa...

0 Prateek Yadav, et al. ∙

research

∙ 04/19/2018

Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention

Relation extraction is the problem of classifying the relationship betwe...

0 Sharmistha Jat, et al. ∙

research

∙ 02/18/2018

Inductive Framework for Multi-Aspect Streaming Tensor Completion with Side Information

Low-rank tensor completion is a well-studied problem and has application...

0 Madhav Nimishakavi, et al. ∙

research

∙ 10/26/2017

CANDiS: Coupled & Attention-Driven Neural Distant Supervision

Distant Supervision for Relation Extraction uses heuristically aligned t...

0 Tushar Nagarajan, et al. ∙

research

∙ 07/06/2017

Event Schema Induction using Tensor Factorization with Back-off

The goal of Event Schema Induction(ESI) is to identify schemas of events...

0 Madhav Nimishakavi, et al. ∙

research

∙ 10/21/2016

KGEval: Estimating Accuracy of Automatically Constructed Knowledge Graphs

Automatic construction of large knowledge graphs (KG) by mining web-scal...

0 Prakhar Ojha, et al. ∙

research

∙ 05/12/2016

Relation Schema Induction using Tensor Factorization with Side Information

Given a set of documents from a specific domain (e.g., medical research ...

0 Madhav Nimishakavi, et al. ∙

research

∙ 12/06/2015

Want Answers? A Reddit Inspired Study on How to Pose Questions

Questions form an integral part of our everyday communication, both offl...

0 Danish, et al. ∙

research

∙ 09/09/2009

Interactive Data Integration through Smart Copy & Paste

In many scenarios, such as emergency response or ad hoc collaboration, i...

0 Zachary Ives, et al. ∙

Partha Talukdar

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