18 citations · 40 across the 11 of their papers we have counts for
14 papers
Cultural Re-contextualization of Fairness Research in Language Technologies in India
Shaily Bhatt, Sunipa Dev, Partha Talukdar +2
Recent research has revealed undesirable biases in NLP data and models. However, these efforts largely focus on social disparities in the West, and are not directly portable to oth…
UGIF: UI Grounded Instruction Following
Sagar Gubbi Venkatesh, Partha Talukdar, Srini Narayanan
Smartphone users often find it difficult to navigate myriad menus to perform common tasks such as "How to block calls from unknown numbers?". Currently, help documents with step-by…
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs
Aditya Sharma, Apoorv Saxena, Chitrank Gupta +3
Recent years have witnessed much interest in temporal reasoning over knowledge graphs (KG) for complex question answering (QA), but there remains a substantial gap in human capabil…
Re-contextualizing Fairness in NLP: The Case of India
Shaily Bhatt, Sunipa Dev, Partha Talukdar +2
Recent research has revealed undesirable biases in NLP data and models. However, these efforts focus on social disparities in West, and are not directly portable to other geo-cultu…
Evaluating the Diversity, Equity and Inclusion of NLP Technology: A Case Study for Indian Languages
Simran Khanuja, Sebastian Ruder, Partha Talukdar
In order for NLP technology to be widely applicable, fair, and useful, it needs to serve a diverse set of speakers across the world's languages, be equitable, i.e., not unduly bias…
OKGIT: Open Knowledge Graph Link Prediction with Implicit Types
Chandrahas, Partha Pratim Talukdar
Open Knowledge Graphs (OpenKG) refer to a set of (head noun phrase, relation phrase, tail noun phrase) triples such as (tesla, return to, new york) extracted from a corpus using Op…
MergeDistill: Merging Pre-trained Language Models using Distillation
Simran Khanuja, Melvin Johnson, Partha Talukdar
Pre-trained multilingual language models (LMs) have achieved state-of-the-art results in cross-lingual transfer, but they often lead to an inequitable representation of languages d…
Reordering Examples Helps during Priming-based Few-Shot Learning
Sawan Kumar, Partha Talukdar
The ability to learn from limited data, or few-shot learning, is a desirable and often critical requirement for NLP systems. While many existing methods do poorly at learning from…
Question Answering Over Temporal Knowledge Graphs
Apoorv Saxena, Soumen Chakrabarti, Partha Talukdar
Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs by providing temporal scopes (start and end times) on each edge in the KG. While Question Answering over KG…
Higher-order Relation Schema Induction using Tensor Factorization with Back-off and Aggregation
Madhav Nimishakavi, Partha Talukdar
Relation Schema Induction (RSI) is the problem of identifying type signatures of arguments of relations from unlabeled text. Most of the previous work in this area have focused onl…
KGEval: Estimating Accuracy of Automatically Constructed Knowledge Graphs
Prakhar Ojha, Partha Talukdar
Automatic construction of large knowledge graphs (KG) by mining web-scale text datasets has received considerable attention recently. Estimating accuracy of such automatically cons…
Relation Schema Induction using Tensor Factorization with Side Information
Madhav Nimishakavi, Uday Singh Saini, Partha Talukdar
Given a set of documents from a specific domain (e.g., medical research journals), how do we automatically build a Knowledge Graph (KG) for that domain? Automatic identification of…
Want Answers? A Reddit Inspired Study on How to Pose Questions
Danish, Yogesh Dahiya, Partha Talukdar
Questions form an integral part of our everyday communication, both offline and online. Getting responses to our questions from others is fundamental to satisfying our information…
Seeing the Forest through the Trees: Adaptive Local Exploration of Large Graphs
Robert Pienta, Zhiyuan Lin, Minsuk Kahng +5
Visualization is a powerful paradigm for exploratory data analysis. Visualizing large graphs, however, often results in a meaningless hairball. In this paper, we propose a differen…