26 citations · 32 across the 5 of their papers we have counts for
7 papers
Mixed Attention Transformer for Leveraging Word-Level Knowledge to Neural Cross-Lingual Information Retrieval
Zhiqi Huang, Hamed Bonab, Sheikh Muhammad Sarwar +2
Pretrained contextualized representations offer great success for many downstream tasks, including document ranking. The multilingual versions of such pretrained representations pr…
Unsupervised Domain Adaptation for Hate Speech Detection Using a Data Augmentation Approach
Sheikh Muhammad Sarwar, Vanessa Murdock
Online harassment in the form of hate speech has been on the rise in recent years. Addressing the issue requires a combination of content moderation by people, aided by automatic d…
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
Andrew Halterman, Katherine A. Keith, Sheikh Muhammad Sarwar +1
Automated event extraction in social science applications often requires corpus-level evaluations: for example, aggregating text predictions across metadata and unbiased estimates…
Semantic Driven Fielded Entity Retrieval
Shahrzad Naseri, Sheikh Muhammad Sarwar, James Allan
A common approach for knowledge-base entity search is to consider an entity as a document with multiple fields. Models that focus on matching query terms in different fields are po…
A Multi-Task Architecture on Relevance-based Neural Query Translation
Sheikh Muhammad Sarwar, Hamed Bonab, James Allan
We describe a multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query translation. The translati…
Named Entity Recognition with Extremely Limited Data
John Foley, Sheikh Muhammad Sarwar, James Allan
Traditional information retrieval treats named entity recognition as a pre-indexing corpus annotation task, allowing entity tags to be indexed and used during search. Named entity…