241 citations · 686 across the 25 of their papers we have counts for
6 papers · 1 filter
Overcoming low-utility facets for complex answer retrieval
Sean MacAvaney, Andrew Yates, Arman Cohan +4
Many questions cannot be answered simply; their answers must include numerous nuanced details and additional context. Complex Answer Retrieval (CAR) is the retrieval of answers to…
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval
Canjia Li, Yingfei Sun, Ben He +5
Pseudo-relevance feedback (PRF) is commonly used to boost the performance of traditional information retrieval (IR) models by using top-ranked documents to identify and weight new…
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning
Kashyap Popat, Subhabrata Mukherjee, Andrew Yates +1
Misinformation such as fake news is one of the big challenges of our society. Research on automated fact-checking has proposed methods based on supervised learning, but these appro…
SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions
Arman Cohan, Bart Desmet, Andrew Yates +3
Mental health is a significant and growing public health concern. As language usage can be leveraged to obtain crucial insights into mental health conditions, there is a need for l…
RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses
Sean MacAvaney, Bart Desmet, Arman Cohan +4
Self-reported diagnosis statements have been widely employed in studying language related to mental health in social media. However, existing research has largely ignored the tempo…
Characterizing Question Facets for Complex Answer Retrieval
Sean MacAvaney, Andrew Yates, Arman Cohan +4
Complex answer retrieval (CAR) is the process of retrieving answers to questions that have multifaceted or nuanced answers. In this work, we present two novel approaches for CAR ba…