387 citations · 592 across the 31 of their papers we have counts for
9 papers · 1 filter
Behavioral gender differences are reinforced during the COVID-19 crisis
Tobias Reisch, Georg Heiler, Jan Hurt +3
Behavioral gender differences are known to exist for a wide range of human activities including the way people communicate, move, provision themselves, or organize leisure activiti…
Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
Sebastian Hofstätter, Sophia Althammer, Michael Schröder +2
Retrieval and ranking models are the backbone of many applications such as web search, open domain QA, or text-based recommender systems. The latency of neural ranking models at qu…
The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data
Georg Heiler, Allan Hanbury, Peter Filzmoser
Evaluating relative changes leads to additional insights which would remain hidden when only evaluating absolute changes. We analyze a dataset describing mobility of mobile phones…
Country-wide mobility changes observed using mobile phone data during COVID-19 pandemic
Georg Heiler, Tobias Reisch, Jan Hurt +4
In March 2020, the Austrian government introduced a widespread lock-down in response to the COVID-19 pandemic. Based on subjective impressions and anecdotal evidence, Austrian publ…
Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering
Sebastian Hofstätter, Markus Zlabinger, Mete Sertkan +2
There are many existing retrieval and question answering datasets. However, most of them either focus on ranked list evaluation or single-candidate question answering. This divide…
DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts
Markus Zlabinger, Marta Sabou, Sebastian Hofstätter +2
The success of crowdsourcing based annotation of text corpora depends on ensuring that crowdworkers are sufficiently well-trained to perform the annotation task accurately. To that…
Local Self-Attention over Long Text for Efficient Document Retrieval
Sebastian Hofstätter, Hamed Zamani, Bhaskar Mitra +2
Neural networks, particularly Transformer-based architectures, have achieved significant performance improvements on several retrieval benchmarks. When the items being retrieved ar…
Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking
Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury
Search engines operate under a strict time constraint as a fast response is paramount to user satisfaction. Thus, neural re-ranking models have a limited time-budget to re-rank doc…
DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations
Markus Zlabinger, Sebastian Hofstätter, Navid Rekabsaz +1
The effective extraction of ranked disease-symptom relationships is a critical component in various medical tasks, including computer-assisted medical diagnosis or the discovery of…