12 citations · 12 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…