25 citations · 27 across the 4 of their papers we have counts for
4 papers
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection
Sophia Althammer, Guido Zuccon, Sebastian Hofstätter +2
Search methods based on Pretrained Language Models (PLM) have demonstrated great effectiveness gains compared to statistical and early neural ranking models. However, fine-tuning P…
TripJudge: A Relevance Judgement Test Collection for TripClick Health Retrieval
Sophia Althammer, Sebastian Hofstätter, Suzan Verberne +1
Robust test collections are crucial for Information Retrieval research. Recently there is a growing interest in evaluating retrieval systems for domain-specific retrieval tasks, ho…
PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval
Sophia Althammer, Sebastian Hofstätter, Mete Sertkan +2
Dense passage retrieval (DPR) models show great effectiveness gains in first stage retrieval for the web domain. However in the web domain we are in a setting with large amounts of…
DoSSIER@COLIEE 2021: Leveraging dense retrieval and summarization-based re-ranking for case law retrieval
Sophia Althammer, Arian Askari, Suzan Verberne +1
In this paper, we present our approaches for the case law retrieval and the legal case entailment task in the Competition on Legal Information Extraction/Entailment (COLIEE) 2021.…