7 citations · 16 across the 9 of their papers we have counts for
10 papers
Same Meaning, Different Scores: Lexical and Syntactic Sensitivity in LLM Evaluation
Bogdan Kostić, Conor Fallon, Julian Risch +1
The rapid advancement of Large Language Models (LLMs) has established standardized evaluation benchmarks as the primary instrument for model comparison. Yet, their reliability is i…
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Jonas Golde, Patrick Haller, Felix Hamborg +2
Most NLP tasks are modeled as supervised learning and thus require labeled training data to train effective models. However, manually producing such data at sufficient quality and…
Pseudo-Labels Are All You Need
Bogdan Kostić, Mathis Lucka, Julian Risch
Automatically estimating the complexity of texts for readers has a variety of applications, such as recommending texts with an appropriate complexity level to language learners or…
Semantic Answer Similarity for Evaluating Question Answering Models
Julian Risch, Timo Möller, Julian Gutsch +1
The evaluation of question answering models compares ground-truth annotations with model predictions. However, as of today, this comparison is mostly lexical-based and therefore mi…
Multi-modal Retrieval of Tables and Texts Using Tri-encoder Models
Bogdan Kostić, Julian Risch, Timo Möller
Open-domain extractive question answering works well on textual data by first retrieving candidate texts and then extracting the answer from those candidates. However, some questio…
GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrieval
Timo Möller, Julian Risch, Malte Pietsch
A major challenge of research on non-English machine reading for question answering (QA) is the lack of annotated datasets. In this paper, we present GermanQuAD, a dataset of 13,72…