20 citations · 27 across the 4 of their papers we have counts for
14 papers
Empowering Active Learning to Jointly Optimize System and User Demands
Ji-Ung Lee, Christian M. Meyer, Iryna Gurevych
Existing approaches to active learning maximize the system performance by sampling unlabeled instances for annotation that yield the most efficient training. However, when active l…
When is ACL's Deadline? A Scientific Conversational Agent
Mohsen Mesgar, Paul Youssef, Lin Li +4
Our conversational agent UKP-ATHENA assists NLP researchers in finding and exploring scientific literature, identifying relevant authors, planning or post-processing conference vis…
MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
Wei Zhao, Maxime Peyrard, Fei Liu +3
A robust evaluation metric has a profound impact on the development of text generation systems. A desirable metric compares system output against references based on their semantic…
Better Rewards Yield Better Summaries: Learning to Summarise Without References
Florian Böhm, Yang Gao, Christian M. Meyer +3
Reinforcement Learning (RL) based document summarisation systems yield state-of-the-art performance in terms of ROUGE scores, because they directly use ROUGE as the rewards during…
FAMULUS: Interactive Annotation and Feedback Generation for Teaching Diagnostic Reasoning
Jonas Pfeiffer, Christian M. Meyer, Claudia Schulz +7
Our proposed system FAMULUS helps students learn to diagnose based on automatic feedback in virtual patient simulations, and it supports instructors in labeling training data. Diag…
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation
Yang Gao, Christian M. Meyer, Mohsen Mesgar +1
Document summarisation can be formulated as a sequential decision-making problem, which can be solved by Reinforcement Learning (RL) algorithms. The predominant RL paradigm for sum…