activity
20182020
most citedA Retrospective Analysis of the Fake News Challenge Stance Detection Task

68 citations · 153 across the 11 of their papers we have counts for

collaborators
Showing 2019Show all

8 papers · 1 filter

cs.CL2019★ 1 cited

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…

cs.CL2019★ 20 cited

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…

cs.CL2019★ 8 cited

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…

cs.CL2019

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…

cs.CL2019★ 2 cited

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…

cs.CL2019

Manipulating the Difficulty of C-Tests

Ji-Ung Lee, Erik Schwan, Christian M. Meyer

We propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically. This is a crucial step towards generating learner-adaptive exerc…

cs.CL2019★ 6 cited

Preference-based Interactive Multi-Document Summarisation

Yang Gao, Christian M. Meyer, Iryna Gurevych

Interactive NLP is a promising paradigm to close the gap between automatic NLP systems and the human upper bound. Preference-based interactive learning has been successfully applie…

cs.CL2019

Analysis of Automatic Annotation Suggestions for Hard Discourse-Level Tasks in Expert Domains

Claudia Schulz, Christian M. Meyer, Jan Kiesewetter +5

Many complex discourse-level tasks can aid domain experts in their work but require costly expert annotations for data creation. To speed up and ease annotations, we investigate th…