Daniel Varab

11 papers A* 1B 1Journal 4Unranked 5
YearRankTypeTitle / Venue / Authors
2024 J jnl
With Good MT There is No Need For End-to-End: A Case for Translate-then-Summarize Cross-lingual Summarization.
CoRR
Daniel Varab, Christian Hardmeier
2023 — conf
Abstractive Summarizers are Excellent Extractive Summarizers.
ACL (2)
Daniel Varab, Yumo Xu
2022 J jnl
Experimental Standards for Deep Learning Research: A Natural Language Processing Perspective.
CoRR
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Christian Hardmeier, Barbara Plank
2022 — conf
Experimental Standards for Deep Learning in Natural Language Processing Research.
EMNLP (Findings)
Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Rob van der Goot, Christian Hardmeier, Barbara Plank
2021 — conf
MassiveSumm: a very large-scale, very multilingual, news summarisation dataset.
EMNLP (1)
Daniel Varab, Natalie Schluter
2021 — conf
The Danish Gigaword Corpus.
NoDaLiDa
Leon Derczynski, Manuel R. Ciosici, Rebekah Baglini, Morten H. Christiansen, Jacob Aarup Dalsgaard, Riccardo Fusaroli, Peter Juel Henrichsen, Rasmus Hvingelby, Andreas Kirkedal, Alex Speed Kjeldsen, Claus Ladefoged, Finn Årup Nielsen, Jens Madsen, Malte Lau Petersen, Jonathan Hvithamar Rystrøm, Daniel Varab
2020 B conf
DaNewsroom: A Large-scale Danish Summarisation Dataset.
LREC
Daniel Varab, Natalie Schluter
2020 J jnl
The Danish Gigaword Project.
CoRR
Leon Derczynski, Rebekah Baglini, Morten H. Christiansen, Manuel R. Ciosici, Jacob Aarup Dalsgaard, Riccardo Fusaroli, Peter Juel Henrichsen, Rasmus Hvingelby, Andreas Kirkedal, Alex Speed Kjeldsen, Claus Ladefoged, Finn Årup Nielsen, Malte Lau Petersen, Jonathan Hvithamar Rystrøm, Daniel Varab
2019 — conf
UniParse: A universal graph-based parsing toolkit.
NODALIDA
Daniel Varab, Natalie Schluter
2018 J jnl
UniParse: A universal graph-based parsing toolkit.
CoRR
Daniel Varab, Natalie Schluter
2018 A* conf
When data permutations are pathological: the case of neural natural language inference.
EMNLP
Natalie Schluter, Daniel Varab