34 citations · 103 across the 67 of their papers we have counts for
8 papers · 1 filter
DS-TOD: Efficient Domain Specialization for Task Oriented Dialog
Chia-Chien Hung, Anne Lauscher, Simone Paolo Ponzetto +1
Recent work has shown that self-supervised dialog-specific pretraining on large conversational datasets yields substantial gains over traditional language modeling (LM) pretraining…
Sustainable Modular Debiasing of Language Models
Anne Lauscher, Tobias Lüken, Goran Glavaš
Unfair stereotypical biases (e.g., gender, racial, or religious biases) encoded in modern pretrained language models (PLMs) have negative ethical implications for widespread adopti…
Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biases
Tobias Walter, Celina Kirschner, Steffen Eger +3
We analyze bias in historical corpora as encoded in diachronic distributional semantic models by focusing on two specific forms of bias, namely a political (i.e., anti-communism) a…
MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting
Anne Lauscher, Brandon Ko, Bailey Kuehl +4
Citation context analysis (CCA) is an important task in natural language processing that studies how and why scholars discuss each others' work. Despite decades of study, tradition…
Scientia Potentia Est -- On the Role of Knowledge in Computational Argumentation
Anne Lauscher, Henning Wachsmuth, Iryna Gurevych +1
Despite extensive research efforts in recent years, computational argumentation (CA) remains one of the most challenging areas of natural language processing. The reason for this i…
RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models
Soumya Barikeri, Anne Lauscher, Ivan Vulić +1
Text representation models are prone to exhibit a range of societal biases, reflecting the non-controlled and biased nature of the underlying pretraining data, which consequently l…
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces
Niklas Friedrich, Anne Lauscher, Simone Paolo Ponzetto +1
Recent research efforts in NLP have demonstrated that distributional word vector spaces often encode stereotypical human biases, such as racism and sexism. With word representation…
Self-Supervised Learning for Visual Summary Identification in Scientific Publications
Shintaro Yamamoto, Anne Lauscher, Simone Paolo Ponzetto +2
Providing visual summaries of scientific publications can increase information access for readers and thereby help deal with the exponential growth in the number of scientific publ…