05.11.2021
MCML at EMNLP 2021
Three Accepted Papers (2 Main, and 1 Workshop)
Conference on Empirical Methods in Natural Language Processing, Punta Cana, Dominican Republic, Nov 07-11, 2021
We are happy to announce that MCML researchers have contributed a total of 3 papers to EMNLP 2021: 2 Main, and 1 Workshop papers. Congrats to our researchers!
Main Track (2 papers)
A. Imani • M. J. Sabet • L. K. Senel • P. Dufter • F. Yvon • H. Schütze
Graph Algorithms for Multiparallel Word Alignment.
EMNLP 2021 - Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
Graph Algorithms for Multiparallel Word Alignment.
EMNLP 2021 - Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
N. Kassner • O. Tafjord • H. Schütze • P. Clark
BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief.
EMNLP 2021 - Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
BeliefBank: Adding Memory to a Pre-Trained Language Model for a Systematic Notion of Belief.
EMNLP 2021 - Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
Workshops (1 paper)
N. Kees • M. Fromm • E. Faerman • T. Seidl
Active Learning for Argument Strength Estimation.
Insights @EMNLP 2021 - 2nd Workshop on Insights from Negative Results at the Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
Active Learning for Argument Strength Estimation.
Insights @EMNLP 2021 - 2nd Workshop on Insights from Negative Results at the Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI
Related
31.07.2026
Benedikt Wiestler: We Want to Build a Time Machine
MCML PI Benedikt Wiestler explains how AI models help to develop specific strategies in clinical therapy for brain tumor patients.
28.07.2026
Gaps in the Benchmark: Why Medical AI Fails in the Real World
MCML researchers show in Nature Health how dynamic red teaming exposes hidden weaknesses in Medical AI beyond static benchmarks.