14.11.2020
MCML at EMNLP 2020
Two Accepted Papers (2 Findings)
Findings of the Conference on Empirical Methods in Natural Language Processing, Virtual, Nov 16-20, 2020
We are happy to announce that MCML researchers have contributed a total of 2 papers to EMNLP 2020: 2 Finding papers. Congrats to our researchers!
Findings Track (2 papers)
N. Kassner • H. Schütze
BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA.
Findings @EMNLP 2020 - Findings of the Conference on Empirical Methods in Natural Language Processing. Virtual, Nov 16-20, 2020. DOI
BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA.
Findings @EMNLP 2020 - Findings of the Conference on Empirical Methods in Natural Language Processing. Virtual, Nov 16-20, 2020. DOI
M. J. Sabet • P. Dufter • F. Yvon • H. Schütze
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings.
Findings @EMNLP 2020 - Findings of the Conference on Empirical Methods in Natural Language Processing. Virtual, Nov 16-20, 2020. DOI
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings.
Findings @EMNLP 2020 - Findings of the Conference on Empirical Methods in Natural Language Processing. Virtual, Nov 16-20, 2020. DOI
#research #top-tier-work #schuetze
Related
©Terzo Algeri/Fotoatelier M/ TUM
30.10.2025
Language Shapes Gender Bias in AI Images
Alexander Fraser shows AI image generators reproduce gender stereotypes differently across languages, highlighting the need for fair multilingual AI.
20.10.2025
Björn Ommer Appointed LMU Chief AI Officer
Our PI Björn Ommer has been appointed LMU’s Chief AI Officer to strengthen AI research and collaborations.
17.10.2025
MCML at ICCV 2025
MCML researchers are represented with 28 papers at ICCV 2025 (22 Main, and 6 Workshops).
