Authorship Attribution in Fan-fictional Texts given Variable Length Character and Word n-grams. - Lukas Muttenthaler; Gordon Lucas; Janek Amann (CLEF (Working Notes), 2019)

Assisted Declarative Process Creation from Natural Language Descriptions. - Hugo A. López 001; Morten Marquard; Lukas Muttenthaler; Rasmus Strømsted (EDOC Workshops, 2019)

Unsupervised Evaluation for Question Answering with Transformers. - Lukas Muttenthaler; Isabelle Augenstein; Johannes Bjerva (BlackboxNLP@EMNLP, 2020)

Human brain activity for machine attention. - Lukas Muttenthaler; Nora Hollenstein; Maria Barrett (CoRR, 2020)

Subjective Question Answering: Deciphering the inner workings of Transformers in the realm of subjectivity. - Lukas Muttenthaler (CoRR, 2020)

THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks. - Lukas Muttenthaler; Martin N. Hebart (Frontiers Neuroinformatics, 2021)

VICE: Variational Interpretable Concept Embeddings. - Lukas Muttenthaler; Charles Y. Zheng; Patrick McClure; Robert A. Vandermeulen; Martin N. Hebart; Francisco Pereira 001 (NeurIPS, 2022)

Human alignment of neural network representations. - Lukas Muttenthaler; Jonas Dippel; Lorenz Linhardt; Robert A. Vandermeulen; Simon Kornblith (ICLR, 2023)

Improving neural network representations using human similarity judgments. - Lukas Muttenthaler; Lorenz Linhardt; Jonas Dippel; Robert A. Vandermeulen; Katherine L. Hermann; Andrew K. Lampinen; Simon Kornblith (NeurIPS, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Set Learning for Accurate and Calibrated Models. - Lukas Muttenthaler; Robert A. Vandermeulen; Qiuyi Zhang 001; Thomas Unterthiner; Klaus-Robert Müller (ICLR, 2024)

When does perceptual alignment benefit vision representations? - Shobhita Sundaram; Stephanie Fu; Lukas Muttenthaler; Netanel Tamir; Lucy Chai; Simon Kornblith; Trevor Darrell; Phillip Isola (NeurIPS, 2024)

Dimensions underlying the representational alignment of deep neural networks with humans. - Florian P. Mahner; Lukas Muttenthaler; Umut Güçlü; Martin N. Hebart (CoRR, 2024)

Aligning Machine and Human Visual Representations across Abstraction Levels. - Lukas Muttenthaler; Klaus Greff; Frieda Born; Bernhard Spitzer; Simon Kornblith; Michael C. Mozer; Klaus-Robert Müller; Thomas Unterthiner; Andrew K. Lampinen (CoRR, 2024)

Training objective drives the consistency of representational similarity across datasets. - Laure Ciernik; Lorenz Linhardt; Marco Morik; Jonas Dippel; Simon Kornblith; Lukas Muttenthaler (CoRR, 2024)