Dennis Ulmer

According to our database, Dennis Ulmer authored at least 20 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Calibrating Large Language Models Using Their Generations Only.

Dennis Ulmer, Martin Gubri, Hwaran Lee, Sangdoo Yun, Seong Joon Oh

CoRR, 2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification.

Martin Gubri, Dennis Ulmer, Hwaran Lee, Sangdoo Yun, Seong Joon Oh

CoRR, 2024

Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk.

Dennis Ulmer, Elman Mansimov, Kaixiang Lin, Justin Sun, Xibin Gao, Yi Zhang

CoRR, 2024

Non-Exchangeable Conformal Language Generation with Nearest Neighbors.

Dennis Ulmer, Chrysoula Zerva, André F. T. Martins

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

2023

A taxonomy and review of generalization research in NLP.

Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos E. Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin

Nat. Mac. Intell., October, 2023

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation.

Dennis Ulmer, Christian Hardmeier, Jes Frellsen

Trans. Mach. Learn. Res., 2023

Non-Exchangeable Conformal Risk Control.

António Farinhas, Chrysoula Zerva, Dennis Ulmer, André F. T. Martins

CoRR, 2023

Uncertainty in Natural Language Generation: From Theory to Applications.

Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer, Haau-Sing Li, Raquel Fernández, Barbara Plank, Rico Sennrich, Chrysoula Zerva, Wilker Aziz

CoRR, 2023

2022

State-of-the-art generalisation research in NLP: a taxonomy and review.

Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, Mikel Artetxe, Yanai Elazar, Tiago Pimentel, Christos Christodoulopoulos, Karim Lasri, Naomi Saphra, Arabella Sinclair, Dennis Ulmer, Florian Schottmann, Khuyagbaatar Batsuren, Kaiser Sun, Koustuv Sinha, Leila Khalatbari, Maria Ryskina, Rita Frieske, Ryan Cotterell, Zhijing Jin

CoRR, 2022

deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks.

Dennis Ulmer, Christian Hardmeier, Jes Frellsen

CoRR, 2022

Experimental Standards for Deep Learning Research: A Natural Language Processing Perspective.

Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Christian Hardmeier, Barbara Plank

CoRR, 2022

Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity.

Dennis Ulmer, Jes Frellsen, Christian Hardmeier

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Experimental Standards for Deep Learning in Natural Language Processing Research.

Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Rob van der Goot, Christian Hardmeier, Barbara Plank

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation.

Dennis Ulmer

CoRR, 2021

Recoding latent sentence representations - Dynamic gradient-based activation modification in RNNs.

Dennis Ulmer

CoRR, 2021

Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection.

Dennis Ulmer, Giovanni Cinà

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Know Your Limits: Monotonicity & Softmax Make Neural Classifiers Overconfident on OOD Data.

Dennis Ulmer, Giovanni Cinà

CoRR, 2020

Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data.

Dennis Ulmer, Lotta Meijerink, Giovanni Cinà

Proceedings of the Machine Learning for Health Workshop, 2020

2019

Assessing Incrementality in Sequence-to-Sequence Models.

Dennis Ulmer, Dieuwke Hupkes, Elia Bruni

Proceedings of the 4th Workshop on Representation Learning for NLP, 2019

On the Realization of Compositionality in Neural Networks.

Joris Baan, Jana Leible, Mitja Nikolaus, David Rau, Dennis Ulmer, Tim Baumgärtner, Dieuwke Hupkes, Elia Bruni

Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019