On the Realization of Compositionality in Neural Networks. - Joris Baan; Jana Leible; Mitja Nikolaus; David Rau; Dennis Ulmer; Tim Baumgärtner; Dieuwke Hupkes; Elia Bruni (BlackboxNLP@ACL, 2019)

Assessing Incrementality in Sequence-to-Sequence Models. - Dennis Ulmer; Dieuwke Hupkes; Elia Bruni (RepL4NLP@ACL, 2019)

Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data. - Dennis Ulmer; Lotta Meijerink; Giovanni Cinà (ML4H@NeurIPS, 2020)

Know Your Limits: Monotonicity & Softmax Make Neural Classifiers Overconfident on OOD Data. - Dennis Ulmer; Giovanni Cinà (CoRR, 2020)

Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection. - Dennis Ulmer; Giovanni Cinà (UAI, 2021)

Recoding latent sentence representations - Dynamic gradient-based activation modification in RNNs. - Dennis Ulmer (CoRR, 2021)

A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation. - Dennis Ulmer (CoRR, 2021)

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 (EMNLP (Findings), 2022)

Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity. - Dennis Ulmer; Jes Frellsen; Christian Hardmeier (EMNLP (Findings), 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)

deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks. - Dennis Ulmer; Christian Hardmeier; Jes Frellsen (CoRR, 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 001; Karim Lasri; Naomi Saphra; Arabella Sinclair; Dennis Ulmer; Florian Schottmann; et al. (CoRR, 2022)

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)

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)

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; et al. (Nat. Mac. Intell., 2023)

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification. - Martin Gubri; Dennis Ulmer; Hwaran Lee; Sangdoo Yun; Seong Joon Oh (ACL (Findings), 2024)

Calibrating Large Language Models Using Their Generations Only. - Dennis Ulmer; Martin Gubri; Hwaran Lee; Sangdoo Yun; Seong Joon Oh (ACL (1), 2024)

Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk. - Dennis Ulmer; Elman Mansimov; Kaixiang Lin; Lijia Sun; Xibin Gao; Yi Zhang (ACL (Findings), 2024)

Non-Exchangeable Conformal Language Generation with Nearest Neighbors. - Dennis Ulmer; Chrysoula Zerva; André F. T. Martins (EACL (Findings), 2024)

Non-Exchangeable Conformal Risk Control. - António Farinhas; Chrysoula Zerva; Dennis Ulmer; André F. T. Martins (ICLR, 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)

On Uncertainty In Natural Language Processing. - Dennis Ulmer (CoRR, 2024)

Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing. - Dennis Ulmer; Alexandra Lorson; Ivan Titov; Christian Hardmeier (CoRR, 2025)