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ORCIDDennis Ulmer
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2020 – today
- 2024
[c11]Dennis Ulmer, Elman Mansimov, Kaixiang Lin, Lijia Sun, Xibin Gao, Yi Zhang:
Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk. ACL (Findings) 2024: 9500-9522- [c10]Martin Gubri, Dennis Ulmer, Hwaran Lee, Sangdoo Yun, Seong Joon Oh:
TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification. ACL (Findings) 2024: 11496-11517 - [c9]Dennis Ulmer, Martin Gubri, Hwaran Lee, Sangdoo Yun, Seong Joon Oh:
Calibrating Large Language Models Using Their Generations Only. ACL (1) 2024: 15440-15459 - [c8]Dennis Ulmer, Chrysoula Zerva, André F. T. Martins:
Non-Exchangeable Conformal Language Generation with Nearest Neighbors. EACL (Findings) 2024: 1909-1929 - [c7]António Farinhas, Chrysoula Zerva, Dennis Ulmer, André F. T. Martins:
Non-Exchangeable Conformal Risk Control. ICLR 2024 - [i17]Dennis Ulmer, Elman Mansimov, Kaixiang Lin, Justin Sun, Xibin Gao, Yi Zhang:
Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk. CoRR abs/2401.05033 (2024) - [i16]Dennis Ulmer, Chrysoula Zerva
, André F. T. Martins:
Non-Exchangeable Conformal Language Generation with Nearest Neighbors. CoRR abs/2402.00707 (2024) - [i15]Martin Gubri, Dennis Ulmer, Hwaran Lee, Sangdoo Yun, Seong Joon Oh:
TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification. CoRR abs/2402.12991 (2024) - [i14]Dennis Ulmer, Martin Gubri, Hwaran Lee, Sangdoo Yun, Seong Joon Oh:
Calibrating Large Language Models Using Their Generations Only. CoRR abs/2403.05973 (2024) - [i13]Dennis Ulmer:
On Uncertainty In Natural Language Processing. CoRR abs/2410.03446 (2024) - 2023
- [j2]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:
A taxonomy and review of generalization research in NLP. Nat. Mac. Intell. 5(10): 1161-1174 (2023) - [j1]Dennis Ulmer, Christian Hardmeier, Jes Frellsen:
Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [i12]Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer, Haau-Sing Li, Raquel Fernández, Barbara Plank, Rico Sennrich, Chrysoula Zerva, Wilker Aziz:
Uncertainty in Natural Language Generation: From Theory to Applications. CoRR abs/2307.15703 (2023) - [i11]António Farinhas, Chrysoula Zerva, Dennis Ulmer, André F. T. Martins:
Non-Exchangeable Conformal Risk Control. CoRR abs/2310.01262 (2023) - 2022
- [c6]Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Rob van der Goot, Christian Hardmeier, Barbara Plank:
Experimental Standards for Deep Learning in Natural Language Processing Research. EMNLP (Findings) 2022: 2673-2692 - [c5]Dennis Ulmer, Jes Frellsen, Christian Hardmeier:
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity. EMNLP (Findings) 2022: 2707-2735 - [i10]Dennis Ulmer, Elisa Bassignana, Max Müller-Eberstein, Daniel Varab, Mike Zhang, Christian Hardmeier, Barbara Plank:
Experimental Standards for Deep Learning Research: A Natural Language Processing Perspective. CoRR abs/2204.06251 (2022) - [i9]Dennis Ulmer, Christian Hardmeier, Jes Frellsen:
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks. CoRR abs/2204.06815 (2022) - [i8]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:
State-of-the-art generalisation research in NLP: a taxonomy and review. CoRR abs/2210.03050 (2022) - [i7]Dennis Ulmer, Jes Frellsen, Christian Hardmeier:
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity. CoRR abs/2210.15452 (2022) - 2021
- [c4]Dennis Ulmer, Giovanni Cinà:
Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection. UAI 2021: 1766-1776 - [i6]Dennis Ulmer:
Recoding latent sentence representations - Dynamic gradient-based activation modification in RNNs. CoRR abs/2101.00674 (2021) - [i5]Dennis Ulmer:
A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation. CoRR abs/2110.03051 (2021) - 2020
- [c3]Dennis Ulmer, Lotta Meijerink, Giovanni Cinà:
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data. ML4H@NeurIPS 2020: 341-354 - [i4]Dennis Ulmer, Lotta Meijerink, Giovanni Ciná:
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data. CoRR abs/2011.03274 (2020) - [i3]Dennis Ulmer, Giovanni Cinà:
Know Your Limits: Monotonicity & Softmax Make Neural Classifiers Overconfident on OOD Data. CoRR abs/2012.05329 (2020)
2010 – 2019
- 2019
- [c2]Joris Baan, Jana Leible, Mitja Nikolaus, David Rau, Dennis Ulmer, Tim Baumgärtner, Dieuwke Hupkes, Elia Bruni:
On the Realization of Compositionality in Neural Networks. BlackboxNLP@ACL 2019: 127-137 - [c1]Dennis Ulmer, Dieuwke Hupkes, Elia Bruni:
Assessing Incrementality in Sequence-to-Sequence Models. RepL4NLP@ACL 2019: 209-217 - [i2]Joris Baan, Jana Leible, Mitja Nikolaus, David Rau, Dennis Ulmer, Tim Baumgärtner, Dieuwke Hupkes, Elia Bruni:
On the Realization of Compositionality in Neural Networks. CoRR abs/1906.01634 (2019) - [i1]Dennis Ulmer, Dieuwke Hupkes, Elia Bruni:
Assessing incrementality in sequence-to-sequence models. CoRR abs/1906.03293 (2019)
Coauthor Index
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