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Dennis Ulmer
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2020 – today
- 2024
- [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 - [i16]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) - [i15]Dennis Ulmer, Chrysoula Zerva
, André F. T. Martins:
Non-Exchangeable Conformal Language Generation with Nearest Neighbors. CoRR abs/2402.00707 (2024) - [i14]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) - [i13]Dennis Ulmer, Martin Gubri
, Hwaran Lee, Sangdoo Yun, Seong Joon Oh:
Calibrating Large Language Models Using Their Generations Only. CoRR abs/2403.05973 (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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last updated on 2024-08-08 20:12 CEST by the dblp team
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