Dennis Ulmer

According to our database1, Dennis Ulmer authored at least 22 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
On Uncertainty In Natural Language Processing.
CoRR, 2024

Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk.
CoRR, 2024

Non-Exchangeable Conformal Risk Control.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Non-Exchangeable Conformal Language Generation with Nearest Neighbors.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Calibrating Large Language Models Using Their Generations Only.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
A taxonomy and review of generalization research in NLP.
Nat. Mac. Intell., October, 2023

Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation.
Trans. Mach. Learn. Res., 2023

Uncertainty in Natural Language Generation: From Theory to Applications.
CoRR, 2023

2022
State-of-the-art generalisation research in NLP: a taxonomy and review.
CoRR, 2022

deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks.
CoRR, 2022

Experimental Standards for Deep Learning Research: A Natural Language Processing Perspective.
CoRR, 2022

Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Experimental Standards for Deep Learning in Natural Language Processing Research.
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.
CoRR, 2021

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

Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection.
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.
CoRR, 2020

Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data.
Proceedings of the Machine Learning for Health Workshop, 2020

2019
Assessing Incrementality in Sequence-to-Sequence Models.
Proceedings of the 4th Workshop on Representation Learning for NLP, 2019

On the Realization of Compositionality in Neural Networks.
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019


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