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2020 – today
- 2024
[c6]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Xavier Garcia, Daniel Cremers:
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model. ACL (1) 2024: 15660-15679- [i8]Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, Mark Ibrahim:
Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations. CoRR abs/2404.10960 (2024) - 2023
- [c5]Christian Tomani, Futa Kai Waseda, Yuesong Shen, Daniel Cremers:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. ICML 2023: 34344-34368 - [i7]Christian Tomani, Futa Waseda, Yuesong Shen, Daniel Cremers
:
Beyond In-Domain Scenarios: Robust Density-Aware Calibration. CoRR abs/2302.05118 (2023) - [i6]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Daniel Cremers:
Quality Control at Your Fingertips: Quality-Aware Translation Models. CoRR abs/2310.06707 (2023) - 2022
- [c4]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. ECCV (13) 2022: 555-569 - [c3]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? NeurIPS 2022 - [i5]Christian Tomani, Daniel Cremers:
CHALLENGER: Training with Attribution Maps. CoRR abs/2205.15094 (2022) - [i4]Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers:
What Makes Graph Neural Networks Miscalibrated? CoRR abs/2210.06391 (2022) - 2021
- [c2]Christian Tomani, Florian Buettner:
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. AAAI 2021: 9886-9896 - [c1]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-Hoc Uncertainty Calibration for Domain Drift Scenarios. CVPR 2021: 10124-10132 - [i3]Christian Tomani, Daniel Cremers, Florian Buettner:
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration. CoRR abs/2102.12182 (2021) - 2020
- [i2]Christian Tomani, Florian Buettner:
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration. CoRR abs/2012.10923 (2020) - [i1]Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem, Daniel Cremers, Florian Buettner:
Post-hoc Uncertainty Calibration for Domain Drift Scenarios. CoRR abs/2012.10988 (2020)
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