Conference Contributions
Lower-level publication types
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Conference Paper [34966]
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Conference Poster [2349]
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Conference Proceedings [497]
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Other Conference Item [18980]
Recent Submissions
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FPGA-based real-time laser beam profiling and stabilization system for quantum simulation applications
(2023)2023 26TH EUROMICRO CONFERENCE ON DIGITAL SYSTEM DESIGN, DSD 2023Lasers are imperative in quantum simulation experiments to trap and cool atoms. With the growing complexity of experimental setups, precise control and stability of the position and exotic shape of lasers have become essential for high-fidelity operations. However, disturbances such as temperature fluctuations, mechanical vibrations, deformation of materials, and acoustic noise pose challenges to fulfill these requirements. In this paper, ...Conference Paper -
Reducing Load-Use dependency-induced performance penalty in the Open-Source RISC-V CVA6 CPU
(2023)2023 26TH EUROMICRO CONFERENCE ON DIGITAL SYSTEM DESIGN, DSD 2023Embedded CPUs play a critical role in many modern electronic devices and are commonly used in a range of applications, from IoT edge, to automotive and industrial systems. In particular, application class processors are designed to run operating systems such as Linux, providing a platform for running a broad range of software ecosystems. As such, the performance of these processors is critical for ensuring that these systems can operate ...Conference Paper -
An Ionospheric Forecasting Model Based on Transfer Learning Using High-Resolution Global Ionospheric Maps
(2024)EGUsphereOther Conference Item -
Developing an Automated Observability System for HPC: Integrating Operational and Energy Datasets
(2024)Other Conference Item -
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Data-driven subgrouping of patient trajectories with chronic diseases: Evidence from low back pain
(2024)Conference Paper -
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Modelling the mountain boundary layer: Does higher resolution improve model performance?
(2024)The horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range, where topography, land-use, and other static parameters are well-resolved. Still, models have to be evaluated over complex terrain, because it cannot be assumed that higher horizontal resolution automatically yields better model performance. In this study, we perform limited-area simulations with the ICON model across horizontal ...Other Conference Item -
Improving the planning of future track interventions using digital tools
(2024)Other Conference Item -
Non-line-of-sight GNSS Signal Classification for Urban Navigation Using Machine Learning
(2024)EGUsphereOther Conference Item -
A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1We have recently witnessed a number of impressive results on hard mathematical reasoning problems with language models. At the same time, the robustness of these models has also been called into question; recent works have shown that models can rely on shallow patterns in the problem description when generating a solution. Building on the idea of behavioral testing, we propose a novel framework, which pins down the causal effect of various ...Conference Paper -
An Ordinal Latent Variable Model of Conflict Intensity
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of '' who did what to whom '' micro-records that enable datadriven approaches to monitoring conflict. The Goldstein scale is a widely-used expert-based measure that scores events on a conflictualcooperative scale. It is based only on the action category ('' what '') and disregards ...Conference Paper -
Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1Natural language generation models reproduce and often amplify the biases present in their training data. Previous research explored using sequence-to-sequence rewriting models to transform biased model outputs (or original texts) into more gender-fair language by creating pseudo training data through linguistic rules. However, this approach is not practical for languages with more complex morphology than English. We hypothesise that ...Conference Paper -
Poor Man's Quality Estimation: Predicting Reference-Based MT MetricsWithout the Reference
(2023)17TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, EACL 2023Machine translation quality estimation (QE) predicts human judgements of a translation hypothesis without seeing the reference. Stateof-the-art QE systems based on pretrained language models have been achieving remarkable correlations with human judgements yet they are computationally heavy and require human annotations, which are slow and expensive to create. To address these limitations, we define the problem of metric estimation (ME) ...Conference Paper -
Convergence and Diversity in the Control Hierarchy
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1Weir has defined a hierarchy of language classes whose second member (L-2) is generated by tree-adjoining grammars (TAG), linear indexed grammars (LIG), combinatory categorial grammars, and head grammars. The hierarchy is obtained using the mechanism of control, and L-2 is obtained using a contextfree grammar (CFG) whose derivations are controlled by another CFG. We adapt Weir's definition of a controllable CFG to give a definition of ...Conference Paper -
Log-linear Guardedness and its Implications
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023): LONG PAPERS, VOL 1Methods for erasing human-interpretable concepts from neural representations that assume linearity have been found to be tractable and useful. However, the impact of this removal on the behavior of downstream classifiers trained on the modified representations is not fully understood. In this work, we formally define the notion of log-linear guardedness as the inability of an adversary to predict the concept directly from the representation, ...Conference Paper -
What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023): LONG PAPERS, VOL 1Moral rhetoric influences our judgement. Although social scientists recognize moral expression as domain specific, there are no systematic methods for analyzing whether a text classifier learns the domain-specific expression of moral language or not. We propose Tomea, a method to compare a supervised classifier's representation of moral rhetoric across domains. Tomea enables quantitative and qualitative comparisons of moral rhetoric via ...Conference Paper -
XDailyDialog: A Multilingual Parallel Dialogue Corpus
(2023)PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023): LONG PAPERS, VOL 1High-quality corpora are significant to the development of dialogue models. However, most existing corpora for open-domain dialogue modeling are limited to a single language. The absence of multilingual open-domain dialog corpora not only limits the research on multilingual or cross-lingual transfer learning but also hinders the development of robust open-domain dialogue systems that can be deployed in other parts of the world. In this ...Conference Paper