Papers by Pius Von Däniken

3 papers
A Measure of the System Dependence of Automated Metrics (2025.acl-short)

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Challenge: Recent advances in machine translation evaluations are expensive and time-intensive.
Approach: They propose a method to evaluate the correlation between human and metric scores . they argue that it is equally important to ensure that metrics treat all systems fairly and consistently.
Outcome: The proposed method ignores a central requirement of the evaluation process, and ignores the need for a thorough evaluation procedure.
Favi-Score: A Measure for Favoritism in Automated Preference Ratings for Generative AI Evaluation (2024.acl-long)

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Challenge: Generative AI systems are becoming ubiquitous for all kinds of modalities . evaluation of generated outputs is increasingly difficult due to cost and complexity of human evaluations.
Approach: They propose to evaluate preference ratings on sign accuracy and favoritism . they propose to use automated metrics to assess generated outputs .
Outcome: The proposed evaluations of preference ratings rely on correlation to human judgments or sign accuracy scores, but this does not tell the whole story.
Probing the Robustness of Trained Metrics for Conversational Dialogue Systems (2022.acl-short)

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Challenge: Existing methods for evaluating conversational dialogue systems have been shown to be inefficient and instabile.
Approach: They propose an adversarial method to stress-test trained metrics for evaluation of conversational dialogue systems using Reinforcement Learning.
Outcome: The proposed method outperforms existing methods and can be applied to stress-test trained metrics for conversational dialogue systems.

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