Maxime Peyrard
6 papers in the PaperMetrix corpus
Papers by this author
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A Principled Framework for Evaluating Summarizers: Comparing Models of Summary Quality against Human Judgments
2017
We present a new framework for evaluating extractive summarizers, which is based on a principled representation as optimization problem. We prove that every extractive summarizer can be decomposed into an objective function and an optimization …
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Learning to Score System Summaries for Better Content Selection Evaluation.
2017
The evaluation of summaries is a challenging but crucial task of the summarization field. In this work, we propose to learn an automatic scoring metric based on the human judgements available as part of classical …
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A Ladder of Causal Distances
2021
Causal discovery, the task of automatically constructing a causal model from data, is of major significance across the sciences. Evaluating the performance of causal discovery algorithms should ideally involve comparing the inferred models to ground-truth …
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Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning
2022 · arXiv (Cornell University)
Machine learning (ML) models are typically optimized for their accuracy on a given dataset. However, this predictive criterion rarely captures all desirable properties of a model, in particular how well it matches a domain expert's …
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Flows: Building Blocks of Reasoning and Collaborating AI
2023 · arXiv (Cornell University)
Recent advances in artificial intelligence (AI) have produced highly capable and controllable systems. This creates unprecedented opportunities for structured reasoning as well as collaboration among multiple AI systems and humans. To fully realize this potential, …
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MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance
2019
Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer, Steffen Eger. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing …