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Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications ...
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A Generative Framework for Simultaneous Machine Translation ...
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Continual Quality Estimation with Online Bayesian Meta-Learning ...
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SentSim: Crosslingual Semantic Evaluation of Machine Translation ...
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What Makes a Scientific Paper be Accepted for Publication? ...
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Abstract:
Despite peer-reviewing being an essential component of academia since the 1600s, it has repeatedly received criticisms for lack of transparency and consistency. We posit that recent work in machine learning and explainable AI provide tools that enable insights into the decisions from a given peer review process. We start by extracting global explanations in the form of linguistic features that affect the acceptance of a scientific paper for publication on an open peer-review dataset. Second, since such global explanations do not justify causal interpretations, we provide a methodology for detecting confounding effects in natural language in order to generate causal explanations, under assumptions, in the form of lexicons. Our proposed linguistic explanation methodology indicates the following on a case dataset of ICLR submissions: a) the organising committee follows, for the most part, the recommendations of reviewers, and, b) the paper's main characteristics that led to reviewers recommending acceptance for ...
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Keyword:
68T50; Computation and Language cs.CL; FOS Computer and information sciences; I.2.7
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URL: https://arxiv.org/abs/2104.07112 https://dx.doi.org/10.48550/arxiv.2104.07112
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MultiSubs: A Large-scale Multimodal and Multilingual Dataset ...
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Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Classifying Dyads for Militarized Conflict Analysis
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Efficient Sampling of Dependency Structure
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Searching for More Efficient Dynamic Programs
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In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding
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In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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A Bayesian Framework for Information-Theoretic Probing
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Findings of the WMT 2021 Shared Task on Quality Estimation ...
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Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation ...
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The (Un)Suitability of Automatic Evaluation Metrics for Text Simplification ...
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