Papers by Segev Shlomov
Deep Dominance - How to Properly Compare Deep Neural Models (P19-1)
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| Challenge: | Existing methods for comparing DNNs on unseen data are not suitable for this task. |
| Approach: | They propose to adapt a test for the Almost Stochastic Dominance relation between two distributions to the problem by comparing their performance on unseen data. |
| Outcome: | The proposed method meets all criteria while previously proposed methods fail to do so. |
The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing (P18-1)
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| Challenge: | Statistical significance testing is a standard statistical tool designed to ensure that experimental results are not coincidental. |
| Approach: | They propose a protocol for statistical significance test selection in NLP setups . they propose he proposes a survey of the most relevant tests to help guide the protocol . |
| Outcome: | The proposed protocol includes a survey of the most relevant tests. |
We’ve had this conversation before: A Novel Approach to Measuring Dialog Similarity (2021.emnlp-main)
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| Challenge: | Dialogs are a building block of human natural language interactions. |
| Approach: | They propose a new edit distance metric for dialog similarity analysis using conversation semantics, conversation flow, and the participants. |
| Outcome: | The proposed method outperforms existing methods on two publicly available datasets and is better aligned with human perception of conversation similarity. |