Papers by Hervé Jégou

2 papers
Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion (D18-1)

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Challenge: Existing approaches to learn orthogonal matrix aligning bilingual lexicons are suboptimal . resulting models suffer from "hubness problem" because word vectors tend to be nearest neighbors of abnormally high number of other words.
Approach: They propose a unified formulation that directly optimizes a retrieval criterion in an end-to-end fashion.
Outcome: The proposed approach outperforms the state-of-the-art on word translation on standard benchmarks.
Gradient-based Adversarial Attacks against Text Transformers (2021.emnlp-main)

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Challenge: Existing methods for obtaining adversarial examples are difficult with text data.
Approach: They propose a gradient-based adversarial attack against transformer models that searches for a distribution of adversarials parameterized by a continuous-valued matrix.
Outcome: The proposed attack outperforms existing methods on a variety of natural language tasks with matching imperceptibility.

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