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John Kelleher

4 accepted papers

2021

Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods

EMNLP 2021main

Despite the widespread use of Knowledge Graph Embeddings (KGE), little is known about the security vulnerabilities that might disrupt their intended behaviour. We study data poisoning attacks against KGE models for link prediction. These attacks craft adversarial additions or deletions at training t…

2021

Poisoning Knowledge Graph Embeddings via Relation Inference Patterns

ACL 2021long

We study the problem of generating data poisoning attacks against Knowledge Graph Embedding (KGE) models for the task of link prediction in knowledge graphs. To poison KGE models, we propose to exploit their inductive abilities which are captured through the relationship patterns like symmetry, inve…

2020

Language-Driven Region Pointer Advancement for Controllable Image Captioning

COLING 2020main

Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated natural language caption. This puts a stronger focus on producing more detailed descriptions, and opens the…

2020

Style versus Content: A distinction without a (learnable) difference?

COLING 2020main

Textual style transfer involves modifying the style of a text while preserving its content. This assumes that it is possible to separate style from content. This paper investigates whether this separation is possible. We use sentiment transfer as our case study for style transfer analysis. Our exper…

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