Papers by Peter Vickers
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering (2021.acl-short)
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| Challenge: | Current Visual Question Answering (VQA) models are trained on labelled data that may be insufficient to learn complex knowledge representations. |
| Approach: | They propose a method to integrate external knowledge into a visual pre-trained model by integrating facts extracted from a knowledge base. |
| Outcome: | The proposed method outperforms baseline models on the KVQA dataset benchmark by 19% and shows that it is weaker than previous models. |
Comparing Edge-based and Node-based Methods on a Citation Prediction Task (2024.findings-emnlp)
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| Challenge: | Citation Prediction is the task of estimating whether paper a cites paper b. |
| Approach: | They propose a new Citation Prediction task that evaluates both a node-based model and an edge-based one to quantify these trends. |
| Outcome: | The proposed model improves with larger training sets and degrades with longer forecast horizons. |