Papers by Ian Wood
Integrating Lexical Information into Entity Neighbourhood Representations for Relation Prediction (2021.naacl-main)
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| Challenge: | Existing methods to predict knowledge base relations are limited by maintenance costs and text-based formats. |
| Approach: | They propose a system that can extend relational database tables with information extracted from a document corpus. |
| Outcome: | The proposed system outperforms existing methods by incorporating embeddings of text-based representations of the entities and relations. |
Mention Flags (MF): Constraining Transformer-based Text Generators (2021.acl-long)
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| Challenge: | Constrained decoding algorithms produce hypotheses satisfying all constraints, but they are computationally expensive and can lower the generated text quality. |
| Approach: | They propose a Mention Flag mechanism which traces whether lexical constraints are satisfied in outputs of an S2S decoder. |
| Outcome: | The proposed models maintain higher constraint satisfaction and text quality than baseline models and other constrained decoding algorithms. |
ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning (2021.eacl-main)
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| Challenge: | Novel Object Captioning is a zero-shot Image Caption task requiring describing objects not seen in the training captions, but for which information is available from external object detectors. |
| Approach: | They propose a novel captioning model that encourages copying of object labels with reinforcement learning that encourage a copy-augmented transformer model to accurately describe the object labels. |
| Outcome: | The proposed model sets new state-of-the-art on the nocaps and held-out COCO benchmarks. |
A Comparison Of Emotion Annotation Schemes And A New Annotated Data Set (L18-1)
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| Challenge: | a series of study on positive/negative sentiments has been conducted on tweets, but recognition of more nuanced affect has received little attention . valence, arousal, dominance and surprise are the most commonly used emotion representation schemes . |
| Approach: | They propose to annotate tweets with scores on four emotion dimensions . they compare annotator agreement with relative annotation schemes over categorical ones . |
| Outcome: | The proposed model improves agreement with relative annotation schemes over categorical ones on Ekman's six basic emotions. |