Representation Learning for Relational and Cross-Lingual Data

Representation Learning for Relational and Cross-Lingual Data
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This is a past event

Utilising real-world relational signals (e.g., structured knowledge) and understanding different languages are two (of the many) fundamental goals of Artificial General Intelligence. The corresponding explorations, however, have been relatively separate. In this talk, I will introduce our recent research outputs on bridging this gap: 

- We discovered the unnoticed connections between embedding algorithms for entities and cross-lingual lexicons;

- We theoretically and empirically justified that the success of cross-lingual encodings relies on the consistency of relational encodings;

- Based on the above findings and insights, we accomplished complex tasks such as Cross-Lingual Knowledge Graph Alignment and Knowledge-Aware Cross-Lingual Language Model Pretraining.

Speaker
Xutan Peng
Venue
Meston 2 and MS Teams
Contact

Contact Ehud Reiter (e.reiter@abdn.ac.uk) for more information