Papers by Dora Jambor
LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing (2022.acl-long)
Copied to clipboard
| Challenge: | Semantic parsers struggle to generalize to examples with unseen combinations of seen rules from the training set. |
| Approach: | They propose a general framework to produce semantic parses by predicting node labels for a complete multi-layer input-aligned graph. |
| Outcome: | The proposed framework produces better generalizations than the baseline framework . it produces representations directly as a graph and not as sequences . |
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing methods for few-shot link prediction are limited by having only a few examples of a relation . low-frequency relations are abundant in knowledge graphs, but link prediction for these relations is important . |
| Approach: | They perform few-shot link prediction for a set of new relations unseen during training, given only a few examples of each relation at test time. |
| Outcome: | The proposed model is based on a simple, zero-shot baseline that ignores relation-specific information and achieves surprisingly strong performance. |