Name
Abstract | ||
|---|---|---|
We propose a new dataset for evaluating question answering models with respect to their capacity to reason about beliefs. Our tasks are inspired by theory-of-mind experiments that examine whether children are able to reason about the beliefs of others, in particular when those beliefs differ from reality. We evaluate a number of recent neural models with memory augmentation. We find that all fail on our tasks, which require keeping track of inconsistent states of the world; moreover, the modelsu0027 accuracy decreases notably when random sentences are introduced to the tasks at test. |
Year | Venue | DocType |
|---|---|---|
2018 | EMNLP | Conference |
Volume | Citations | PageRank |
abs/1808.09352 | 0 | 0.34 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aida Nematzadeh | 1 | 25 | 9.37 |
| Kaylee Burns | 2 | 3 | 1.72 |
| Erin Grant | 3 | 25 | 5.71 |
| Alison Gopnik | 4 | 46 | 17.65 |
| Thomas L. Griffiths | 5 | 0 | 0.34 |