Name
Title | ||
|---|---|---|
CogNLP-Sheffield at CMCL 2021 Shared Task: Blending Cognitively Inspired Features with Transformer-based Language Models for Predicting Eye Tracking Patterns |
Abstract | ||
|---|---|---|
The CogNLP-Sheffield submissions to the CMCL 2021 Shared Task examine the value of a variety of cognitively and linguistically inspired features for predicting eye tracking patterns, as both standalone model inputs and as supplements to contextual word embeddings (XLNet). Surprisingly, the smaller pre-trained model (XLNet-base) outperforms the larger (XLNet-large), and despite evidence that multi-word expressions (MWEs) provide cognitive processing advantages, MWE features provide little benefit to either model. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.18653/v1/2021.cmcl-1.16 | CMLS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Vickers | 1 | 0 | 0.34 |
| Rosa Wainwright | 2 | 0 | 0.34 |
| Harish Tayyar Madabushi | 3 | 0 | 1.01 |
| Aline Villavicencio | 4 | 20 | 3.41 |