sileod commited on
Commit
5b64836
1 Parent(s): f5ad723

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +0 -15
README.md CHANGED
@@ -38,19 +38,4 @@ https://colab.research.google.com/drive/1J_RqDSw9iPxJSBvCJu-VRbjXnrEjKVvr?usp=sh
38
  journal={arXiv preprint arXiv:1502.05698},
39
  year={2015}
40
  }
41
-
42
- @inproceedings{sileo-moens-2022-analysis,
43
- title = "Analysis and Prediction of {NLP} Models via Task Embeddings",
44
- author = "Sileo, Damien and
45
- Moens, Marie-Francine",
46
- booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
47
- month = jun,
48
- year = "2022",
49
- address = "Marseille, France",
50
- publisher = "European Language Resources Association",
51
- url = "https://aclanthology.org/2022.lrec-1.67",
52
- pages = "633--647",
53
- abstract = "Task embeddings are low-dimensional representations that are trained to capture task properties. In this paper, we propose MetaEval, a collection of 101 NLP tasks. We fit a single transformer to all MetaEval tasks jointly while conditioning it on learned embeddings. The resulting task embeddings enable a novel analysis of the space of tasks. We then show that task aspects can be mapped to task embeddings for new tasks without using any annotated examples. Predicted embeddings can modulate the encoder for zero-shot inference and outperform a zero-shot baseline on GLUE tasks. The provided multitask setup can function as a benchmark for future transfer learning research.",
54
- }
55
-
56
  ```
 
38
  journal={arXiv preprint arXiv:1502.05698},
39
  year={2015}
40
  }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
41
  ```