ltg
/

ltgoslo commited on
Commit
dfeae3f
1 Parent(s): 08e34c0

ACL Anthology

Browse files
Files changed (1) hide show
  1. README.md +24 -1
README.md CHANGED
@@ -34,7 +34,7 @@ Its input is the usage example and the instruction question "What is the definit
34
 
35
  ## Model description
36
 
37
- See details in the paper [Enriching Word Usage Graphs with Cluster Definitions](https://arxiv.org/abs/2403.18024) (LREC-COLING'2024) by
38
  Mariia Fedorova, Andrey Kutuzov, Nikolay Arefyev and Dominik Schlechtweg.
39
 
40
  ## Intended uses & limitations
@@ -87,3 +87,26 @@ The following hyperparameters were used during training:
87
  - Tokenizers 0.12.1
88
 
89
  ## Citation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
34
 
35
  ## Model description
36
 
37
+ See details in the paper [Enriching Word Usage Graphs with Cluster Definitions](https://aclanthology.org/2024.lrec-main.546/) (LREC-COLING'2024) by
38
  Mariia Fedorova, Andrey Kutuzov, Nikolay Arefyev and Dominik Schlechtweg.
39
 
40
  ## Intended uses & limitations
 
87
  - Tokenizers 0.12.1
88
 
89
  ## Citation
90
+ ```
91
+ @inproceedings{kutuzov-etal-2024-enriching-word,
92
+ title = "Enriching Word Usage Graphs with Cluster Definitions",
93
+ author = "Kutuzov, Andrey and
94
+ Fedorova, Mariia and
95
+ Schlechtweg, Dominik and
96
+ Arefyev, Nikolay",
97
+ editor = "Calzolari, Nicoletta and
98
+ Kan, Min-Yen and
99
+ Hoste, Veronique and
100
+ Lenci, Alessandro and
101
+ Sakti, Sakriani and
102
+ Xue, Nianwen",
103
+ booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
104
+ month = may,
105
+ year = "2024",
106
+ address = "Torino, Italia",
107
+ publisher = "ELRA and ICCL",
108
+ url = "https://aclanthology.org/2024.lrec-main.546",
109
+ pages = "6189--6198",
110
+ abstract = "We present a dataset of word usage graphs (WUGs), where the existing WUGs for multiple languages are enriched with cluster labels functioning as sense definitions. They are generated from scratch by fine-tuned encoder-decoder language models. The conducted human evaluation has shown that these definitions match the existing clusters in WUGs better than the definitions chosen from WordNet by two baseline systems. At the same time, the method is straightforward to use and easy to extend to new languages. The resulting enriched datasets can be extremely helpful for moving on to explainable semantic change modeling.",
111
+ }
112
+ ```