Update README.md

README.md

@@ -78,7 +78,7 @@ datasets:
 thumbnail: "https://github.com/sberbank-ai/mgpt"
 ---
 
-# Multilingual GPT model
+# mGPT 1.3B
 
 We introduce a family of autoregressive GPT-like models with 1.3 billion parameters trained on 61 languages from 25 language families using Wikipedia and Colossal Clean Crawled Corpus. 
 
@@ -88,32 +88,33 @@ We reproduce the GPT-3 architecture using GPT-2 sources and the sparse attention
 The source code for the mGPT XL model is available on [Github](https://github.com/sberbank-ai/mgpt)
 
 ## Paper
- mGPT: Few-Shot Learners Go Multilingual
+
+ **mGPT: Few-Shot Learners Go Multilingual**
+
+ Published at TACL 2024 (MIT Press). Presented at EMNLP 2023.
  
  [Abstract](https://arxiv.org/abs/2204.07580) [PDF](https://arxiv.org/pdf/2204.07580.pdf)
 
- ![](https://habrastorage.org/webt/1q/ru/yt/1qruytul6m2m-upyk9frq3pgrds.png)
-
  ```
-@misc{https://doi.org/10.48550/arxiv.2204.07580,
-  doi = {10.48550/ARXIV.2204.07580},
-  
-  url = {https://arxiv.org/abs/2204.07580},
-  
-  author = {Shliazhko, Oleh and Fenogenova, Alena and Tikhonova, Maria and Mikhailov, Vladislav and Kozlova, Anastasia and Shavrina, Tatiana},
-  
-  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2; I.2.7, 68-06, 68-04, 68T50, 68T01},
-  
-  title = {mGPT: Few-Shot Learners Go Multilingual},
-  
-  publisher = {arXiv},
-  
-  year = {2022},
-  
-  copyright = {Creative Commons Attribution 4.0 International}
+@article{shliazhko-etal-2024-mgpt,
+    title = "m{GPT}: Few-Shot Learners Go Multilingual",
+    author = "Shliazhko, Oleh  and
+      Fenogenova, Alena  and
+      Tikhonova, Maria  and
+      Kozlova, Anastasia  and
+      Mikhailov, Vladislav  and
+      Shavrina, Tatiana",
+    journal = "Transactions of the Association for Computational Linguistics",
+    volume = "12",
+    year = "2024",
+    address = "Cambridge, MA",
+    publisher = "MIT Press",
+    url = "https://aclanthology.org/2024.tacl-1.4",
+    doi = "10.1162/tacl_a_00633",
+    pages = "58--79",
+    abstract = "This paper introduces mGPT, a multilingual variant of GPT-3, pretrained on 61 languages from 25 linguistically diverse language families using Wikipedia and the C4 Corpus. We detail the design and pretraining procedure. The models undergo an intrinsic and extrinsic evaluation: language modeling in all languages, downstream evaluation on cross-lingual NLU datasets and benchmarks in 33 languages, and world knowledge probing in 23 languages. The in-context learning abilities are on par with the contemporaneous language models while covering a larger number of languages, including underrepresented and low-resource languages of the Commonwealth of Independent States and the indigenous peoples in Russia. The source code and the language models are publicly available under the MIT license.",
 }
-
- ```
+```
 
 
 ## Languages