update README.md

README.md

 System for generating DEFT 2023 outputs from LLMs
 =================================================
 
+The DEFT'23 shared task consists in answering pharma exam MCQs. This system converts the questions and possible answers to prompts and uses LLMs to generate answers.
+The approach is described in our [paper](http://talnarchives.atala.org/CORIA-TALN/CORIA-TALN-2023/479307.pdf). It ranked 1st at the shared task.
+This repository contains scripts to generate prompts, run off-the-shelf models and finetune the LLaMa models. It also contains the LoRA weights for the finetuned models. 
+
 This repository uses git LFS for large files.
 Use 'git lfs install' before cloning to retrive the binary files.
 
@@ -9,11 +13,25 @@ Install:
 pip install -r requirements.txt
 ```
 
-Installing bitsandbytes for llama models is a bit more [involved](https://gitlab.lis-lab.fr/cluster/wiki/-/wikis/Compiling%20bitsandbytes%20for%20int8%20inference).
+Note that bitsandbytes may need to be recompiled to support your cuda version.
 
 See RESULTS for the exact match results on the dev.
-See runs.sh for how to generate runs.
+See runs for how to generate runs.
 
 Note that external APIs require API keys. Please rename api_keys.template.py to api_keys.py and set keys you need inside.
 
-
+Please cite the follwing paper:
+```
+@inproceedings{Favre:CORIA-TALN:2023,
+    author = "Favre, Benoit",
+    title = "LIS@DEFT'23 : les LLMs peuvent-ils r\'epondre \`a des QCM ? (a) oui; (b) non; (c) je ne sais pas.",
+    booktitle = "Actes de CORIA-TALN 2023. Actes du D\'efi Fouille de Textes@TALN2023",
+    month = "6",
+    year = "2023",
+    address = "Paris, France",
+    publisher = "Association pour le Traitement Automatique des Langues",
+    pages = "46-56",
+    note = "",
+    url = "http://talnarchives.atala.org/CORIA-TALN/CORIA-TALN-2023/479307.pdf"
+}
+```