Update README.md

README.md

@@ -8,7 +8,7 @@ language:
 # modafact-ita
 
 `modafact-ita` is a sequence-to-sequence fine-tuned model for joint **event Factuality and Modality** detection in **Italian**.
-The model was fine-tuned on [ModaFact](https://huggingface.co/datasets/dhfbk/modafact-ita), a dataset manually annotated with Factuality and Modality values.
+The model was fine-tuned on [ModaFact](https://huggingface.co/datasets/dhfbk/modafact-ita), a dataset manually annotated with Factuality and Modality values, using [mT5-xxl](https://huggingface.co/google/mt5-xxl) as a base model.
 
 
 ## Model Details
@@ -25,8 +25,9 @@ The model was fine-tuned on [ModaFact](https://huggingface.co/datasets/dhfbk/mod
 
 <!-- Provide the basic links for the model. -->
 
-- **Paper:** coming soon!
-<!-- - **Inference script:** [https://github.com/dhfbk/ModaFact](https://github.com/dhfbk/ModaFact) -->
+- **Inference script:** if you want to use the model for inference, please refer to our [github repo](https://github.com/dhfbk/ModaFact).
+- **Paper:** [ModaFact: Multi-paradigm Evaluation for Joint Event Modality and Factuality Detection]([https://aclanthology.org/2025.coling-main.425/])
+
 
 ## Uses
 
@@ -47,17 +48,35 @@ and outputs a sequence of span=labels, in this format:
 
 [https://huggingface.co/datasets/dhfbk/modafact-ita](https://huggingface.co/datasets/dhfbk/modafact-ita)
 
-#### Training Hyperparameters
-
-- **Hyperparameters:** 
+<!-- #### Training Hyperparameters -->
 
-
-## Evaluation
+<!-- ## Evaluation -->
 
 
 ## Citation
 
+If you use or refer to ModaFact, please consider citing this paper:
+
+```
+@inproceedings{rovera-etal-2025-modafact,
+    title = "{M}oda{F}act: Multi-paradigm Evaluation for Joint Event Modality and Factuality Detection",
+    author = "Rovera, Marco  and
+      Cristoforetti, Serena  and
+      Tonelli, Sara",
+    editor = "Rambow, Owen  and
+      Wanner, Leo  and
+      Apidianaki, Marianna  and
+      Al-Khalifa, Hend  and
+      Eugenio, Barbara Di  and
+      Schockaert, Steven",
+    booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
+    month = jan,
+    year = "2025",
+    address = "Abu Dhabi, UAE",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2025.coling-main.425/",
+    pages = "6378--6396",
+    abstract = "Factuality and modality are two crucial aspects concerning events, since they convey the speaker`s commitment to a situation in discourse as well as how this event is supposed to occur in terms of norms, wishes, necessity, duty and so on. Capturing them both is necessary to truly understand an utterance meaning and the speaker`s perspective with respect to a mentioned event. Yet, NLP studies have mostly dealt with these two aspects separately, mainly devoting past efforts to the development of English datasets. In this work, we propose ModaFact, a novel resource with joint factuality and modality information for event-denoting expressions in Italian. We propose a novel annotation scheme, which however is consistent with existing ones, and compare different classification systems trained on ModaFact, as a preliminary step to the use of factuality and modality information in downstream tasks. The dataset and the best-performing model are publicly released and available under an open license."
+}
+```
 
-**BibTeX:**
-
-coming soon!