Update README.md

README.md

@@ -1,4 +1,104 @@
 ---
-license: mit
+annotations_creators:
+- crowdsourced
+language:
+- en
+license:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 1k<n<10k
+task_categories:
+- conversational
+- text-generation
+task_ids:
+- dialogue-modeling
 ---
-Coming soon!
+## Overview
+
+`CHARP` is diagnostic testbed, exclusively assess whether information-seeking dialogue systems effectively attend to and 
+use the conversation history. `CHARP` is built by modifying examples from the [FaithDial](https://huggingface.co/datasets/McGill-NLP/FaithDial) 
+validation set to ensure maximum domain alignment with FaithDial and to minimize annotation costs. That is, we edit 
+FaithDial examples to make their response dependent on the conversation history analogously to FaithDial's editing of 
+WoW annotations to make them hallucination-free. `CHARP` consists of 2 subsets, where only the last seeker utterance 
+differs: a self-contained *easy* version (`eCHARP`), and a *hard* (`hCHARP`) which requires reasoning over the 
+conversation history and the provided knowledge that corresponds to the last seeker.
+
+## Data Splits
+We create two variants of `CHARP`: `hCHARP` for examples where addressing the last seeker's inquiry requires reasoning 
+over the conversation history, and `eCHARP`, where the last inquiry can be addressed without such reasoning. We annotate
+ 42\% of the FaithDial validation set (after excluding examples without conversation history) . `CHARP` consists of
+containing `2,160` examples, split equally between `eCHARP` and `hCHARP`:
+- `eCHARP`: 1080 samples
+- `hCHARP`: 1080 samples
+
+## Data Fields
+
+* Both `eCHARP` and `hCHARP` have the same  data format:
+
+ - `row_idx`:  `int`. Index of the sample that is equivalent to the one in FaithDial validation (row enumeration).
+ - `history`: `List[string]`. The dialogue history.
+ - `knowledge`: `string`. The source knowkedge on which the bot should ground its response.
+ - `response`:   `string`.  The expected model response
+
+
+## Data Instance
+
+An example of `eCHARP` looks as follows: 
+
+```json
+{
+  "row_idx": "1293",
+  "history": [
+    "I love watching and playing basketball.",
+    "I see. Have you ever tried to describe basketball? I would say it is a low contact sport where the game is held in a rectangular court.",
+    "Yeah I never though of that, can you repeat what you told me again so I can take notes?",
+    "Yes I can, basketball is a sport with limited contact. It is held on a rectangular like court.",
+    "What would you describe the sport is played like?",
+    "The objective for basketball is shooting the ball into the hoops. The hoops are high and placed with a backboard on each side of the court.",
+    "Oh yea, that's pretty simple. Do you know any famous basketball courts?"
+  ],
+  "knowledge": "Supreme Court in the USA is very famous to have well-known judges, while the Philippine Arena is popular due to the size of the basketball court.",
+  "response": "Ah yeah, I heard that the Philippine Arena is popular because of the size of the basketball court."
+}
+```
+An example of `hCHARP` looks as follows: 
+
+```json
+{
+  "row_idx": "1293",
+  "history": [
+    "I love watching and playing basketball.",
+    "I see. Have you ever tried to describe basketball? I would say it is a low contact sport where the game is held in a rectangular court.",
+    "Yeah I never though of that, can you repeat what you told me again so I can take notes?",
+    "Yes I can, basketball is a sport with limited contact. It is held on a rectangular like court.",
+    "What would you describe the sport is played like?",
+    "The objective for basketball is shooting the ball into the hoops. The hoops are high and placed with a backboard on each side of the court.",
+    "Oh yea, that's pretty simple. Do you know any famous courts?"
+  ],
+  "knowledge": "Supreme Court in the USA is very famous to have well-known judges, while the Philippine Arena is popular due to the size of the basketball court.",
+  "response": "Ah yeah, I heard that the Philippine Arena is popular because of the size of the basketball court."
+}
+```
+
+# Who are the annotators?
+
+We would like to thank Imad Mousaoui, Ella Cho, Abdulmuizz Yusuf, and Parminder Singh Bharot, the professional annotators without whom this work would have not been possible.
+
+## Licensing Information
+
+MIT
+
+## Citation
+
+```bibtex
+@article{ghaddar2024charp,
+      title={CHARP: Conversation History AwaReness Probing for Knowledge-grounded Dialogue Systems}, 
+      author={Abbas Ghaddar and David Alfonso-Hermelo and Philippe Langlais and Mehdi Rezagholizadeh and Boxing Chen and Prasanna Parthasarathi},
+      year={2024},
+      eprint={2405.15110},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```