[DOC] Add FCS paper

README.md

@@ -10,6 +10,9 @@
 
 # ABLkit: A Toolkit for Abductive Learning
 
+- [Documentation](https://ablkit.readthedocs.io/en/latest/index.html)
+- [Read the paper](https://journal.hep.com.cn/fcs/EN/10.1007/s11704-024-40085-7)
+
 **ABLkit** is an efficient Python toolkit for [**Abductive Learning (ABL)**](https://www.lamda.nju.edu.cn/publication/chap_ABL.pdf). ABL is a novel paradigm that integrates machine learning and logical reasoning in a unified framework. It is suitable for tasks where both data and (logical) domain knowledge are available. 
 
 <p align="center">
@@ -182,7 +185,7 @@ bridge.test(test_data)
 
 </details>
 
-To explore detailed tutorials and information, please refer to - [document](https://ablkit.readthedocs.io/en/latest/index.html).
+To explore detailed tutorials and information, please refer to: [Documentation on Read the Docs](https://ablkit.readthedocs.io/en/latest/index.html).
 
 ## Examples
 
@@ -218,4 +221,20 @@ For more information about ABL, please refer to: [Zhou, 2019](http://scis.scichi
   address   = {Amsterdam},
   year      = {2022}
 }
+```
+
+## Cite
+
+To cite ABLkit, please cite the following paper:  [Huang et al., 2024](https://journal.hep.com.cn/fcs/EN/10.1007/s11704-024-40085-7).
+
+```
+@article{ABLkit2024,
+  author     = {Huang, Yu-Xuan and Hu, Wen-Chao and Gao, En-Hao and Jiang, Yuan},
+  title      = {ABLkit: a Python toolkit for abductive learning},
+  journal    = {Frontiers of Computer Science},
+  volume     = {18},
+  number     = {6},
+  pages      = {186354},
+  year       = {2024}
+}
 ```

docs/References.rst

@@ -1,6 +1,23 @@
 References
 ==========
 
+To cite ABLkit, please cite the following paper:  
+
+Yu-Xuan Huang, Wen-Chao Hu, En-Hao Gao and Yuan Jiang. `ABLkit: a Python toolkit for abductive learning <https://journal.hep.com.cn/fcs/EN/10.1007/s11704-024-40085-7>`. **Frontiers of Computer Science**, 2024, 18: 186354.
+
+.. code-block:: latex
+    @article{ABLkit2024,
+    author     = {Huang, Yu-Xuan and Hu, Wen-Chao and Gao, En-Hao and Jiang, Yuan},
+    title      = {ABLkit: a Python toolkit for abductive learning},
+    journal    = {Frontiers of Computer Science},
+    volume     = {18},
+    number     = {6},
+    pages      = {186354},
+    year       = {2024}
+    }
+
+For more information about ABL, please refer to:
+
 Zhi-Hua Zhou. `Abductive learning: Towards bridging machine learning and logical reasoning <http://scis.scichina.com/en/2019/076101.pdf>`_. **Science China Information Sciences**, 2019, 62: 076101.
 
 Zhi-Hua Zhou and Yu-Xuan Huang. `Abductive learning <https://www.lamda.nju.edu.cn/publication/chap_ABL.pdf>`_. In P. Hitzler and M. K. Sarker eds., **Neuro-Symbolic Artificial Intelligence: The State of the Art**, IOP Press, Amsterdam, 2022, p.353-379
@@ -26,4 +43,4 @@ Zhi-Hua Zhou and Yu-Xuan Huang. `Abductive learning <https://www.lamda.nju.edu.c
         pages     = {353--369},
         address   = {Amsterdam},
         year      = {2022}
-    }
+    }

docs/index.rst

@@ -92,6 +92,22 @@ and `Zhou and Huang, 2022 <https://www.lamda.nju.edu.cn/publication/chap_ABL.pdf
         year      = {2022}
     }
 
+Cite
+----
+To cite ABLkit, please cite the following paper:  `Huang et al., 2024 <https://journal.hep.com.cn/fcs/EN/10.1007/s11704-024-40085-7>`.
+
+.. code-block:: latex
+    @article{ABLkit2024,
+    author     = {Huang, Yu-Xuan and Hu, Wen-Chao and Gao, En-Hao and Jiang, Yuan},
+    title      = {ABLkit: a Python toolkit for abductive learning},
+    journal    = {Frontiers of Computer Science},
+    volume     = {18},
+    number     = {6},
+    pages      = {186354},
+    year       = {2024}
+    }
+
+
 .. toctree::
    :maxdepth: 1
    :caption: Overview