Update README.md

README.md

@@ -42,7 +42,7 @@ datasets:
 ---
 
 ## LongForm-OPT-2.7B
-The LongForm dataset is created by leveraging English corpus examples with augmented instructions. We select a diverse set of human-written documents from existing corpora such as C4 and Wikipedia and generate instructions for the given documents via LLMs. Then, we extend these examples with structured corpora examples such as Stack Exchange and WikiHow and task examples such as question answering, email writing, grammar error correction, story/poem generation, and text summarization.
+The LongForm dataset is created by leveraging English corpus examples with reverse instructions. We select a diverse set of human-written documents from existing corpora such as C4 and Wikipedia and generate instructions for the given documents via LLMs. Then, we extend these examples with structured corpora examples such as Stack Exchange and WikiHow and task examples such as question answering, email writing, grammar error correction, story/poem generation, and text summarization.
 
 
 Github Repo: https://github.com/akoksal/LongForm
@@ -97,12 +97,12 @@ Smaller versions of LongForm-OPT models are also available:
 The LongForm dataset and models mainly focus on long text generation and have limitations regarding structured prediction tasks in NLP. Additionally, we observe that LongForm models may present hallucination problems similar to those found in LLMs.
 
 ## License
-The LongForm project is subject to a MIT License with custom limitations for restrictions imposed by OpenAI (for the instruction generation part), as well as the license of language models (OPT, LLaMA, and T5).
+The LongForm project is subject to a MIT License with custom limitations for restrictions imposed by OpenAI (for the instruction generation part), as well as the license of language models (OPT, LLaMA, and T5). The WikiHow subset of LongForm-C is subject to the license proposed by WikiHow.
 
 ## Citation
 ```
 @misc{koksal2023longform,
-      title={LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction}, 
+      title={LongForm: Effective Instruction Tuning with Reverse Instructions}, 
       author={Abdullatif Köksal and Timo Schick and Anna Korhonen and Hinrich Schütze},
       year={2023},
       eprint={2304.08460},