Update README.md

README.md

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   By clicking Submit below I accept the terms of the license and Acceptable Use policy: checkbox
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----
+---
+## Links
+ - Website
+ - Paper
+ - Leaderboard
+ - Repo
+
+## Summary
+
+## Dataset format
+The data was created by generating up to 6 obfuscations per problem for 82 problems source from original LingOly benchmark.
+
+```python
+{'question_n':  # The question number in the problem
+ 'prompt':      # The main text of the question 
+ 'subprompts': [
+  {'questionpart_n':         # For questions with several sub-parts (e.g. translating several sentences or matching paris of sentences)
+   'question':               # The text of the question part
+   'answer':                 # The correct answer
+   'matches_human_scoring':  # Annotation metadata
+   'fuzzy_matching':         # Annotation metadata
+   'manual_edit':            # Annotation metadata
+  }],
+ 'metadata.preamble':        # General text from the overall problem that is shared across all questions for that problem
+ 'metadata.context':         # Context text that includes important information, you should prepend your prompt with context for solvability
+ 'metadata.obfuscated':      # If this example was obfuscated or not
+ 'metadata.obf_num':         # Obfuscation counter (unique per problem). This is 0 if unobfuscated 
+ 'metadata.overall_question_n':    # The problem number
+ 'metadata.obfuscated_question_n': # Concatenation of problem number and obfuscation number
+}
+```
+
+## Citation
+```
+@article{khouja2025lingolytoo,
+      title={LINGOLY-TOO: Disentangling Memorisation from Reasoning with Linguistic Templatisation and Orthographic Obfuscation}, 
+      author={Khouja, Jude and Korgul, Karolina and Hellsten, Simeon and Yang, Lingyi and Neacșu, Vlad A. and Mayne, Harry and Kearns, Ryan O. and Bean, Andrew M. and Mahdi, Adam},
+      year={2025},
+      eprint=,
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url=, 
+}
+
+```