Update README.md

LangHack is a dataset of [diff history](https://diffhistory.github.io/) demonstration data for the rogue-like video game [NetHack](https://github.com/facebookresearch/nle) generated using the symbolic [AutoAscend bot](https://github.com/maciej-sypetkowski/autoascend), which boasts state-of-the-art performance in the game (as of 07/22/2024).

This dataset was created by sub-sampling 10,000 full NetHack games played by AutoAscend into contiguous "chunks" of 64 timesteps, and converting the agent's game state observations in natural language text using the [NetHack Language Wrapper](https://github.com/ngoodger/nle-language-wrapper). Sub-sampling was performed uniformly at random over all recorded game data.

LangHack prompts correspond to a full game state observation at one timestep of AutoAscend gameplay, while completions correspond to a interleaved set of the subsequent bot actions and their resultant text deltas in the world state.

A detailed report of NetHack agent performance achieved by finetuning a tiny LLM ([GPT2-127M](https://huggingface.co/openai-community/gpt2)) on LangHack is provided [here](https://arxiv.org/abs/2312.07540).

README.md

@@ -1,20 +1,28 @@
----
-license: mit
-dataset_info:
-  features:
-  - name: prompt
-    dtype: string
-  - name: completion
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 13449668588
-    num_examples: 500000
-  download_size: 3251708048
-  dataset_size: 13449668588
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+license: mit
+dataset_info:
+  features:
+  - name: prompt
+    dtype: string
+  - name: completion
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 13449668588
+    num_examples: 500000
+  download_size: 3251708048
+  dataset_size: 13449668588
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+task_categories:
+- text-generation
+tags:
+- nethack
+- interactive decision-making
+- llm agents
+- imitation learning
+- behavioral cloning
+---