Update README.md

README.md

@@ -4,6 +4,23 @@ library_name: peft
 license: apache-2.0
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+# MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs
+
+🔗 Paper link: [Arxiv preprint](https://arxiv.org/abs/2507.02851)
+
+🔗 Link to the trained models: [Hugging Face collection](https://huggingface.co/collections/purbeshmitra/motif-paper-models-686a2f36407bb88f750eef75)
+
+The [INFTYTHINK architecture](https://arxiv.org/abs/2503.06692v1), shown below, allows multi-round thinking for extended LLM reasoning beyond its context size.
+<p align="center">
+  <img src="assets/multiround.png" alt="Alt Text" width="750">
+</p>
+
+In this work, we propose a GRPO based training method for such a system that allows to calculate the accuracy reward by rolling out trajectories and applying the reward at the first round of inference outcomes. This is depicted as following:
+<p align="center">
+  <img src="assets/multiround_grpo.png" alt="Alt Text" width="750">
+</p>
+
+
 ## Usage
 ```python
 from peft import PeftModel