fix name

README.md

@@ -10,14 +10,7 @@ library_name: transformers
 
 # The Era of Real-World Human Interaction: RL from User Conversations
 
-This repository contains the `lil-lab/respect` model, based on the paper [The Era of Real-World Human Interaction: RL from User Conversations](https://huggingface.co/papers/2509.25137).
-
-## Model Description
-The model introduces Reinforcement Learning from Human Interaction (RLHI), a paradigm that learns directly from in-the-wild user conversations to achieve continual model improvement and multifaceted alignment. It develops two complementary methods: (1) RLHI with User-Guided Rewrites, which revises unsatisfactory model outputs based on users' natural-language follow-up responses, and (2) RLHI with User-Based Rewards, which learns via a reward model conditioned on knowledge of the user's long-term interaction history (termed persona). These methods link long-term user personas to turn-level preferences via persona-conditioned preference optimization.
-
-## Project Resources
-*   **Project Page:** [https://lil-lab.github.io/respect](https://lil-lab.github.io/respect)
-*   **Code Repository:** [https://github.com/lil-lab/respect](https://github.com/lil-lab/respect)
+This repository contains the `lil-lab/respect` model, based on the ACL paper [Retrospective Learning from Interactions](https://huggingface.co/papers/2410.13852). For more resources, please see <https://lil-lab.github.io/respect> and <https://github.com/lil-lab/respect>.
 
 ## Sample Usage
 
@@ -60,4 +53,5 @@ peft_model = PeftModel.from_pretrained(
 ```
 
 ## Reproducibility
-To generate plots from the paper, run `analysis/plots.ipynb` in the [GitHub repository](https://github.com/lil-lab/respect).
+
+To generate plots from the paper, run `analysis/plots.ipynb` in the [GitHub repository](https://github.com/lil-lab/respect).