Update README.md

README.md

@@ -3,10 +3,11 @@ language:
 - en
 license: apache-2.0
 task_categories:
-- conversational
+- question-answering
 - text-generation
 tags:
 - reinforcement-learning-from-human-feedback
+- reinforcement-learning
 - dialogue
 - conversational-ai
 - preference-alignment
@@ -182,13 +183,7 @@ configs:
 
 # Retrospective Learning from Interactions (Respect) Dataset
 
-This dataset supports **Retrospective Learning from Interactions (Respect)**, a paradigm introduced in the paper [The Era of Real-World Human Interaction: RL from User Conversations](https://huggingface.co/papers/2509.25137).
-
-The paper introduces Reinforcement Learning from Human Interaction (RLHI), a novel approach that learns directly from in-the-wild user conversations. This enables continual model improvement and multifaceted alignment of conversational models, moving beyond traditional pre-annotated, expert-generated human feedback. The dataset facilitates two complementary methods: RLHI with User-Guided Rewrites and RLHI with User-Based Rewards, linking long-term user personas to turn-level preferences.
-
-*   **Paper**: [The Era of Real-World Human Interaction: RL from User Conversations](https://huggingface.co/papers/2509.25137)
-*   **Project Page**: [https://lil-lab.github.io/respect](https://lil-lab.github.io/respect)
-*   **GitHub Repository**: [https://github.com/lil-lab/respect](https://github.com/lil-lab/respect)
+This repository contains the `lil-lab/respect` data, 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
 
@@ -211,4 +206,4 @@ model = Idefics2ForConditionalGeneration.from_pretrained(
     checkpoint, torch_dtype=torch.bfloat16)
 peft_model = PeftModel.from_pretrained(
     model, model_id, adapter_name="r6_bp", revision="r6_bp")
-```
+```