Update: fix username links to PremC1F and premxai/emotion_engine

README.md

@@ -26,7 +26,7 @@ emotional appraisal in generative agents.
 
 > Paper: *Emergent Emotional Appraisal in Generative Agents via Predictive World Modeling*
 > Author: Prem Babu Kanaparthi
-> Code: [github.com/YOUR_USERNAME/emotion-engine](https://github.com/YOUR_USERNAME/emotion-engine)
+> Code: [github.com/premxai/emotion_engine](https://github.com/premxai/emotion_engine)
 
 ---
 
@@ -160,10 +160,10 @@ Each record contains the following fields:
 from datasets import load_dataset
 
 # Load a specific condition
-ds = load_dataset("YOUR_USERNAME/emotion-engine", "condition_d")
+ds = load_dataset("PremC1F/emotion-engine", "condition_d")
 
 # Load all conditions
-ds = load_dataset("YOUR_USERNAME/emotion-engine", "all")
+ds = load_dataset("PremC1F/emotion-engine", "all")
 
 # Filter to a specific scenario
 night_only = ds["train"].filter(lambda x: x["scenario"] == "standard_night")
@@ -179,7 +179,7 @@ from datasets import load_dataset
 import numpy as np
 from scipy.stats import fisher_exact
 
-ds = load_dataset("YOUR_USERNAME/emotion-engine", "condition_d", split="train")
+ds = load_dataset("PremC1F/emotion-engine", "condition_d", split="train")
 df = ds.to_pandas()
 
 ghost_present = df[df["obs_visible_ghosts"] > 0]
@@ -206,7 +206,7 @@ print(f"Fisher p = {p:.2e}")
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("YOUR_USERNAME/emotion-engine", "condition_d", split="train")
+ds = load_dataset("PremC1F/emotion-engine", "condition_d", split="train")
 df = ds.to_pandas()
 
 refusals = df[df["action"] == "refuse_help"].copy()

emotion_engine.py

@@ -8,10 +8,10 @@ Usage:
     from datasets import load_dataset
 
     # Single condition
-    ds = load_dataset("YOUR_USERNAME/emotion-engine", "condition_d")
+    ds = load_dataset("PremC1F/emotion-engine", "condition_d")
 
     # All conditions concatenated
-    ds = load_dataset("YOUR_USERNAME/emotion-engine", "all")
+    ds = load_dataset("PremC1F/emotion-engine", "all")
 """
 
 import datasets
@@ -47,7 +47,7 @@ Each record contains: full 14-dim observation, 6-dim emotion vector,
 action taken, and outcome metadata.
 """
 
-_HOMEPAGE = "https://github.com/YOUR_USERNAME/emotion-engine"
+_HOMEPAGE = "https://github.com/PremC1F/emotion-engine"
 _LICENSE  = "MIT"
 
 _CONDITIONS = [