Update README.md

README.md

@@ -23,7 +23,8 @@ The model is trained in two stages from a pretrained vanilla VAR checkpoint:
 - **Stage 1 — SFT.** Supervised fine-tuning on 267,710 paired (content, style, target) triplets.
 - **Stage 2 — GRPO.** Reinforcement fine-tuning with Group Relative Policy Optimization against a DreamSim-based perceptual reward, using LoRA adapters ($r{=}256$) and Per-Action Normalization Weighting (PANW) to rebalance credit across the $256\times$ token imbalance between coarse and fine scales.
 
-- **Paper / code:** https://github.com/Senfier-LiqiJing/StyleVAR
+- **Code:** https://github.com/Senfier-LiqiJing/StyleVAR
+- **Paper (OpenReview):** https://openreview.net/forum?id=UHW3PgLUsa
 - **Authors:** Liqi Jing, Dingming Zhang, Peinian Li, Lichen Zhu (Duke University)
 
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