Add library_name and links to paper, code, and project page

README.md

@@ -1,13 +1,17 @@
----
-license: mit
-language:
-- en
-pipeline_tag: image-text-to-text
----
+---
+language:
+- en
+license: mit
+pipeline_tag: image-text-to-text
+library_name: transformers
+---
+
 # UniMod
 
 **UniMod** is a multimodal moderation framework that transitions from *sparse decision supervision* to *dense, multi-attribute reasoning trajectories*.  
 
+[[Paper](https://huggingface.co/papers/2602.02536)] [[Code](https://github.com/Carol-gutianle/UniMod)] [[Project Page](https://trustworthylab.github.io/UniMod/)]
+
 ---
 
 ## Introduction
@@ -33,10 +37,10 @@ The UniMod framework consists of the following components:
 
 | Name | Type | Download |
 |------|------|----------|
-| **UniTrace** |  | TBA |
-| **UniRM** |  | TBA |
-| **UniReward** | | TBA |
-| **UniMod** | | TBA |
+| **UniTrace** | Dataset | TBA |
+| **UniRM** | Model | [UniRM](https://huggingface.co/Carol0110/UniRM) |
+| **UniReward** | Dataset | TBA |
+| **UniMod** | Model | [UniMod-3B](https://huggingface.co/Carol0110/UniMod-3B) |
 
 
 ---
@@ -147,6 +151,18 @@ python -m evaluations.eval \
 * `--task`: Comma-separated list of evaluation benchmarks, including
   `harmbench`, `xstest`, `wildguard`, `toxic`, `aegis`, `spavl`, and `beaver`.
 
+---
 
-
----
+## Citation
+
+```bibtex
+@misc{gu2026sparsedecisionsdensereasoning,
+      title={From Sparse Decisions to Dense Reasoning: A Multi-attribute Trajectory Paradigm for Multimodal Moderation}, 
+      author={Tianle Gu and Kexin Huang and Lingyu Li and Ruilin Luo and Shiyang Huang and Zongqi Wang and Yujiu Yang and Yan Teng and Yingchun Wang},
+      year={2026},
+      eprint={2602.02536},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2602.02536}, 
+}
+```