Add library_name and fix paper link

README.md

@@ -1,23 +1,26 @@
 ---
-license: apache-2.0
+base_model:
+- Qwen/Qwen2.5-VL-7B-Instruct
 datasets:
 - hitsmy/AdaReasoner-TC-Randomized
 - hitsmy/AdaReasoner-TG-Data-Randomized
 language:
 - en
+license: apache-2.0
 metrics:
 - accuracy
-base_model:
-- Qwen/Qwen2.5-VL-7B-Instruct
 pipeline_tag: image-text-to-text
+library_name: transformers
 tags:
 - agent
+arxiv: 2601.18631
 ---
+
 <div align="center">
   <img src="docs/logo.png" alt="Logo" width="300">
   <h1 align="center">Dynamic Tool Orchestration for Iterative Visual Reasoning</h1>
 
-  <a href="#">
+  <a href="https://arxiv.org/abs/2601.18631">
     <img src="https://img.shields.io/badge/Paper-A42C25?style=for-the-badge&logo=arxiv&logoColor=white" alt="Paper">
   </a>
   <a href="https://github.com/ssmisya/AdaReasoner/tree/main/docs">
@@ -44,8 +47,7 @@ tags:
 
 ## 📋 Model Description
 
-**AdaReasoner-7B** is a vision-language model trained with dynamic tool orchestration capabilities for iterative visual reasoning. This model is AdaReasoner-7B-Randomized.
-
+**AdaReasoner-7B** is a vision-language model trained with dynamic tool orchestration capabilities for iterative visual reasoning. This model is AdaReasoner-7B-Randomized. It was introduced in the paper [AdaReasoner: Dynamic Tool Orchestration for Iterative Visual Reasoning](https://arxiv.org/abs/2601.18631).
 
 We provide three variants of AdaReasoner-7B, each optimized for different use cases:
 
@@ -64,7 +66,8 @@ We provide three variants of AdaReasoner-7B, each optimized for different use ca
 
 ## 🚀 Quick Start
 
-AdaReasoner-7B can be deployed for single-turn inference using standard inference frameworks such as vLLM.
+AdaReasoner-7B can be deployed for single-turn inference using standard inference frameworks such as vLLM or the `transformers` library.
+
 However, AdaReasoner is a tool-planning model whose full capabilities require interaction with an external tool environment.
 To fully evaluate or utilize its tool-planning behavior, we recommend using [AdaEval](https://github.com/ssmisya/AdaReasoner/tree/main/tool_server/tf_eval) provided in our repository for batch inference and evaluation, or trying the [Demo](https://github.com/ssmisya/AdaReasoner/tree/main/tool_server/tf_eval/demo) interface for interactive, single-instance GUI-based reasoning.