Update README.md

README.md

@@ -8,7 +8,7 @@ language:
   - en
 ---
 
-This repository contains the evaluation data presented in: [OneThinker: All-in-one Reasoning Model for Image and Video](https://arxiv.org/abs/2512.03043)
+This repository contains the **evaluation data** presented in: [OneThinker: All-in-one Reasoning Model for Image and Video](https://arxiv.org/abs/2512.03043)
 
 Project Page: https://github.com/tulerfeng/OneThinker
 Code: https://github.com/tulerfeng/OneThinker
@@ -25,24 +25,5 @@ We construct the large-scale **OneThinker-600k** multi-task training corpus and
 
 OneThinker demonstrates **strong performance on 31 benchmarks across 10 fundamental vision tasks**, while showing cross-task knowledge transfer and promising zero-shot generalization toward a **unified multimodal reasoning generalist**.
 
-All code, models, and data are fully released.
 
-## Dataset
 
-Our dataset covers both image and video modalities and spans a series of fundamental visual reasoning tasks, including rule-based QA, open-ended QA, captioning, spatial grounding, temporal grounding, spatio-temporal grounding, tracking, and segmentation
-
-<div align="center">
-  <img src="https://github.com/tulerfeng/OneThinker/blob/main/assets/dataset.png?raw=true" alt="OneThinker Dataset Overview" width="90%">
-</div>
-
-To enable effective SFT initialization for reasoning, we leverage a strong proprietary model, Seed1.5-VL to produce CoT annotations.
-
-The `onethinker_rl_train.json` file is for RL training while `onethinker_sft_image.json` and `onethinker_sft_video.json` is for SFT cold start. The json files end with `_unsampled` are unsampled full set.
-
-## Sample Usage
-
-For inference on a single example, you may refer to:
-
-```bash
-python ./Evaluation/inference_single/inference.py
-```