Update task categories to include image-text-to-text

README.md

@@ -5,16 +5,18 @@ language:
 - en
 license: cc-by-4.0
 multilinguality: monolingual
-pretty_name: SciVer
 size_categories:
 - 1K<n<10K
 source_datasets:
 - original
 task_categories:
 - text-classification
+- image-text-to-text
 task_ids:
 - fact-checking
+pretty_name: SciVer
 ---
+
 # SCIVER: A Benchmark for Multimodal Scientific Claim Verification
 
 <p align="center">
@@ -23,7 +25,6 @@ task_ids:
   <a href="https://huggingface.co/datasets/chengyewang/SciVer">🤗 Data</a>
 </p>
 
-
 ## 📰 News
 - [May 15, 2025] SciVer has been accepted by ACL 2025 Main!
 
@@ -47,7 +48,7 @@ task_ids:
   - Analytical
 - 📚 Context includes **text paragraphs, multiple tables, and charts**
 - 🔍 Labels: `Entailed`, `Refuted`
-- 📈 Evaluated across **21 leading foundation models**, including GPT-4o, Gemini, Claude 3.5, Qwen2.5-VL, LLaMA-3.2-Vision, etc.
+- 📈 Evaluated across **21 leading foundation models**, including o4-mini, GPT-4o, Gemini, Claude 3.5, Qwen2.5-VL, LLaMA-3.2-Vision, etc.
 - ⚖️ Includes **step-by-step rationale** and **automated accuracy evaluation**
 
 ------
@@ -65,8 +66,9 @@ Each SCIVER sample includes:
 
 1. **Direct Reasoning** – extract simple facts
 2. **Parallel Reasoning** – synthesize info from multiple sources
-3. **Sequential Reasoning** – perform step-by-step inference
-4. **Analytical Reasoning** – apply domain expertise and logic
+3. **Sequential Reasoning** – synthesize info from multiple sources
+4. **Sequential Reasoning** – perform step-by-step inference
+5. **Analytical Reasoning** – apply domain expertise and logic
 
 ------
 
@@ -153,5 +155,4 @@ If you use our work and are inspired by our work, please consider cite us:
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2506.15569}, 
 }
-```
-
+```