Update README.md

README.md

@@ -28,4 +28,174 @@ configs:
   data_files:
   - split: eval
     path: metadata/vimu_ss.jsonl
----
+---
+
+<div align="center">
+
+<img src="assets/overall.png" width="100%"/>
+
+# ViMU: Benchmarking Video Metaphorical Understanding
+
+[![Project Page](https://img.shields.io/badge/Project-Page-blue?style=for-the-badge&logo=googlechrome&logoColor=white)](https://liqiiiii.github.io/Video-Metaphorical-Understanding/)
+[![arXiv](https://img.shields.io/badge/arXiv-Paper-b31b1b?style=for-the-badge&logo=arxiv&logoColor=white)](https://arxiv.org/abs/2605.14607)
+[![Hugging Face](https://img.shields.io/badge/HuggingFace-Dataset-yellow?style=for-the-badge&logo=huggingface&logoColor=black)](https://huggingface.co/datasets/LIQIIIII/ViMU)
+
+
+[Qi Li](https://liqiiiii.github.io/), [Xinchao Wang](https://sites.google.com/site/sitexinchaowang/)<sup>*</sup>
+
+<sup>*</sup>Corresponding author
+
+[xML Lab](https://sites.google.com/view/xml-nus), National University of Singapore
+
+</div>
+
+This repository contains the evaluation scripts for ViMU, a benchmark for video metaphorical understanding. The code evaluates multimodal models on four tasks:
+
+1. Open-ended interpretation (OE)
+2. Evidence grounding (EG)
+3. Rhetoric mechanism identification (RM)
+4. Social value signal identification (SV)
+
+## Directory Structure
+
+Expected project structure:
+
+```text
+ViMU/
+├── videos/
+│   ├── vimu_000001.mp4
+│   └── ...
+├── metadata/
+│   ├── vimu_oe.jsonl
+│   ├── vimu_eg.jsonl
+│   ├── vimu_ss.jsonl
+│   ├── video_evidence.jsonl
+│   └── cache/
+├── scripts/
+│   ├── 00-vimu_oe.py
+│   ├── 01-vimu_oe_judge.py
+│   ├── 02-vimu_oe_score.py
+│   ├── 10-vimu_eg.py
+│   ├── 11-vimu_eg_score.py
+│   ├── 20-vimu_ss.py
+│   ├── 21-vimu_ss_score.py
+│   └── utils.py
+└── output/
+````
+
+## Setup
+
+Install dependencies:
+
+```bash
+pip install openai requests numpy pandas tqdm
+```
+
+Depending on the models used, additional API keys may be required.
+
+Set API keys:
+
+```bash
+export OPENAI_API_KEY="your_openai_key"
+export OPENROUTER_API_KEY="your_openrouter_key"
+export GOOGLE_API_KEY="your_google_key"
+```
+
+Not all keys are required if you only run a subset of models.
+
+## Path Configuration
+
+Before running, edit each script and set:
+
+```python
+PROJECT_ROOT = "/Your/Path/To/ViMU"
+```
+
+## Recommended Running Order
+
+For a full evaluation, run:
+
+```bash
+# Open-ended interpretation
+python scripts/00-vimu_oe.py
+python scripts/01-vimu_oe_judge.py
+python scripts/02-vimu_oe_score.py
+
+# Evidence grounding
+python scripts/10-vimu_eg.py
+python scripts/11-vimu_eg_score.py
+
+# Structured subtext tasks without guidance
+python scripts/20-vimu_ss.py --prompt_mode without_guidance
+python scripts/21-vimu_ss_score.py --prompt_mode without_guidance
+
+# Structured subtext tasks with guidance
+python scripts/20-vimu_ss.py --prompt_mode with_guidance
+python scripts/21-vimu_ss_score.py --prompt_mode with_guidance
+```
+
+## Model Configuration
+
+Models are configured in the `MODEL_SPECS` list inside the inference scripts.
+
+To enable or disable a model, edit:
+
+```python
+"enabled": True
+```
+
+or
+
+```python
+"enabled": False
+```
+
+For OpenRouter models, make sure the model ID and API key are valid.
+
+## Output Files
+
+The main output files are:
+
+```text
+output/vimu_oe_summary.json
+output/vimu_eg_summary.json
+output/vimu_ss_without_guidance_summary.json
+output/vimu_ss_with_guidance_summary.json
+```
+
+These files contain aggregated evaluation results.
+
+## Scoring Rules
+
+### Open-ended Interpretation
+
+Open-ended answers are evaluated using an LLM-as-a-judge protocol. The judge scores semantic understanding based on:
+
+```text
+core intent
+implicit signal
+target or social meaning
+hallucination penalty
+literal-only penalty
+```
+
+Evidence grounding is scored as a multi-label prediction problem. If the prediction contains any incorrect option, the score is 0. Otherwise, if the prediction is a subset of the gold answer, the score is: `score = number of correctly selected options / number of gold options`. Rhetoric and social value tasks use the same multi-label scoring rule. If no incorrect option is selected; otherwise: `score = 0`.
+
+## Notes
+
+The dataset contains socially sensitive video memes. The benchmark is intended for research use only.
+
+## Citation
+
+If you finding our work interesting or helpful to you, please cite as follows:
+
+```
+@article{li2026vimu,
+  title={ViMU: Benchmarking Video Metaphorical Understanding},
+  author={Li, Qi and Wang, Xinchao},
+  journal={arXiv preprint arXiv:2605.14607},
+  year={2026}
+}
+```
+
+