[data] fixing visual

src/about.py

@@ -21,52 +21,47 @@ NUM_FEWSHOT = 0 # Change with your few shot
 
 
 # Your leaderboard name
-TITLE = """<h1 align="center" id="space-title">🪷 LOTUS: A Leaderboard for Detailed Image Captioning  from Quality to Societal Bias and User Preferences</h1>"""
+TITLE = """
+<div align="center">
+    <h1>🪷 LOTUS: Detailed LVLM Evaluation from Quality to Societal Bias</h1>
+</div>
+"""
 
 # What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
-(ACL 2025 Industry Track) Large Vision-Language Models (LVLMs) have transformed image captioning, shifting from concise captions to detailed, context-rich descriptions. We introduce LOTUS, a unified leaderboard for evaluating such detailed captions, addressing three main gaps in existing evaluation approaches: lack of standardized criteria, absence of bias-aware assessments, and evaluations that disregard user preferences.
-"""
 
-# Which evaluations are you running? how can people reproduce what you have?
-LLM_BENCHMARKS_TEXT = f"""
-## How it works
+**LOTUS** (short for **L**arge Language Model (**L**L**M**) E**o**s E**t**hos and Pa**u**to**s** Benchmark) is a new comprehensive benchmark for Large Vision Language Models (LVLMs). 
 
-## Reproducibility
-To reproduce our results, here is the commands you can run:
+For more information, check out our [paper](https://arxiv.org/abs/2402.10542) and the [project page](https://lotus-benchmark.github.io/).
 
 """
 
-EVALUATION_QUEUE_TEXT = """
-## Some good practices before submitting a model
-
-### 1) Make sure you can load your model and tokenizer using AutoClasses:
-```python
-from transformers import AutoConfig, AutoModel, AutoTokenizer
-config = AutoConfig.from_pretrained("your model name", revision=revision)
-model = AutoModel.from_pretrained("your model name", revision=revision)
-tokenizer = AutoTokenizer.from_pretrained("your model name", revision=revision)
-```
-If this step fails, follow the error messages to debug your model before submitting it. It's likely your model has been improperly uploaded.
+# Which evaluations are you running? how can people reproduce what you have?
+LLM_BENCHMARKS_TEXT = """
+Details about the LLM benchmarks will go here.
+"""
 
-Note: make sure your model is public!
-Note: if your model needs `use_remote_code=True`, we do not support this option yet but we are working on adding it, stay posted!
+EVALUATION_QUEUE_TEXT = """
+## Evaluation Queue and Submission
 
-### 2) Convert your model weights to [safetensors](https://huggingface.co/docs/safetensors/index)
-It's a new format for storing weights which is safer and faster to load and use. It will also allow us to add the number of parameters of your model to the `Extended Viewer`!
+Models are evaluated on the private test set of COCO Captions, and results are protected from misuse.
 
-### 3) Make sure your model has an open license!
-This is a leaderboard for Open LLMs, and we'd love for as many people as possible to know they can use your model 🤗
+**To submit your model for evaluation, please follow these steps:**
 
-### 4) Fill up your model card
-When we add extra information about models to the leaderboard, it will be automatically taken from the model card
+1. **Prepare your model's predictions**: Ensure your model's predictions are in the same format as the COCO Captions [dataset](https://cocodataset.org/#format-data).
+2. **Submit via our form**: Fill out the [submission form](https://forms.gle/your_form_link_here) with your model details and prediction file.
+3. **Wait for results**: The evaluation may take some time. Results will be updated on the leaderboard.
 
-## In case of model failure
-If your model is displayed in the `FAILED` category, its execution stopped.
-Make sure you have followed the above steps first.
-If everything is done, check you can launch the EleutherAIHarness on your model locally, using the above command without modifications (you can add `--limit` to limit the number of examples per task).
+For any issues or questions, please open an issue on our [GitHub repository](https://github.com/lotus-benchmark/lotus).
 """
 
-CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
-CITATION_BUTTON_TEXT = r"""
+CITATION_BUTTON_LABEL = "BibTeX" # Keep this label or change if needed
+
+CITATION_BUTTON_TEXT = """
+@inproceedings{hirota2025lotus,
+  author    = {Yusuke Hirota and Boyi Li and Ryo Hachiuma and Yueh-Hua Wu and Boris Ivanovic and Yuta Nakashima and Marco Pavone and Yejin Choi and Yu-Chiang Frank Wang and Huck Yang},
+  title     = {LOTUS: {A} Leaderboard for Detailed Image Captioning from Quality to Societal Bias and User Preferences},
+  booktitle = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL)},
+  year      = {2025}
+}
 """