diff --git a/README.md b/README.md
index c05982f..893aad6 100644
--- a/README.md
+++ b/README.md
@@ -7,18 +7,18 @@
---
+ 🌻Acknowledgement •
🤗Benchmark •
🍎Demo •
🌟Overview •
🔧Installation •
⏩Quickstart •
🚩Citation •
- Acknowledgement •
- 🎉Contributors
+
-[](https://opensource.org/licenses/MIT)
+
@@ -26,8 +26,7 @@
## Table of Contents
-
-- 🚩Acknowledgement
+- 🌻Acknowledgement
- 🌟Overview
- Unified Multimodal Hallucination
- Dataset: MHalluBench Statistic
@@ -35,12 +34,14 @@
- 🔧Installation
- ⏩Quickstart
- 🚩Citation
-- 🎉Contributors
---
-## Acknowledgement
+## 🌻Acknowledgement
+
+Part implementation of this project were assisted and inspired by the related hallucination toolkits including [FactTool](https://github.com/GAIR-NLP/factool), [Woodpecker](https://github.com/BradyFU/Woodpecker), and others.
+This repository also benefits from the project from [mPLUG-Owl](https://github.com/X-PLUG/mPLUG-Owl), [MiniGPT-4](https://github.com/Vision-CAIR/MiniGPT-4), [LLaVA](https://github.com/haotian-liu/LLaVA), [GroundingDINO](https://github.com/IDEA-Research/GroundingDINO), and [MAERec ](https://github.com/Mountchicken/Union14M).
+We follow the same license for open-sourcing and thank them for their contributions to the community.
-Part implementation of this project were assisted and inspired by the related hallucination toolkits including [FactTool](https://github.com/GAIR-NLP/factool), [Woodpecker](https://github.com/BradyFU/Woodpecker), and others. We follow the same license for open-sourcing and thank them for their contributions to the community.
## 🌟Overview
@@ -55,7 +56,7 @@ A prerequisite for unified detection is the coherent categorization of the princ
-
+
**Figure 1:** Unified multimodal hallucination detection aims to identify and detect modality-conflicting hallucinations at
@@ -204,17 +205,9 @@ print(claim_list)
Please cite our repository if you use EasyDetect in your work.
```bibtex
-@article{DBLP:journals/corr/abs-2310-12086,
- author = {Xiang Chen and
- Duanzheng Song and
- Honghao Gui and
- Chengxi Wang and
- Ningyu Zhang and
- Jiang Yong and
- Fei Huang and
- Chengfei Lv and
- Dan Zhang and
- Huajun Chen},
+@article{chen23factchd,
+ author = {Xiang Chen and Duanzheng Song and Honghao Gui and Chengxi Wang and Ningyu Zhang and
+ Jiang Yong and Fei Huang and Chengfei Lv and Dan Zhang and Huajun Chen},
title = {FactCHD: Benchmarking Fact-Conflicting Hallucination Detection},
journal = {CoRR},
volume = {abs/2310.12086},
@@ -228,10 +221,19 @@ Please cite our repository if you use EasyDetect in your work.
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{chen2024unified,
- title={Unified Hallucination Detection for Multimodal Large Language Models},
- author={Chen, Xiang and Wang, Chenxi and Xue, Yida and Zhang, Ningyu and Yang, Xiaoyan and Li, Qiang and Shen, Yue and Gu, Jinjie and Chen, Huajun},
- journal={arXiv preprint arXiv:2402.03190},
- year={2024}
+ author = {Xiang Chen and Chenxi Wang and Yida Xue and Ningyu Zhang and Xiaoyan Yang and
+ Qiang Li and Yue Shen and Lei Liang and Jinjie Gu and Huajun Chen},
+ title = {Unified Hallucination Detection for Multimodal Large Language Models},
+ journal = {CoRR},
+ volume = {abs/2402.03190},
+ year = {2024},
+ url = {https://doi.org/10.48550/arXiv.2402.03190},
+ doi = {10.48550/ARXIV.2402.03190},
+ eprinttype = {arXiv},
+ eprint = {2402.03190},
+ timestamp = {Mon, 12 Feb 2024 13:36:38 +0100},
+ biburl = {https://dblp.org/rec/journals/corr/abs-2402-03190.bib},
+ bibsource = {dblp computer science bibliography, https://dblp.org}
}
```
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