Update README.md

README.md

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 MEET-MR provides high-quality human-annotated benchmarks and models to bridge the evaluation gap for the English–Thai language pair. Our work focuses on fine-grained error analysis (MQM) and human preference alignment.
 
-### 🛠 Key Resources
-*   **[MEET-MR Dataset](https://huggingface.co/datasets/MEET-MR/MEET-MR):** 20k+ segments across 9 domains with MQM labels and 10-way human rankings.
-*   **[Evaluation Models](https://huggingface.co/MEET-MR/COMET-21-MEET-MR):** Fine-tuned COMET metrics optimized for English-Thai quality estimation.
+### Resources
+- [Dataset](https://huggingface.co/datasets/MEET-MR/MEET-MR): 20k segments with MQM and human rankings.
+- [Models](https://huggingface.co/MEET-MR/COMET-21-MEET-MR): Optimized COMET for English-Thai quality estimation.
 
-### 📖 Publication
-Introduced at **EACL 2026**: 
-*"Machine Translation Evaluation English-Thai MQM Ranking Dataset"*  
-[Read the Paper](https://openreview.net/forum?id=0IbK0VeN8y)
+### Publication
+EACL 2026: Machine Translation Evaluation English-Thai MQM Ranking Dataset.
+[OpenReview Paper](https://openreview.net/forum?id=0IbK0VeN8y)
 
-### 🏫 Affiliations
-*   Department of Computer Engineering, **Chulalongkorn University**
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 *For inquiries or collaborations, please reach out via our primary repository issues or the contacts listed in our paper.*