---
configs:
- config_name: en-tl
  data_files:
  - split: train
    path: paracore_en-tl/*.parquet
- config_name: en-zh
  data_files:
  - split: train
    path: paracore_en-zh/*.parquet
- config_name: en-th
  data_files:
  - split: train
    path: paracore_en-th/*.parquet
- config_name: en-ru
  data_files:
  - split: train
    path: paracore_en-ru/*.parquet
- config_name: en-ja
  data_files:
  - split: train
    path: paracore_en-ja/*.parquet
- config_name: en-fr
  data_files:
  - split: train
    path: paracore_en-fr/*.parquet
- config_name: en-de
  data_files:
  - split: train
    path: paracore_en-de/*.parquet
- config_name: en-ar
  data_files:
  - split: train
    path: paracore_en-ar/*.parquet
---

# ParaRater: Enhancing Cross-Lingual Transfer in LLMs with Meta-Learning

**ParaRater** is a data selection method that enhances cross-lingual transfer by **selecting the most valuable parallel pairs**, forming high-impact parallel corpora with two meta-learned raters.

# ParaCore

This is the parallel data filtered by ParaRater. English data is sampled from Common Crawl. The translation is conducted using `Qwen3-8B`. Each language contains about 1 B tokens.