# On the effective transfer of knowledge from English to Hindi Wikipedia

arXiv: https://arxiv.org/abs/2412.05708 · HTML: https://mlsanity.com/paper/2412.05708/

## Key facts

- No citing papers in the map yet (data through 7 Oct 2026).
- Builds on 14 of its 38 references that are in the map.
- First posted on arXiv 7 Dec 2024.

## Builds on (most cited first, 14 of 14)

- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://mlsanity.com/paper/2010.00133/) (2020)
- [SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://mlsanity.com/paper/1911.03437/) (2019)
- [ChipNeMo: Domain-Adapted LLMs for Chip Design](https://mlsanity.com/paper/2311.00176/) (2023)
- [Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://mlsanity.com/paper/2402.14207/) (2024)
- [IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages](https://mlsanity.com/paper/2305.16307/) (2023)
- [Automatically Neutralizing Subjective Bias in Text](https://mlsanity.com/paper/1911.09709/) (2019)
- [Why the World Reads Wikipedia: Beyond English Speakers](https://mlsanity.com/paper/1812.00474/) (2018)
- [The Tower of Babel Meets Web 2.0: User-Generated Content and its Applications in a Multilingual Context](https://mlsanity.com/paper/1904.01689/) (2019)
- [Wikipedia Reader Navigation: When Synthetic Data Is Enough](https://mlsanity.com/paper/2201.00812/) (2022)
- [Language-Agnostic Modeling of Wikipedia Articles for Content Quality Assessment across Languages](https://mlsanity.com/paper/2404.09764/) (2024)
- [Global gender differences in Wikipedia readership](https://mlsanity.com/paper/2007.10403/) (2020)
- [Growing Wikipedia Across Languages via Recommendation](https://mlsanity.com/paper/1604.03235/) (2016)
- [Wikipedia and Westminster: Quality and Dynamics of Wikipedia Pages about UK Politicians](https://mlsanity.com/paper/2006.13400/) (2020)

## Abstract (arXiv)

Although Wikipedia is the largest multilingual encyclopedia, it remains inherently incomplete. There is a significant disparity in the quality of content between high-resource languages (HRLs, e.g., English) and low-resource languages (LRLs, e.g., Hindi), with many LRL articles lacking adequate information. To bridge these content gaps, we propose a lightweight framework to enhance knowledge equity between English and Hindi. In case the English Wikipedia page is not up-to-date, our framework extracts relevant information from external resources readily available (such as English books) and adapts it to align with Wikipedia's distinctive style, including its textitneutral point of view (NPOV) policy, using in-context learning capabilities of large language models. The adapted content is then machine-translated into Hindi for integration into the corresponding Wikipedia articles. On the other hand, if the English version is comprehensive and up-to-date, the framework directly transfers knowledge from English to Hindi. Our framework effectively generates new content for Hindi Wikipedia sections, enhancing Hindi Wikipedia articles respectively by 65% and 62% according to automatic and human judgment-based evaluations.