Summary of On the Effective Transfer Of Knowledge From English to Hindi Wikipedia, by Paramita Das et al.
On the effective transfer of knowledge from English to Hindi Wikipedia
by Paramita Das, Amartya Roy, Ritabrata Chakraborty, Animesh Mukherjee
First submitted to arxiv on: 7 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Information Retrieval (cs.IR); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a lightweight framework to bridge the content gaps between high-resource languages (HRLs) like English and low-resource languages (LRLs) like Hindi. The framework leverages large language models’ in-context learning capabilities to adapt information from external resources, such as English books, to align with Wikipedia’s neutral point of view (NPOV) policy. This adapted content is then machine-translated into Hindi for integration into corresponding Wikipedia articles. If the English version is comprehensive and up-to-date, the framework directly transfers knowledge from English to Hindi. The proposed framework effectively generates new content for Hindi Wikipedia sections, enhancing Hindi Wikipedia articles by 65% and 62% according to automatic and human judgment-based evaluations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper aims to make Wikipedia more complete by sharing information between languages. Right now, some languages have much better articles than others. To fix this, the researchers created a special way to take information from other sources, like books, and adapt it to fit Wikipedia’s style. They use big language models to help with this process. If the English version of an article is already good, they can just copy the knowledge over to Hindi. This new content makes Hindi articles 65% and 62% better, according to some tests. |
