arXiv AI By Dalton Raphael Harmsen, Swier Garst, Thomas van Osch, Zar\`e Palanciyan, Joaquin Vanschoren

Zero-Compute Cross-Lingual Transferability Estimation Using Typological Feature Proxies

Read the original on arXiv AI →

The Flow has not summarised this story yet — read it at arXiv AI.

arXiv AI
1d ago

Linguistic Loopholes in LLM Unlearning: From a 174-Language Benchmark to Coverage-Aware Unlearning

The paper introduces the problem of cross‑lingual loopholes in large language model (LLM) unlearning, where forgetting a fact in one language can leave it accessible in others. It presents a new 174‑language benchmark, the Cross‑Lingual Unlearning Tensor, and proposes COVER, a method that selects a subset of source languages to maximize unlearning coverage under a language budget. Experiments show COVER reduces residual knowledge by 7.8–27.3% compared to uniform selection and works on both synthetic and real low‑resource news data.

By Tyler Skow, Shravan Chaudhari, Rama Chellappa, Abhay Yadav