Teaching 7,000 Languages: How LASA’s Semantic Bottleneck Enables Multilingual LLM Safety

The paper reveals a language‑agnostic "semantic bottleneck" layer inside large language models and introduces LASA, a three‑step framework that locates this layer, extracts safety signals with a lightweight interpreter, and injects them via KTO loss, dramatically improving multilingual safety without per‑language data collection.

AI safetyLASALLM safety

0 likes · 8 min read

Teaching 7,000 Languages: How LASA’s Semantic Bottleneck Enables Multilingual LLM Safety

DataFunTalk

Jul 18, 2025 · Artificial Intelligence

How Alibaba Tackles Low-Resource Language Data for Multilingual LLMs

Alibaba International’s senior data science expert explains a systematic five‑strategy solution—data acquisition, augmentation, quality optimization, engineering pipeline, and evaluation loop—to overcome data scarcity, high annotation cost, and processing challenges for low‑resource languages in multilingual large language models.

AIdata engineeringlow-resource languages

0 likes · 13 min read

How Alibaba Tackles Low-Resource Language Data for Multilingual LLMs

DataFunSummit

Jul 13, 2025 · Artificial Intelligence

How Alibaba Tackles Low-Resource Language Data for Multilingual LLMs

In this interview, Alibaba International’s senior data‑science expert Li Haijun explains the challenges of low‑resource languages for multilingual large models and details a five‑step data‑collection, augmentation, quality‑optimization, engineering, and evaluation framework that powers their cross‑border e‑commerce AI applications.

AIlarge language modelslow-resource languages

0 likes · 12 min read