# Sakana AI — TAID: A Novel Method for Efficient Knowledge Transfer from Large Language Models to Small Language Models

- Company: Sakana AI (sakana.ai)
- Announced: 2025-02-24T15:00:00+00:00
- Category: research-paper
- Subject: Sakana models
- Models affected: TAID-LLM-1.5B, TinySwallow-1.5B
- Source: https://sakana.ai/taid
- Record: https://forck.live/items/4723-taid-a-novel-method-for-efficient-knowledge-transfer-from-large-language

Sakana AI introduces TAID, a novel knowledge distillation method for transferring knowledge from large language models to small ones. They release two models: TAID-LLM-1.5B (English) and TinySwallow-1.5B (Japanese), with TinySwallow-1.5B achieving state-of-the-art performance among similar-sized models. The research is accepted as a Spotlight paper at ICLR 2025.

## Evidence

Verbatim from https://sakana.ai/taid:

> Key highlights of this release:
> 
> We introduce TAID (Temporally Adaptive Interpolated Distillation), a novel knowledge distillation method that enables efficient transfer of knowledge from large language models to smaller ones.
> 
> In collaboration with the Institute of Science Tokyo, we have developed TinySwallow-1.5B, a compact Japanese language model that enables offline execution on edge devices like smartphones.
> 
> Our research has been accepted as a Spotlight paper at ICLR, a top international conference in machine learning.

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