This is an official Pytorch implementation of "TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models".

2025年1月28日 · To address these issues, we introduce Temporally Adaptive Interpolated Distillation (TAID), a novel knowledge distillation approach that dynamically interpolates student and teacher distributions through an adaptive intermediate distribution, gradually shifting from the student's initial distribution towards the teacher's distribution.

We introduce TAID (Section 3), a new knowledge distillation method that reimagines the distillation process as a dynamic, adaptive knowledge transfer from student to teacher distributions. This approach addresses common challenges in distilling large language models.

we showcase TAID’s practical impact by developing two state-of-the-art compact foundation models: TAID-LLM-1.5B for language tasks and TAID-VLM-2B for vision-language tasks. These results demonstrate TAID’s effectiveness in creat-ing high-performing and efficient models, advancing the development of more accessible AI technologies. 1 ...

2025年2月25日 · TAID represents a new approach to knowledge distillation, a technique for transferring knowledge from LLMs to SLMs. Unlike existing distillation methods, TAID achieves more efficient and effective knowledge transfer by gradually transferring LLM knowledge based on the student model’s learning progress.

we experimentally reveal TAID’s robustness to capacity gaps (Section 6.3.2), and its ability to bal-ance between mode averaging and mode collapse, unlike existing KD methods (Section 6.3.3). •We demonstrate TAID’s practical impact by developing two state-of …

2025年1月22日 · TL;DR: We propose TAID, a novel knowledge distillation method for language models that uses a time-dependent intermediate distribution to dynamically bridge student-teacher gaps, addressing common challenges in distilling large language models.

2025年1月30日 · To address these issues, we introduce Temporally Adaptive Interpolated Distillation (TAID), a novel knowledge distillation approach that dynamically interpolates student and teacher distributions through an adaptive intermediate distribution, gradually shifting from the student's initial distribution towards the teacher's distribution.

TAID International is a globally recognized exporter of premium agricultural products, committed to delivering quality, sustainability, and excellence. Based on a foundation of trust and integrity, we specialize in sourcing and exporting a diverse range of agricultural commodities, including fresh produce, grains, pulses, and spices, to meet ...

2025年2月18日 · What is Temporally Adaptive Interpolated Distillation (TAID)? TAID enhances LLM distillation by dynamically interpolating student-teacher distributions, solving capacity gaps and mode collapse. Large language models (LLMs) have revolutionised AI but they face significant deployment challenges because of their size.