MIT introduces Self-Distillation Fine-Tuning to reduce catastrophic forgetting; it uses student-teacher demonstrations and needs 2.5x compute.

Knowledge Distillation (KD) has been established as an effective technique for reducing the resource requirements of models when tackling computer vision tasks. Prior work has studied how to distill ...

Discover how SharePoint’s 25‑year legacy powers Microsoft 365 Copilot, Work IQ, and AI‑driven knowledge for organizations worldwide.

Microsoft researchers have developed On-Policy Context Distillation (OPCD), a training method that permanently embeds ...

Anthropic alleges Chinese AI labs including DeepSeek, Moonshot and MiniMax used fake accounts to distill Claude, raising new concerns about AI model theft, proxies and U.S. export controls.

Anthropic said it is investing heavily in defences designed to make distillation attacks harder to execute and easier to identify.

This repository showcases a complete pipeline for high-quality Image Sharpening using Knowledge Distillation (KD). A pretrained Restormer model acts as the high-capacity teacher, while a lightweight ...

The troubleshooting methods described here can help engineers to understand operational realities when “running blind” in complex distillation processes One of the most critical aspects in ethanol ...

Netflix’s latest Korean blockbuster The Great Flood has surged to the top of the platform’s global charts for nonglobal films, but audiences are divided over its cryptic ending and philosophical twist ...

Abstract: Online action detection and anticipation aim to understand current or upcoming actions in video streams. In industry, current artificial neural network (ANN)-based methods suffer from ...

Abstract: Knowledge distillation (KD) improves the performance of a low-complexity student model with the help of a more powerful teacher. The teacher in KD is a black-box model’ imparting knowledge ...