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  • AI
    Artificial Intelligence

    Benefits of Using LiteLLM for Your LLM Apps

    Artificial Intelligence

    5 Fun Generative AI Projects for Absolute Beginners

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    iOS 18.6 release notes: Here’s what’s coming in next iPhone update

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    Start generating free AI art on iPhone with Adobe Firefly

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  • ComputerWorld
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    Trump gets aggressive with new US AI action plan

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    Clorox sues Cognizant for $380M over alleged helpdesk failures in cyberattack

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    Kandji helps secure Apple enterprise with Vulnerability Response

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    Alibaba rolls out new AI coding model Qwen3-Coder, says it’s their most powerful

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    Microsoft will stop using Chinese workers on US DoD systems

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    Microsoft SharePoint zero-day breach hits on-prem servers

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    Retro Rewind: Computer Gaming World Magazine Issue 73 December 1998

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    Retro Rewind: Electronic Gaming Monthly Magazine Number 55 February 1994

    Retro Rewind: Electronic Gaming Monthly Magazine Number 55 February 1994

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  • Apple
    iOS 26: Here’s the list of iPhone models compatible with the update

    iOS 26: Here’s the list of iPhone models compatible with the update

    iOS 26 beta release date, latest, how to get public and dev iOS beta

    iOS 26 beta release date, latest, how to get public and dev iOS beta

    Apple launches AirPods firmware public beta for iOS 26, here’s what’s new

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    Apple solves its social media fragmentation problem with ‘In the Loop’

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    iOS 18.6 release notes: Here’s what’s coming in next iPhone update

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    Epic Games annoyed by UK’s alt-App Store progress

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    Start generating free AI art on iPhone with Adobe Firefly

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  • ComputerWorld
    Apple wants to build a circular manufacturing economy

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    Trump gets aggressive with new US AI action plan

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    Clorox sues Cognizant for $380M over alleged helpdesk failures in cyberattack

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    Kandji helps secure Apple enterprise with Vulnerability Response

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    Alibaba rolls out new AI coding model Qwen3-Coder, says it’s their most powerful

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  • Gaming
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Home AI

EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing

AI by AI
April 16, 2025
in AI
Reading Time: 4 mins read
129
A A
0

2025-04-14 20:00:00
machinelearning.apple.com

Diffusion transformers have been widely adopted for text-to-image synthesis. While scaling these models up to billions of parameters shows promise, the effectiveness of scaling beyond current sizes remains underexplored and challenging. By explicitly exploiting the computational heterogeneity of image generations, we develop a new family of Mixture-of-Experts (MoE) models (EC-DIT) for diffusion transformers with expert-choice routing. EC-DIT learns to adaptively optimize the compute allocated to understand the input texts and generate the respective image patches, enabling heterogeneous computation aligned with varying text-image complexities. This heterogeneity provides an efficient way of scaling EC-DIT up to 97 billion parameters and achieving significant improvements in training convergence, text-to-image alignment, and overall generation quality over dense models and conventional MoE models. Through extensive ablations, we show that EC-DIT demonstrates superior scalability and adaptive compute allocation by recognizing varying textual importance through end-to-end training. Notably, in text-to-image alignment evaluation, our largest models achieve a state-of-the-art GenEval score of 71.68% and still maintain competitive inference speed with intuitive interpretability.

Figure 1: Expert-choice routing for Heterogenous compute allocation. EC-DiT leverages sequence-wide information to route toeksn adaptively. This dynamic routing allocates more computation to detailed areas (like the space station and moon) while reducing it for simpler regions like the background.

†Work done during an Apple internship.

‡Georgia Institute of Technology

Source Link



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