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New framework ReDIL-GNN tackles domain shift in circuit GNNs

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced ReDIL-GNN, a novel framework designed to address domain shift in circuit graph neural networks (GNNs) that arises from logic resynthesis. This framework enables GNNs to adapt to new synthesis styles while retaining performance on previously encountered domains. To guide adaptation, ReDIL-GNN incorporates the Resynthesis Adaptability Index (RAI), a score that assesses the need for adaptation, recoverability, structural coverage, and update compatibility. AI

IMPACT This framework could improve the robustness and adaptability of GNNs in dynamic environments like circuit design, enabling more efficient and reliable model updates.

RANK_REASON The cluster contains a research paper detailing a new framework and methodology for graph neural networks.

Read on arXiv cs.NE (Neural & Evolutionary) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework ReDIL-GNN tackles domain shift in circuit GNNs

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The cluster contains a research paper detailing a new framework and methodology for graph neural networks.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Rupesh Raj Karn, Johann Knechtel, Ozgur Sinanoglu ·

    ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks

    arXiv:2609.18595v1 Announce Type: new Abstract: Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit graph neural networks (GNNs) without changing task labels. To study this settin…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Ozgur Sinanoglu ·

    ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks

    Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit graph neural networks (GNNs) without changing task labels. To study this setting, we introduce ReDIL-GNN, a resynthesis domain-…

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