Huawei · 9.1.4.2

Huawei argues that MI-Option 1 is inapplicable to the revised WID scope for two-sided models and proposes excluding it from further discussion. For MI-Option 2 and 3, Huawei specifies that model identification relies on the delivery of Dataset IDs or Model IDs alongside their respective data or parameters, with detailed meta-information requirements for quantization and structure. Regarding model transfer Case z4, Huawei presents a technical case against immediate standardization of model structures due to proprietary concerns and performance limits, proposing that partial parameter transfer and Model ID composition be deferred to RAN2. For UE-trained models (Class 2), Huawei opposes the necessity of Case z1, proposing Case y as the baseline to avoid offline cross-vendor collaboration burdens. Finally, Huawei argues that UE-side data collection mechanisms are out of RAN1 scope and proposes lowering the priority of this study item.

Huawei advocates FOR focusing model identification discussions exclusively on two-sided models while eliminating MI-Option 1 from scope, and pushes FOR using Case y as baseline for UE-side training scenarios. They are AGAINST pursuing Case z1 for UE-side trained models due to cross-vendor collaboration burdens and lack of benefits over Case y, and AGAINST prioritizing UE data collection mechanisms at RAN1 since it's outside their scope.