ProMax uses dense retrieval and dual distribution reshaping on LLM-derived profiles to guide recommender models toward preferences for unseen items, substantially boosting base model performance on public datasets.
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2026 2verdicts
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DealMaTe proposes a simplified diffusion framework for material transfer that injects multi-dimensional 3D conditions via Multi-Dim 3D Shader LoRA and Shader Causal Mutual Attention with KV caching.
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ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems
ProMax uses dense retrieval and dual distribution reshaping on LLM-derived profiles to guide recommender models toward preferences for unseen items, substantially boosting base model performance on public datasets.
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DealMaTe: Multi-Dimensional Material Transfer via Diffusion Transformer
DealMaTe proposes a simplified diffusion framework for material transfer that injects multi-dimensional 3D conditions via Multi-Dim 3D Shader LoRA and Shader Causal Mutual Attention with KV caching.