arXiv subjects

Luo Yang

Publications and source records attributed to Luo Yang.

3 recordsLinked to original sources

arXiv2026

GateDiffInt: Gate-Mediated Controllable Diffusion and Multi-Intent LLM Distillation for User Behavior Modeling

Existing ranking models encode intent only implicitly, making it hard to disentangle structured intents of varying strength and temporal scale. Noise and intent in behavior sequences are mutually reinforcing---we call this Noise--Intent Coupling (NIC). Noise dilutes true intents, while the lack of structured intent priors leaves denoising without a clear target. To address NIC, we propose GateDiffInt, an intent interaction framework for industrial ranking. It uses the final conversion signal to jointly align sequence denoising and intent extraction. GateDiffInt applies a controllable forward diffusion process with dual gating to enhance and denoise behavior sequences. A large language model then acts as teacher to distill four structured intents---long-term, short-term, latent, and conversion into a lightweight student model. The enhanced sequence and structured intent representations are deeply fused via attention to produce intent-aware representations for conversion-rate prediction. Extensive experiments on public and large-scale industrial datasets show consistent gains over strong baselines. In online A/B tests serving hundreds of millions of daily active users, GateDiffInt delivers substantial GMV improvements and has been deployed to primary traffic, confirming both effectiveness and production readiness.

cs.IR↗

arXiv2025

ArchGPT: Understanding the World's Architectures with Large Multimodal Models

Architecture embodies aesthetic, cultural, and historical values, standing as a tangible testament to human civilization. Researchers have long leveraged virtual reality (VR), mixed reality (MR), and augmented reality (AR) to enable immersive exploration and interpretation of architecture, enhancing accessibility, public understanding, and creative workflows around architecture in education, heritage preservation, and professional design practice. However, existing VR/MR/AR systems are often developed case-by-case, relying on hard-coded annotations and task-specific interactions that do not scale across diverse built environments. In this work, we present ArchGPT, a multimodal architectural visual question answering (VQA) model, together with a scalable data-construction pipeline for curating high-quality, architecture-specific VQA annotations. This pipeline yields Arch-300K, a domain-specialized dataset of approximately 315,000 image-question-answer triplets. Arch-300K is built via a multi-stage process: first, we curate architectural scenes from Wikimedia Commons and filter unconstrained tourist photo collections using a novel coarse-to-fine strategy that integrates 3D reconstruction and semantic segmentation to select occlusion-free, structurally consistent architectural images. To mitigate noise and inconsistency in raw textual metadata, we propose an LLM-guided text verification and knowledge-distillation pipeline to generate reliable, architecture-specific question-answer pairs. Using these curated images and refined metadata, we further synthesize formal analysis annotations-including detailed descriptions and aspect-guided conversations-to provide richer semantic variety while remaining faithful to the data. We perform supervised fine-tuning of an open-source multimodal backbone ,ShareGPT4V-7B, on Arch-300K, yielding ArchGPT.

cs.GR↗

arXiv2019

Chaos Phase Induced Mass-producible Monolayer Two-dimensional Material

Crystal phase is well studied and presents a periodical atom arrangement in three dimensions lattice, but the "amorphous phase" is poorly understood. Here, by starting from cage-like bicyclocalix[2]arene[2]triazines building block, a brand-new 2D MOF is constructed with extremely weak interlaminar interaction existing between two adjacent 2D-crystal layer. Inter-layer slip happens under external disturbance and leads to the loss of periodicity at one dimension in the crystal lattice, resulting in an interim phase between the crystal and amorphous phase - the chaos phase, non-periodical in microscopic scale but orderly in mesoscopic scale. This chaos phase 2D MOF is a disordered self-assembly of black-phosphorus like 3D-layer, which has excellent mechanical-strength and a thickness of 1.15 nm. The bulky 2D-MOF material is readily to be exfoliated into monolayer nanosheets in gram-scale with unprecedented evenness and homogeneity, as well as previously unattained lateral size (>10 um), which present the first mass-producible monolayer 2D material and can form wafer-scale film on substrate.

cond-mat.mtrl-sci↗