Shuyan Ke — accepted AI-conference papers

2026

PixDLM: A Dual-Path Multimodal Language Model for UAV Reasoning Segmentation

Shuyan Ke, Yifan Mei, Changli Wu, Yonghan Zheng, Jiayi Ji, Liujuan Cao +1

CVPR 2026

Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including oblique viewpoints, ultra-high resolutions, and extreme scale variations. To address these issues, we formally define the UAV Reasoning Segmentation task

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2026

RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression

Zhengjia Zhong, Shuyan Ke, zaizhou lin, Jiaqi Song, Hongyi Lan, Hui Li

ICML 2026poster

Vector quantization is a fundamental tool for compressing high-dimensional embeddings, yet existing multi-codebook methods rely on static codebooks that limit expressiveness under heterogeneous data geometry. While recent dynamic quantizers like QINCo adapt codebooks to individual inputs and improve…

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