collaborators

7 papers

cs.CV2026

3D-DefectBench: A Controlled Factorial Study of Vision-Language Model Evaluation Pipelines for Fine-Grained 3D Generation Defects

Zhenyu Zhao, Nanshan Jia, Jihyeon Je +7

Automated evaluation is essential for scaling generative 3D systems, where exhaustive human review is costly and slow. However, the reliability of an automated judge depends on the…

stat.ME2026

HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data

Xinrui Ruan, Zhenyu Zhao, Waverly Wei +4

Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these "gold" labels are expensive to collect and limited in quantity. Orga…

cs.CV2026

DB-3DME: From Dataset to Benchmark for Human-aligned Automatic 3D Mesh Evaluation

Nanshan Jia, Zhenyu Zhao, Sui Huang +2

Recent advances in 3D generation have led to substantial improvements in realism, controllability, and efficiency, yet the evaluation of 3D assets remains underexplored. Existing e…

cs.IR2025

OneRec-V2 Technical Report

Guorui Zhou, Hengrui Hu, Hongtao Cheng +72

Recent breakthroughs in generative AI have transformed recommender systems through end-to-end generation. OneRec reformulates recommendation as an autoregressive generation task, a…

cs.IR2025

OneRec Technical Report

Guorui Zhou, Jiaxin Deng, Jinghao Zhang +62

Recommender systems have been widely used in various large-scale user-oriented platforms for many years. However, compared to the rapid developments in the AI community, recommenda…

cs.CV2025

Kwai Keye-VL 1.5 Technical Report

Biao Yang, Bin Wen, Boyang Ding +58

In recent years, the development of Large Language Models (LLMs) has significantly advanced, extending their capabilities to multimodal tasks through Multimodal Large Language Mode…