collaborators

5 papers

cs.LG2026

Looped World Models

Hongyuan Adam Lu, Z. L. Victor Wei, Qun Zhang +28

Current world models face a fundamental tension: faithful long-horizon simulation demands deep computation, but deeper models are expensive to deploy and prone to compounding error…

cs.CV2026

Exploring Adaptive Masked Reconstruction for Self-Supervised Skeleton-Based Action Recognition

Shengkai Sun, Zhiyong Cheng, Zefan Zhang +3

Recently, masked skeleton reconstruction models have emerged as strong action representation learners, driving significant progress in self-supervised skeleton-based action recogni…

cs.CL2026

SLoW: Select Low-frequency Words! Automatic Dictionary Selection for Translation on Large Language Models

Hongyuan Lu, Zixuan Li, Zefan Zhang +1

There are more than 7,000 languages around the world, and current Large Language Models (LLMs) only support hundreds of languages. Dictionary-based prompting methods can enhance tr…

cs.CV2026

VERHallu: Evaluating and Mitigating Event Relation Hallucination in Video Large Language Models

Zefan Zhang, Kehua Zhu, Shijie Jiang +3

Video Large Language Models (VideoLLMs) exhibit various types of hallucinations. Existing research has primarily focused on hallucinations involving the presence of events, objects…

cs.CV2025

Towards Efficient General Feature Prediction in Masked Skeleton Modeling

Shengkai Sun, Zefan Zhang, Jianfeng Dong +3

Recent advances in the masked autoencoder (MAE) paradigm have significantly propelled self-supervised skeleton-based action recognition. However, most existing approaches limit rec…