6 papers
WIMLE: Uncertainty-Aware World Models with IMLE for Sample-Efficient Continuous Control
Mehran Aghabozorgi, Alireza Moazeni, Yanshu Zhang +1
Model-based reinforcement learning promises strong sample efficiency but often underperforms in practice due to compounding model error, unimodal world models that average over mul…
SemVideo: Reconstructs What You Watch from Brain Activity via Hierarchical Semantic Guidance
Minghan Yang, Lan Yang, Ke Li +3
Reconstructing dynamic visual experiences from brain activity provides a compelling avenue for exploring the neural mechanisms of human visual perception. While recent progress in…
SynMind: Reducing Semantic Hallucination in fMRI-Based Image Reconstruction
Lan Yang, Minghan Yang, Ke Li +3
Recent advances in fMRI-based image reconstruction have achieved remarkable photo-realistic fidelity. Yet, a persistent limitation remains: while reconstructed images often appear…
DVGBench: Implicit-to-Explicit Visual Grounding Benchmark in UAV Imagery with Large Vision-Language Models
Yue Zhou, Jue Chen, Zilun Zhang +10
Remote sensing (RS) large vision-language models (LVLMs) have shown strong promise across visual grounding (VG) tasks. However, existing RS VG datasets predominantly rely on explic…
PerfGuard: A Performance-Aware Agent for Visual Content Generation
Zhipeng Chen, Zhongrui Zhang, Chao Zhang +5
The advancement of Large Language Model (LLM)-powered agents has enabled automated task processing through reasoning and tool invocation capabilities. However, existing frameworks…
MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation
Yuxiang Fu, Qi Yan, Lele Wang +2
In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans based on their past trajectories…