3 papers
cs.MM2026
Design-MLLM: A Reinforcement Alignment Framework for Verifiable and Aesthetic Interior Design
Yuxuan Yang, Xiaotong Mao, Jingyao Wang
Interior design is a requirements-to-visual-plan generation process that must simultaneously satisfy verifiable spatial feasibility and comparative aesthetic preferences. While rec…
cs.IR2026
Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation
Yifan Jin, Qirui Ji, Bin Qin +4
Graph foundation models (GFMs) emerged as a dominant paradigm in graph representation learning by leveraging large-scale pre-training for cross-domain inference. However, the param…
cs.CV2026
Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models
Zehua Zang, Xi Wang, Fuchun Sun +4
Vision-Language-Action models (VLAs) achieve remarkable performance in sequential decision-making but remain fragile to subtle environmental shifts, such as small changes in object…