6 papers
Why Far Looks Up: Probing Spatial Representation in Vision-Language Models
Cheolhong Min, Jaeyun Jung, Daeun Lee +5
Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D understanding or reliance on st…
IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
Sunghyun Baek, Jaemyung Yu, Seunghee Koh +3
Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. However, fully leveraging the rich repr…
UniSpector: Towards Universal Open-set Defect Recognition via Spectral-Contrastive Visual Prompting
Geonuk Kim, Minhoi Kim, Kangil Lee +5
Although industrial inspection systems should be capable of recognizing unprecedented defects, most existing approaches operate under a closed-set assumption, which prevents them f…
Convergent Functions, Divergent Forms
Hyeonseong Jeon, Ainaz Eftekhar, Aaron Walsman +3
We introduce LOKI, a compute-efficient framework for co-designing morphologies and control policies that generalize across unseen tasks. Inspired by biological adaptation -- where…
Tree-Guided Diffusion Planner
Hyeonseong Jeon, Cheolhong Min, Jaesik Park
Planning with pretrained diffusion models has emerged as a promising approach for solving test-time guided control problems. Standard gradient guidance typically performs optimally…
Learning to Continually Learn with the Bayesian Principle
Soochan Lee, Hyeonseong Jeon, Jaehyeon Son +1
In the present era of deep learning, continual learning research is mainly focused on mitigating forgetting when training a neural network with stochastic gradient descent on a non…