3 papers
cs.RO2026
Test-Time Adaptation for Tactile-Vision-Language Models
Chuyang Ye, Haoxian Jing, Qinting Jiang +4
Tactile-vision-language (TVL) models are increasingly deployed in real-world robotic and multimodal perception tasks, where test-time distribution shifts are unavoidable. Existing…
cs.IR2025
Exploring Test-time Scaling via Prediction Merging on Large-Scale Recommendation
Fuyuan Lyu, Zhentai Chen, Jingyan Jiang +4
Inspired by the success of language models (LM), scaling up deep learning recommendation systems (DLRS) has become a recent trend in the community. All previous methods tend to sca…
cs.LG2025
MoETTA: Test-Time Adaptation Under Mixed Distribution Shifts with MoE-LayerNorm
Xiao Fan, Jingyan Jiang, Zhaoru Chen +6
Test-Time adaptation (TTA) has proven effective in mitigating performance drops under single-domain distribution shifts by updating model parameters during inference. However, real…