1 citations · 1 across the 4 of their papers we have counts for
6 papers
When Repeated Measurements Hurt Tabular Foundation Models
Yixiang Liu, Ruizhe Deng, Bibhas Chakraborty +2
Tabular foundation models (TFMs) achieve state-of-the-art performance on IID benchmarks, but how do they respond to repeated measurements at the same inputs? Across six TFMs, synth…
Routing by Reasoning Need: Trajectory-Aware Decoding Control for Diffusion Vision-Language Models
Yixiang Liu, Zhongxing Xu, Zhonghua Wang +1
Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and controlled at inference time. Ho…
CRISP: Constrained Refinement via Iterative Squeezing Process for Robust Medical Image Segmentation under Domain Shift
Yizhou Fang, Pujin Cheng, Yixiang Liu +2
Distribution shift in medical imaging remains a central bottleneck for the clinical translation of medical AI. Failure to address it can lead to severe performance degradation in u…
CRISP: Rank-Guided Iterative Squeezing for Robust Medical Image Segmentation under Domain Shift
Yizhou Fang, Pujin Cheng, Yixiang Liu +2
Distribution shift in medical imaging remains a central bottleneck for the clinical translation of medical AI. Failure to address it can lead to severe performance degradation in u…
FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation
Li Lin, Yixiang Liu, Jiewei Wu +4
Federated learning (FL) effectively mitigates the data silo challenge brought about by policies and privacy concerns, implicitly harnessing more data for deep model training. Howev…
ProCNS: Progressive Prototype Calibration and Noise Suppression for Weakly-Supervised Medical Image Segmentation
Y. Liu, L. Lin, K. K. Y. Wong +1
Weakly-supervised segmentation (WSS) has emerged as a solution to mitigate the conflict between annotation cost and model performance by adopting sparse annotation formats (e.g., p…