4 papers
Lifting Manifolds to Mitigate Pseudo-Alignment in LLM4TS
Liangwei Nathan Zheng, Wenhao Liang, Wei Emma Zhang +3
Pseudo-Alignment is a pervasive challenge in many large language models for time series (LLM4TS) models, often causing them to underperform compared to linear models or randomly in…
Calibration Attention: Learning Reliability-Aware Representations for Vision Transformers
Wenhao Liang, Wei Emma Zhang, Lin Yue +4
Most calibration methods operate at the logit level, implicitly assuming that miscalibration can be corrected without changing the underlying representation. We challenge this assu…
PostHoc FREE Calibrating on Kolmogorov Arnold Networks
Wenhao Liang, Wei Emma Zhang, Lin Yue +3
Kolmogorov Arnold Networks (KANs) are neural architectures inspired by the Kolmogorov Arnold representation theorem that leverage B Spline parameterizations for flexible, locally a…
We Care Each Pixel: Calibrating on Medical Segmentation Model
Wenhao Liang, Wei Zhang, Lin Yue +3
Medical image segmentation is fundamental for computer-aided diagnostics, providing accurate delineation of anatomical structures and pathological regions. While common metrics suc…