3 papers
cs.LG2026
Counterfactual Evaluation of Temporal Observation Protocols
Xizhe Zhang
We study counterfactual protocol evaluation: whether data collected under a realised observation protocol determine the predictive value of alternatives that were never deployed. P…
stat.ML2026
The Label Defines the Timescale: Trait-State Limits of Temporal-Aggregate Learning
Xizhe Zhang
Machine-learning benchmarks often pair a label that aggregates a long temporal horizon with input observed through one or a few short windows. Their apparent performance ceiling ma…
cs.CV2026
Noise-Robust Box-Supervised Infrared Small Target Detection via Physics-Inspired Soft Label Optimization
Xizhe Zhang, Fan Shi, Mianzhao Wang +3
Infrared small target detection (IRSTD) commonly relies on pixel-level mask supervision. Such annotations, however, are costly and inherently uncertain because infrared targets hav…