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Wanchun Ni

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#artificial intelligence Preprint Sep 2026

STRIDE: Automated Evaluation of Text-to-Trajectory Alignment across Diverse Contexts

This work introduces STRIDE, the first framework for evaluating context alignment between scenario descriptions and pedestrian trajectories, and believes that the STRIDE framework provides a first step toward principled evaluation of context-aligned pedestrian trajectory generation.

Wan-Chun Ni, Tao Qi, Leonel Aguilar et al. · 0 citations
Conference Open access 2026

Robust Membership Inference for Large Language Models under Adversarial Generative Corruption

A robust membership inference framework for reliably identifying training data that adopts a mixture-of-experts formulation to jointly model interactions across complementary features derived from multiple MIA methods and AIGT detectors, which can remain robust against ad-versarially generated samples.

Yuanhong Huang, Huili Wang, Xueying Bai et al. · 1 citation

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