Jiaru Tang — accepted AI-conference papers

2026

CogniTrust: Cognitive Memory-Driven Verifiable Supervision for Robust Hashing

Yiyang Gu, Bohan Wu, Yifang Qin, Jiaru Tang, Rong-Cheng Tu, Zhiping Xiao +6

AAAI 2026technical

In this paper, we study the problem of robust multi-label hashing, where label noise hinders the learning of a reliable semantic structure from data. Many existing methods rely on heuristic sample selection or consistency-based training, but lack a unified mechanism to validate and refine supervisio

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2026

PRISM: Partial-label Relational Inference with Spatial and Spectral Cues

Yiyang Gu, Wenrui Wu, Yifang Qin, Taian Guo, Tao Zhe, Jiaru Tang +8

ICLR 2026poster

In many real-world scenarios, precisely labeling graph data is costly or impractical, especially in domains like molecular biology or social networks, where annotation requires expert effort. This challenge motivates partial-label graph learning, where each graph is weakly annotated with a candidate…

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