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Jingzheng Li

3 accepted papers

2026

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble

IJCAI 2026

LLM Ensemble---which involves the comprehensive use of multiple large language models (LLMs), each aimed at handling user queries during downstream inference, to benefit from their individual strengths---has gained substantial attention recently. The widespread availability of LLMs, coupled with the

Cited by 0Scholar
2026

Misclassification-Aware Robust Learning from Multiple Human Labelers (Student Abstract)

AAAI 2026technical

Adversarial training is an effective technique for enhancing the robustness of deep neural networks (DNNs). Prior research shows that misclassified examples influence final adversarial robustness much more than correctly classified examples. Ignoring this difference during training can hurt model pe

Cited by 0SourcePDFScholar
2026

OBJVanish: Prompt-Driven Generation of Physically Realizable 3D LiDAR-Invisible Objects

ICML 2026poster

LiDAR-based 3D object detectors are fundamental to autonomous driving, where missed detections pose severe safety risks. While adversarial attacks are crucial for evaluating the robustness of these detectors, existing point-level perturbation methods rarely cause complete object disappearance and pr…

Cited by 0SourceScholar