works on

From the 3 of 65 papers with an AI index.

most citedTopological Phase Transition in Mechanical Honeycomb Lattice

184 citations

56 papers

cond-mat.mtrl-sci2026

Quantized Spin Hall Effect in Three-Dimensional Nodal-Ring Semimetal: Geometric Scaling and Symmetry-Engineered Spin Response

Jiali Chen, Chaoxi Cui, Zhi-Ming Yu +2

The anomalous Hall conductivity in magnetic Weyl semimetals scales linearly with the momentum separation between Weyl nodes, establishing a geometric paradigm for three-dimensional…

cs.AI2026

SymDiag: Explainable Diagnosis for LLM Reasoning via Neuro-Symbolic Verification

Wenyao Cui, Huaping Zhang, Yongyi Huang +6

Large language models (LLMs) increasingly serve as data-driven reasoners, yet their chains-of-thought (CoT) can be unfaithful even when final answers are correct. Most existing ``v…

cs.CR2026

Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework

Zhaoqi Wang, Daqing He, Zijian Zhang +13

While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabilities to knowledge corruption att…

cond-mat.soft20261 cited

3D Topologically Polarized Elastic Metamaterials Enable Asymmetric Energy Isolation at Low Frequencies

Shaoyuan Zhang, Xuejian Gong, Fangyuan Ma +5

Topologically polarized elasticity has been extensively studied in lower-dimensions, yet its three-dimensional (3D) counterpart remains largely unexplored. Here, we demonstrate omn…

eess.SP20261 cited

A Robust EDM Optimization Approach for 3D Single-Source Localization with Angle and Range Measurements

Mingyu Zhao, Qingna Li, Hou-Duo Qi

The paper proposes a robust Euclidean distance matrix optimization method that jointly uses range and angle data with an L1-norm criterion to improve 3D single-source localization…

cs.LG2026

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation

Kun Fang, Qinghua Tao, Mingzhen He +6

The paper proposes a kernel PCA based method for out-of-distribution detection that learns a discriminative non-linear subspace using a newly designed Cosine-Gaussian kernel and in…