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From the 1 of 12 papers with an AI index.

most citedLearnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes

46 citations

12 papers

cs.AI2026

From Cheap Fakes to Pure Synthesis: Addressing the New Era of T2V Fake News Videos

Yifeng Luo, Yupeng Li, Liang Lan +1

Recent text-to-video (T2V) generation models enable fake news videos to be synthesized from scratch, shifting the threat beyond cheap fakes assembled from existing footage. Such ne…

cs.CL2026

Novel Claim or Déjà Vu? Rethinking "Contamination-Free'' Dynamic Evaluation for Multimodal Automated Fact-Checking

Haorui He, Xinwen Chen, Dacheng Wen +3

Multimodal automated fact-checking (MAFC) verifies claims by retrieving and reasoning over external evidence. However, most existing static benchmarks risk contamination: they prim…

cs.AI2026

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

Amin Beheshti, Rong N. Chang, Boualem Benatallah +7

The paper proposes Agentic Service-Oriented Computing (ASOC), a framework for engineering large‑language‑model‑powered autonomous agents as services and managing their composition,…

physics.app-ph2026

Tailoring reflectionless complex media for non-Abelian braiding of acoustic modes

Hongkuan Zhang, Guancong Ma

Multiple scattering of sound and light can be tailored for diverse applications. Despite the great progress enabled by technologies such as time-reversal propagation and wavefront…

cs.SE2026

VRExplorer: A Model-based Approach for Semi-Automated Testing of Virtual Reality Scenes

Zhengyang Zhu, Hong-Ning Dai, Hanyang Guo +2

With the proliferation of Virtual Reality (VR) markets, VR applications are rapidly expanding in scale and complexity, thereby driving an urgent need for assuring VR software quali…

cs.LG202646 cited

Learnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes

Yiqun Zhang, Yiu-ming Cheung

The success of categorical data clustering generally much relies on the distance metric that measures the dissimilarity degree between two objects. However, most of the existing cl…