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From the 1 of 17 linked papers with an AI index.

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17 papers

math.AP2026

On solitary wave solutions with two-frequency parameters to the three-component system of quadratic nonlinear Schrödinger equations

Hiroyuki Hirayama, Masahiro Ikeda

In the present paper, we consider the Cauchy problem of a system of three nonlinear Schrödinger equations with quadratic nonlinearity. We first prove the existence of ground states…

cs.AI2026

Who Grades the Grader? Co-Evolving Evaluation Metrics and Skills for Self-Improving LLM Agents

Xing Zhang, Guanghui Wang, Yanwei Cui +4

The paper introduces a framework that co‑evolves evaluation metrics and the skills of LLM agents using an evolutionary loop guided by anchored reference sets, enabling transparent…

cs.AI2026

The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents

Xing Zhang, Yanwei Cui, Guanghui Wang +4

A self-evolving agent retires its bad skills by watching them fail, so what happens when the judge cannot see the failures? Skill retirement is the structural constraint that keeps…

cs.AI2026

Budgeted Act-or-Defer Multi-Agent LLM Deliberation with Local Reliability Bounds

Mengdie Flora Wang, Haochen Xie, Guanghui Wang +2

Multi-agent deliberation among LLMs can improve reasoning, but deployment requires deciding when the current answer is reliable enough to act on and when it should be escalated to…

cs.CL2026

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety

Ting Ma, Xiufeng Huang, Benlei Cui +43

As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We argue that the essence of safet…

cs.CV2026

Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety

Shikai Qiu, Xiaowen Xu, Benlei Cui +55

General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature of content and AI s…