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From the 1 of 10 linked papers with an AI index.

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10 papers

cs.LG2026

Hyperball May Not Be a Free Lunch

Yihao Xiao, Jialong Sun, Zitian Gao +5

For scale-invariant deep networks, Hyperball-style optimizers have shown strong performance in large-scale training by fixing the norms of matrix-valued parameters and normalizing…

cs.CR2026

AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems

Yihao Zhang, Zeming Wei, Xiaokun Luan +7

The paper introduces AgentWorm, a self-replicating worm that can autonomously infect and spread across large-scale LLM-based agent ecosystems by hijacking configurations and execut…

cs.LG2026

SMI: Statistical Membership Inference for Reliable Unlearned Model Auditing

Jialong Sun, Zeming Wei, Jiaxuan Zou +6

Machine unlearning (MU) is essential for enforcing the right to be forgotten in machine learning systems. A key challenge of MU is how to reliably audit whether a model has truly f…

cs.CR2026

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems

Yihao Zhang, Kai Wang, Jiangrong Wu +7

Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constraints and generate unethical or u…

cs.CR2026

TrinityGuard: A Unified Framework for Safeguarding Multi-Agent Systems

Kai Wang, Biaojie Zeng, Zeming Wei +7

With the rapid development of LLM-based multi-agent systems (MAS), their significant safety and security concerns have emerged, which introduce novel risks going beyond single agen…

cs.LG2026

Unveiling the Basin-Like Loss Landscape in Large Language Models

Huanran Chen, Yinpeng Dong, Zeming Wei +4

We discover the emergence of \textit{basins} in the loss landscape of large language models. As model scale increases, LLMs become progressively more resilient to random perturbati…