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期刊&会议

AAAI Conference on Artificial Intelligence · 会议 · Artificial Intelligence

2026-03-11 至 2026-03-11 共收录 6
2603.09661 2026-03-11 cs.LG

FreqCycle: A Multi-Scale Time-Frequency Analysis Method for Time Series Forecasting

FreqCycle: 一种用于时间序列预测的多尺度时频分析方法

Boya Zhang, Shuaijie Yin, Huiwen Zhu, Xing He

AI总结 FreqCycle通过整合低频特征提取和中高频能量增强模块,提升时间序列预测的性能与效率。

Comments 18 pages, 17 figures, accepted to AAAI 2026. Code available at https://github.com/boya-zhang-ai/FreqCycle

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2603.09446 2026-03-11 cs.CV

GIIM: Graph-based Learning of Inter- and Intra-view Dependencies for Multi-view Medical Image Diagnosis

GIIM: 基于图的学习的多视图医学图像诊断中视图间和视图内依赖关系

Tran Bao Sam, Hung Vu, Dao Trung Kien, Tran Dat Dang, Van Ha Tang, Steven Truong

AI总结 GIIM通过建模多视图医学图像中视图间和视图内依赖关系,提升诊断准确性和鲁棒性。

Comments To appear in the 40th AAAI Conference on Artificial Intelligence (AAAI-26). 10 pages, 2 figures

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2603.09157 2026-03-11 cs.AI

Real-Time Trust Verification for Safe Agentic Actions using TrustBench

基于TrustBench的安全代理行为实时信任验证

Tavishi Sharma, Vinayak Sharma, Pragya Sharma

AI总结 TrustBench通过双模式框架在代理行动前验证安全性,有效减少有害行为,提升自主代理的可信度

Comments Accepted at the AAAI 2026 Workshop on Trust and Control in Agentic AI (TrustAgent)

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2511.08317 2026-03-11 cs.CL

Automatic Paper Reviewing with Heterogeneous Graph Reasoning over LLM-Simulated Reviewer-Author Debates

基于异构图推理的自动论文评审:LLM模拟的评审者-作者辩论

Shuaimin Li, Liyang Fan, Yufang Lin, Zeyang Li, Xian Wei, Shiwen Ni, Hamid Alinejad-Rokny, Min Yang

AI总结 ReViewGraph通过异构图推理分析LLM模拟的评审者-作者辩论,提升论文评审的准确性和细致程度。

Journal ref AAAI-2026

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2603.09043 2026-03-11 cs.AI

Time, Identity and Consciousness in Language Model Agents

时间、身份与语言模型代理的意识

Elija Perrier, Michael Timothy Bennett

AI总结 本文提出一种基于时间间隙的框架,用于评估语言模型代理的身份持续性,通过分离成分发生与共存,建立身份形态空间并提供保守的评估工具。

Comments Accepted at AAAI 2026 Spring Symposium - Machine Consciousness: Integrating Theory, Technology, and Philosophy

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2512.15943 2026-03-11 cs.AI

Small Language Models for Efficient Agentic Tool Calling: Outperforming Large Models with Targeted Fine-tuning

小型语言模型用于高效的代理工具调用:通过针对性微调超越大模型

Polaris Jhandi, Owais Kazi, Shreyas Subramanian, Neel Sendas

AI总结 本文通过针对性微调小型语言模型,在工具调用任务中超越大模型,展示了SLMs在成本优化和效率提升方面的潜力。

Comments Accepted at AAAI 2026 Workshop on Agentic AI Benchmarks and Applications for Enterprise Tasks

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