arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

University of California, San Diego(加州大学圣迭戈分校)

2026-01-14 至 2026-01-14 共收录 4
2601.08764 2026-01-14 cs.IR cs.SD eess.AS

FusID: Modality-Fused Semantic IDs for Generative Music Recommendation

FusID: 多模态融合的语义ID用于生成音乐推荐

Haven Kim, Yupeng Hou, Julian McAuley

机构 * University of California San Diego(加州大学圣地亚哥分校)

AI总结 FusID通过多模态融合、表示学习和产品量化技术,解决生成音乐推荐中跨模态交互和ID冲突问题,提升推荐准确率。

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2512.13564 2026-01-14 cs.CL cs.AI

Memory in the Age of AI Agents

人工智能代理时代的记忆

Yuyang Hu, Shichun Liu, Yanwei Yue, Guibin Zhang, Boyang Liu, Fangyi Zhu, Jiahang Lin, Honglin Guo, Shihan Dou, Zhiheng Xi, Senjie Jin, Jiejun Tan, Yanbin Yin, Jiongnan Liu, Zeyu Zhang, Zhongxiang Sun, Yutao Zhu, Hao Sun, Boci Peng, Zhenrong Cheng, Xuanbo Fan, Jiaxin Guo, Xinlei Yu, Zhenhong Zhou, Zewen Hu, Jiahao Huo, Junhao Wang, Yuwei Niu, Yu Wang, Zhenfei Yin, Xiaobin Hu, Yue Liao, Qiankun Li, Kun Wang, Wangchunshu Zhou, Yixin Liu, Dawei Cheng, Qi Zhang, Tao Gui, Shirui Pan, Yan Zhang, Philip Torr, Zhicheng Dou, Ji-Rong Wen, Xuanjing Huang, Yu-Gang Jiang, Shuicheng Yan

机构 * Core Supervisors. 0.5em Affiliations: National University of Singapore, Renmin University of China, Fudan University, Peking University, Nanyang Technological University, Tongji University, University of California San Diego, Hong Kong University of Science Technology (Guangzhou), Griffith University, Georgia Institute of Technology, OPPO, Oxford University

AI总结 本文系统梳理了人工智能代理记忆的现状与分类,提出了记忆的三种形式、功能分类及动态分析,为未来智能设计提供理论基础。

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2506.18124 2026-01-14 cs.LG eess.SP stat.ML

Bayesian Multiobject Tracking With Neural-Enhanced Motion and Measurement Models

基于神经网络的贝叶斯多目标跟踪

Shaoxiu Wei, Mingchao Liang, Florian Meyer

机构 * Department of Electrical and Computer Engineering, University of California San Diego(电气与计算机工程系,加州大学圣地亚哥分校) Scripps Institution of Oceanography(斯克里普斯海洋研究所)

AI总结 本文提出一种结合神经网络与贝叶斯方法的多目标跟踪框架,通过增强统计模型提升预测和更新性能,实现在自动驾驶数据集上的最佳表现。

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2505.20315 2026-01-14 cs.CL cs.AI

Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL

Arctic-Text2SQL-R1: 简单奖励,强推理的文本到SQL

Zhewei Yao, Guoheng Sun, Lukasz Borchmann, Gaurav Nuti, Zheyu Shen, Minghang Deng, Bohan Zhai, Hao Zhang, Ang Li, Yuxiong He

机构 * Snowflake AI Research(Snowflake AI研究院) University of Maryland(马里兰大学) University of California, San Diego(加州大学圣地亚哥分校)

AI总结 Arctic-Text2SQL-R1通过简单奖励机制和强化学习框架,在文本到SQL任务中实现高准确率和高效性,优于现有大型模型。

Comments 22 pages, 2 figures

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