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arxivdaily.com

每日最新的学术信息

ecice06.com

computer engineering

c2.org.cn

阿里云万网是阿里云旗下品牌，中国最大的域名注册服务提供商，致力于成为全球域名服务引领者，提供域名、建站、备案等上云基础服务，让创业更简单！

sqz.ac.cn

期智

huodongjia.com

活动家提供2025上海国际合成生物学与生物制造展览会官网最新门票优惠(更新于:2025年06月09日)。2025上海国际合成生物学与生物制造展览会将于2025年08月07日在上海召开，优惠票在线报名截止2025年08月07日。一键查询2025上海国际合成生物学与生物制造展览会会议通知及邀请函下载，包含开会时间地点、嘉宾演讲主题、日程、价格等会议信息，报名2025上海国际合成生物学与生物制造展览会，轻松快捷。

dqxxkx.cn

[Objectives] Addressing the challenges of weak generalization and heavy reliance on large amounts of city-specific annotated data in environment-dependent crime spatio-temporal prediction, this paper proposes a foundation model named ST-Crime based on generative pre-training and prompt learning, aiming to enhance the accuracy of environment-dependent crime spatio-temporal prediction and improve generalization performance in new environments. [Methods] The method first unifies crime data into a tensor representation, employs a Transformer backbone to capture global spatio-temporal dependencies, and introduces a crime spatio-temporal memory retrieval enhancement module. This module extracts common spatio-temporal patterns from multi-city data and generates prompt information through spatio-temporal memory, crime-type interaction, and adaptive graph learning mechanisms to strengthen the model's expressive capability. [Results] Experiments were conducted using crime data from the year 2019 across four cities—New York, Los Angeles, San Francisco, and Chicago—totaling over 300 000 records and covering four typical environment-dependent crime types: burglary, robbery, felony assault, and grand larceny. In the full-training scenario (using year-long data from New York, Los Angeles, and San Francisco), ST-Crime achieved Macro-F1 scores of 0.739 7, 0.643 3, and 0.665 2, and Micro-F1 scores of 0.687 1, 0.601 8, and 0.537 5 on the three cities respectively, significantly outperforming existing baseline models.Compared to the best-performing baseline model in each city, it achieved improvements of 1.57%, 4.30%, 6.45% in Macro-F1, and 1.15%, 6.06%, 9.63% in Micro-F1, demonstrating significant advancements. For Chicago in the few-shot (fine-tuned with only 20% of data) and zero-shot (direct inference) scenarios, it also achieved Macro-F1 scores of 0.658 6 and 0.603 1, and Micro-F1 scores of 0.596 9 and 0.565 3, which surpassed the best baseline by 7.02%, 7.73% in Macro-F1, and by

wangyunhe.site

yunhe wang is currently a senior researcher at huawei noah's ark lab

zr9558.com

MA 1102R Final Examination Papers: 0809SEM1-MA1102R 0809SEM2-MA1102R 0910SEM1-MA1102R 0910SEM2-MA1102R 1011SEM1-MA1102R 1011SEM2-MA1102R 1112SEM1-MA1102R 1112SEM2-MA1102R 1213SEM1-MA1102R 1213SEM2-…

yankong.org

研控是一个中立开源的科研信息平台，希望所有人都能在这里自由地获取和分享科研信息。研控上线的第一个板块是导师评价，其它功能也正在筹划开发中。