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acclivity    
n. 向上的斜坡

向上的斜坡

acclivity
n 1: an upward slope or grade (as in a road); "the car couldn't
make it up the rise" [synonym: {ascent}, {acclivity}, {rise},
{raise}, {climb}, {upgrade}] [ant: {declension},
{declination}, {decline}, {declivity}, {descent},
{downslope}, {fall}]



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  • GitHub - Ram81 goat-bench
    We refer to finding each goal in a GOAT episode as a subtask Each GOAT episode comprises 5 to 10 subtasks We set up the GOAT task in an open-vocabulary setting; unlike many prior works, we are not restricted to navigating to a predetermined, closed set of object categories
  • GOAT-Bench|多模态导航数据集|终身学习数据集
    GOAT-Bench是由乔治亚理工学院创建的多模态终身导航基准数据集,包含约725,000个训练集条目。 该数据集旨在评估和推动多模态目标导航技术的发展,特别是针对开放词汇目标的导航。
  • CVPR-2024 | 具身推理有果未必有因!GOAT:基于因果学习的视觉语言导航
    提出了 后门调整因果学习 (BACL)和 前门调整因果学习 (FACL)模块,以端到端的方式实现无偏的跨模态干预和决策,通过消除数据集中的潜在虚假相关性,促进了无偏特征的学习和决策。
  • 乔治亚理工学院 发布 GOAT-Bench 数据集, 应用在 多模态导航、终身学习 领域
    乔治亚理工学院 本次发布的数据集 GOAT-Bench, GOAT-Bench是由乔治亚理工学院创建的多模态终身导航基准数据集,包含约725,000个训练集条目。 该数据集旨在评估和推动多模态目标导航技术的发展,特别是针对开放词汇目标的导航。
  • GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
    We propose GOAT-Bench, a benchmark for the GOAT task, where we evaluate modular and monolithic, explicit and implicit map-based navigation approaches
  • GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
    We benchmark monolithic RL and modular methods on the GOAT task, analyzing their performance across modalities, the role of explicit and implicit scene memories, their robustness to noise in goal specifications, and the impact of memory in lifelong scenarios
  • GitHub Pages - GOAT-Bench
    We introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content
  • HKBU-NLP GOAT-Bench · Datasets at Hugging Face
    We introduce the GOAT-Bench, a comprehensive and specialized dataset designed to evaluate large multimodal models through meme-based multimodal social abuse GOAT-Bench comprises over 6K diverse memes, encompassing a range of themes including hate speech and offensive content
  • GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
    为了促进这一目标,我们提出了GOAT-Bench,这是一个通用导航任务的基准,称为“GO to AnyThing”(GOAT)。 在这个任务中,代理被指示导航到由类别名称、语言描述或图像指定的一系列目标,以开放词汇的方式。
  • 厦大等高校打造MSGNav:多模态3D场景图赋能零样本具身导航,解决“最后一公里”难题
    四、实验效果:两大数据集登顶,模块各司其职 我们在GOAT-Bench(多模态终身开放词汇导航)和HM3D-OVON(开放词汇物体目标导航)两个数据集上测试,核心指标是成功率(SR)和成功路径长度(SPL)——SR越高、SPL越高,说明导航越成功、越高效。 核心图表解读





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