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ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes
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2026-02-28 11:48:44
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ARNOLD ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes ICCV 2023 Ran Gong 1✶ , Jiangyong Huang 2,5✶ , Yizhou Zhao 1 , Haoran Geng 2,5 , Xiaofeng Gao 1 , Qingyang Wu 4 , Wensi Ai 1 , Ziheng Zhou 1 , Demetri Terzopoulos 1 , Song-Chun Zhu 2,3,5 , Baoxiong Jia 5 , Siyuan Huang 5 1 University of California, Los Angeles, 2 Peking University, 3 Tsinghua University, 4 Columbia University, 5 National Key Laboratory of General Artificial Intelligence, BIGAI ✶ indicates equal contribution arXiv Code Docs Data Video Challenge We present ARNOLD , a benchmark that evaluates language-grounded task learning with continuous states in realistic 3D scenes . ARNOLD provides 8 tasks with their demonstrations for learning and a testbed for the generalization abilities of agents over (1) novel goal states , (2) novel objects , and (3) novel scenes . Abstract ...
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