Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Tang, Wei"'
Autor:
Ying, Jiahao, Lin, Mingbao, Cao, Yixin, Tang, Wei, Wang, Bo, Sun, Qianru, Huang, Xuanjing, Yan, Shuicheng
This paper introduces the innovative "LLMs-as-Instructors" framework, which leverages the advanced Large Language Models (LLMs) to autonomously enhance the training of smaller target models. Inspired by the theory of "Learning from Errors", this fram
Externí odkaz:
http://arxiv.org/abs/2407.00497
While large language models (LLMs) have made notable advancements in natural language processing, they continue to struggle with processing extensive text. Memory mechanism offers a flexible solution for managing long contexts, utilizing techniques s
Externí odkaz:
http://arxiv.org/abs/2406.13167
Retrieval-Augmented Generation (RAG) is an effective solution to supplement necessary knowledge to large language models (LLMs). Targeting its bottleneck of retriever performance, "generate-then-read" pipeline is proposed to replace the retrieval sta
Externí odkaz:
http://arxiv.org/abs/2406.03963
Novelty search (NS) refers to a class of exploration algorithms that automatically uncover diverse system behaviors through simulations or experiments. Systematically obtaining diverse outcomes is a key component in many real-world design problems su
Externí odkaz:
http://arxiv.org/abs/2406.03616
Regional geometric information is crucial for determining grasp poses. A series of region-based methods succeed in extracting regional features and enhancing grasp detection quality. However, faced with a cluttered scene with multiple objects and pot
Externí odkaz:
http://arxiv.org/abs/2406.01767
Multi-Object Tracking MOT encompasses various tracking scenarios, each characterized by unique traits. Effective trackers should demonstrate a high degree of generalizability across diverse scenarios. However, existing trackers struggle to accommodat
Externí odkaz:
http://arxiv.org/abs/2406.00429
Autor:
Yang, Ziyu W., Zhang, Jie, Pi, Maocai, Ye, Xubin, Kang, Chenxu, Weng, Xiaoliang, Tang, Wei, Cui, Hongzhi, Zeng, Yu-Jia, Long, Youwen
Bulk magnetic and thermodynamic measurements, along with mean-field calculations, were conducted on the ferromagnetic K3Gd5(PO4)6 powders. No magnetic ordering was observed until 2 K, while the application of an external field B > 1 T resulted in the
Externí odkaz:
http://arxiv.org/abs/2405.20714
Conventional recommender systems (RSs) face challenges in precisely capturing users' fine-grained preferences. Large language models (LLMs) have shown capabilities in commonsense reasoning and leveraging external tools that may help address these cha
Externí odkaz:
http://arxiv.org/abs/2405.15114
Autor:
Tang, Wei-Ting, Paulson, Joel A.
Bayesian optimization (BO) is a popular approach for optimizing expensive-to-evaluate black-box objective functions. An important challenge in BO is its application to high-dimensional search spaces due in large part to the curse of dimensionality. O
Externí odkaz:
http://arxiv.org/abs/2405.07760
Fast and robust object grasping in clutter is a crucial component of robotics. Most current works resort to the whole observed point cloud for 6-Dof grasp generation, ignoring the guidance information excavated from global semantics, thus limiting hi
Externí odkaz:
http://arxiv.org/abs/2403.18546