Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu | Summary: Time series data is ubiquitous across various domains, including manufacturing, finance, and healthcare. High-quality annotations are essential for effectively understanding time series and facilitating downstream tasks; however, obtaining such annotations is challenging, particularly in mission-critical […]


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Miniature magneto-oscillatory wireless sensor for magnetic field and gradient measurements

Kavli Affiliate: Felix Fischer | First 5 Authors: Felix Fischer, Moonkwang Jeong, Tian Qiu, , | Summary: Magneto-oscillatory devices have been recently developed as very potent wireless miniature position trackers and sensors with an exceptional accuracy and sensing distance for surgical and robotic applications. However, it is still unclear to which extend a mechanically resonating […]


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Magneto-oscillatory localization for small-scale robots

Kavli Affiliate: Felix Fischer | First 5 Authors: Felix Fischer, Christian Gletter, Moonkwang Jeong, Tian Qiu, | Summary: Magnetism is widely used for the wireless localization and actuation of robots and devices for medical procedures. However, current static magnetic localization methods suffer from large required magnets and are limited to only five degrees of freedom […]


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Supervised Chain of Thought

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Dujian Ding, , , | Summary: Large Language Models (LLMs) have revolutionized natural language processing and hold immense potential for advancing Artificial Intelligence. However, the core architecture of most mainstream LLMs — the Transformer — has inherent limitations in computational depth, rendering them theoretically incapable […]


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Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


Continue.. Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


Continue.. Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Optimal Communication and Key Rate Region for Hierarchical Secure Aggregation with User Collusion

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Kai Wan, Hua Sun, Shiqiang Wang, Mingyue Ji | Summary: Secure aggregation is concerned with the task of securely uploading the inputs of multiple users to an aggregation server without letting the server know the inputs beyond their summation. It finds broad applications in distributed […]


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Trojan Prompt Attacks on Graph Neural Networks

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang | Summary: Graph Prompt Learning (GPL) has been introduced as a promising approach that uses prompts to adapt pre-trained GNN models to specific downstream tasks without requiring fine-tuning of the entire model. Despite the advantages of GPL, […]


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NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models

Kavli Affiliate: Xiang Zhang | First 5 Authors: Han Han, Tong Zhu, Xiang Zhang, Mengsong Wu, Hao Xiong | Summary: Large language models (LLMs) combined with tool learning have gained impressive results in real-world applications. During tool learning, LLMs may call multiple tools in nested orders, where the latter tool call may take the former […]


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