Zobrazeno 1 - 10
of 70 726
pro vyhledávání: '"Wei,Chen"'
Autor:
Song, Kaidong, Zhou, Jingyuan, Wei, Chen, Ponnuchamy, Ashok, Bappy, Md Omarsany, Liao, Yuxuan, Jiang, Qiang, Du, Yipu, Evans, Connor J., Wyatt, Brian C., O'Sullivan, Thomas, Roeder, Ryan K., Anasori, Babak, Hoffman, Anthony J., Jin, Lihua, Duan, Xiangfeng, Zhang, Yanliang
Stretchable electronics capable of conforming to nonplanar and dynamic human body surfaces are central for creating implantable and on-skin devices for high-fidelity monitoring of diverse physiological signals. While various strategies have been deve
Externí odkaz:
http://arxiv.org/abs/2411.03339
Despite significant progress in visual decoding with fMRI data, its high cost and low temporal resolution limit widespread applicability. To address these challenges, we introduce RealMind, a novel EEG-based visual decoding framework that leverages m
Externí odkaz:
http://arxiv.org/abs/2410.23754
We consider realizable contextual bandits with general function approximation, investigating how small reward variance can lead to better-than-minimax regret bounds. Unlike in minimax bounds, we show that the eluder dimension $d_\text{elu}$$-$a compl
Externí odkaz:
http://arxiv.org/abs/2410.12713
In linear bandits, how can a learner effectively learn when facing corrupted rewards? While significant work has explored this question, a holistic understanding across different adversarial models and corruption measures is lacking, as is a full cha
Externí odkaz:
http://arxiv.org/abs/2410.07533
Autor:
Chen, Ziru, Chen, Shijie, Ning, Yuting, Zhang, Qianheng, Wang, Boshi, Yu, Botao, Li, Yifei, Liao, Zeyi, Wei, Chen, Lu, Zitong, Dey, Vishal, Xue, Mingyi, Baker, Frazier N., Burns, Benjamin, Adu-Ampratwum, Daniel, Huang, Xuhui, Ning, Xia, Gao, Song, Su, Yu, Sun, Huan
The advancements of language language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about their true capabilities. In t
Externí odkaz:
http://arxiv.org/abs/2410.05080
The recent development of Video-based Large Language Models (VideoLLMs), has significantly advanced video summarization by aligning video features and, in some cases, audio features with Large Language Models (LLMs). Each of these VideoLLMs possesses
Externí odkaz:
http://arxiv.org/abs/2410.04511
To address the risks of encountering inappropriate or harmful content, researchers managed to incorporate several harmful contents datasets with machine learning methods to detect harmful concepts. However, existing harmful datasets are curated by th
Externí odkaz:
http://arxiv.org/abs/2409.19734
Chern-Simons gravity is known to suffer from graviton ghost production during inflation, which suppresses the parity-violating power spectrum at scales relevant to cosmic microwave background observations. In this work, we show that allowing the init
Externí odkaz:
http://arxiv.org/abs/2409.09935
Autor:
Zhao, Jian, Wang, Shenao, Zhao, Yanjie, Hou, Xinyi, Wang, Kailong, Gao, Peiming, Zhang, Yuanchao, Wei, Chen, Wang, Haoyu
The proliferation of pre-trained models (PTMs) and datasets has led to the emergence of centralized model hubs like Hugging Face, which facilitate collaborative development and reuse. However, recent security reports have uncovered vulnerabilities an
Externí odkaz:
http://arxiv.org/abs/2409.09368
Autor:
Zheng, Xinyi, Wei, Chen, Wang, Shenao, Zhao, Yanjie, Gao, Peiming, Zhang, Yuanchao, Wang, Kailong, Wang, Haoyu
The exponential growth of open-source package ecosystems, particularly NPM and PyPI, has led to an alarming increase in software supply chain poisoning attacks. Existing static analysis methods struggle with high false positive rates and are easily t
Externí odkaz:
http://arxiv.org/abs/2409.09356