Zobrazeno 1 - 10
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pro vyhledávání: '"Chen, HaiFeng"'
Causal inference is an imperative foundation for decision-making across domains, such as smart health, AI for drug discovery and AIOps. Traditional statistical causal discovery methods, while well-established, predominantly rely on observational data
Externí odkaz:
http://arxiv.org/abs/2412.13667
Cross-modal alignment is crucial for multimodal representation fusion due to the inherent heterogeneity between modalities. While Transformer-based methods have shown promising results in modeling inter-modal relationships, their quadratic computatio
Externí odkaz:
http://arxiv.org/abs/2412.00833
Autor:
Zhao, Qiwei, Zhao, Xujiang, Liu, Yanchi, Cheng, Wei, Sun, Yiyou, Oishi, Mika, Osaki, Takao, Matsuda, Katsushi, Yao, Huaxiu, Chen, Haifeng
Large language models (LLMs) integrated into multistep agent systems enable complex decision-making processes across various applications. However, their outputs often lack reliability, making uncertainty estimation crucial. Existing uncertainty esti
Externí odkaz:
http://arxiv.org/abs/2412.01033
Autor:
Wang, Tianchun, Chen, Yuanzhou, Liu, Zichuan, Chen, Zhanwen, Chen, Haifeng, Zhang, Xiang, Cheng, Wei
The advent of large language models (LLMs) has revolutionized the field of text generation, producing outputs that closely mimic human-like writing. Although academic and industrial institutions have developed detectors to prevent the malicious usage
Externí odkaz:
http://arxiv.org/abs/2410.19230
Autor:
Lin, Minhua, Chen, Zhengzhang, Liu, Yanchi, Zhao, Xujiang, Wu, Zongyu, Wang, Junxiang, Zhang, Xiang, Wang, Suhang, Chen, Haifeng
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 annot
Externí odkaz:
http://arxiv.org/abs/2410.17462
Autor:
Light, Jonathan, Wu, Yue, Sun, Yiyou, Yu, Wenchao, liu, Yanchi, Zhao, Xujiang, Hu, Ziniu, Chen, Haifeng, Cheng, Wei
We propose a novel approach to scaling LLM inference for code generation. We frame code generation as a black box optimization problem within the code space, and employ optimization-inspired techniques to enhance exploration. Specifically, we introdu
Externí odkaz:
http://arxiv.org/abs/2411.05010
Root Cause Analysis (RCA) is essential for pinpointing the root causes of failures in microservice systems. Traditional data-driven RCA methods are typically limited to offline applications due to high computational demands, and existing online RCA m
Externí odkaz:
http://arxiv.org/abs/2410.10021
Autor:
Bai, Yuqing, Xiang, Xinji, Pan, Shuang, Zhang, Shichao, Chen, Haifeng Chen Xi, Han, Zhida, Xu, Guizhou, Xu, Feng
As a promising candidate for altermagnet, CrSb possesses a distinctive compensated spin split band structure that could bring groundbreaking concepts to the field of spintronics. In this work, we have grown high-quality CrSb single crystals and compr
Externí odkaz:
http://arxiv.org/abs/2409.14855
Multimodal Emotion Recognition (MER) aims to automatically identify and understand human emotional states by integrating information from various modalities. However, the scarcity of annotated multimodal data significantly hinders the advancement of
Externí odkaz:
http://arxiv.org/abs/2409.05015
Autor:
Deng, Chengyuan, Chen, Zhengzhang, Zhao, Xujiang, Wang, Haoyu, Wang, Junxiang, Chen, Haifeng, Gao, Jie
Change point detection aims to identify abrupt shifts occurring at multiple points within a data sequence. This task becomes particularly challenging in the online setting, where different types of changes can occur, including shifts in both the marg
Externí odkaz:
http://arxiv.org/abs/2407.09698