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pro vyhledávání: '"Zhong, Yan"'
Recent studies in Retrieval-Augmented Generation (RAG) have investigated extracting evidence from retrieved passages to reduce computational costs and enhance the final RAG performance, yet it remains challenging. Existing methods heavily rely on heu
Externí odkaz:
http://arxiv.org/abs/2410.11315
Autor:
Zhao, Xinping, Zhong, Yan, Sun, Zetian, Hu, Xinshuo, Liu, Zhenyu, Li, Dongfang, Hu, Baotian, Zhang, Min
Retrieval-Augmented Generation (RAG) prevails in Large Language Models. It mainly consists of retrieval and generation. The retrieval modules (a.k.a. retrievers) aim to find useful information used to facilitate generation modules (a.k.a. generators)
Externí odkaz:
http://arxiv.org/abs/2410.10293
Autor:
Zhong, Yan, Zhao, Ruoyu, Wang, Chao, Guo, Qinghai, Zhang, Jianguo, Lu, Zhichao, Leng, Luziwei
Spiking neural networks (SNNs) provide an energy-efficient solution by utilizing the spike-based and sparse nature of biological systems. Since the advent of Transformers, SNNs have struggled to compete with artificial networks on long sequential tas
Externí odkaz:
http://arxiv.org/abs/2410.17268
Diabetic foot neuropathy (DFN) is a critical factor leading to diabetic foot ulcers, which is one of the most common and severe complications of diabetes mellitus (DM) and is associated with high risks of amputation and mortality. Despite its signifi
Externí odkaz:
http://arxiv.org/abs/2409.14154
Autor:
Shen, Shuaijie, Wang, Chao, Huang, Renzhuo, Zhong, Yan, Guo, Qinghai, Lu, Zhichao, Zhang, Jianguo, Leng, Luziwei
Known as low energy consumption networks, spiking neural networks (SNNs) have gained a lot of attention within the past decades. While SNNs are increasing competitive with artificial neural networks (ANNs) for vision tasks, they are rarely used for l
Externí odkaz:
http://arxiv.org/abs/2408.14909
Remote Photoplethysmography (rPPG) is a non-contact technique for extracting physiological signals from facial videos, used in applications like emotion monitoring, medical assistance, and anti-face spoofing. Unlike controlled laboratory settings, re
Externí odkaz:
http://arxiv.org/abs/2408.01077
The advent of large language models (LLMs) has facilitated the development of natural language text generation. It also poses unprecedented challenges, with content hallucination emerging as a significant concern. Existing solutions often involve exp
Externí odkaz:
http://arxiv.org/abs/2406.03075
In the algorithm selection research, the discussion surrounding algorithm features has been significantly overshadowed by the emphasis on problem features. Although a few empirical studies have yielded evidence regarding the effectiveness of algorith
Externí odkaz:
http://arxiv.org/abs/2405.11349
Autor:
Li, Xin, Zhong, Yan
Non-malleable extractors are generalizations and strengthening of standard randomness extractors, that are resilient to adversarial tampering. Such extractors have wide applications in cryptography and explicit construction of extractors. In the well
Externí odkaz:
http://arxiv.org/abs/2404.17013
Deep neural networks have demonstrated impressive success in No-Reference Image Quality Assessment (NR-IQA). However, recent researches highlight the vulnerability of NR-IQA models to subtle adversarial perturbations, leading to inconsistencies betwe
Externí odkaz:
http://arxiv.org/abs/2404.13277