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Tokens经济:站上“火山口”
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《计算机应用文摘》 2026年第2期255-257,共3页
Tokens——大模型时代的“新货币”在大模型领域,Tokens是衡量文本处理与计算成本的核心计量单位。这一概念看似简单,却承载着AI技术从实验室走向产业化的关键密码。随着大模型技术的快速发展,Tokens的消耗量逐渐成为衡量行业进展和市... Tokens——大模型时代的“新货币”在大模型领域,Tokens是衡量文本处理与计算成本的核心计量单位。这一概念看似简单,却承载着AI技术从实验室走向产业化的关键密码。随着大模型技术的快速发展,Tokens的消耗量逐渐成为衡量行业进展和市场活跃度的核心指标。然而,当行业将目光聚焦于Tokens数量的增长时,一个更深层次的问题浮现出来:这些Tokens是否真正创造了价值?还是仅仅沦为一场“数字游戏”? 展开更多
关键词 计算成本 文本处理 tokens 大模型 新货币
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Asymmetries in factors influencing non‑fungible tokens’(NFTs)returns
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作者 Botond Benedek Bálint Zsolt Nagy 《Financial Innovation》 2025年第1期602-621,共20页
The asymmetries of factors influencing the return of cryptocurrencies have already been well documented;however,in the case of NFTs,only information asymmetries and hedging properties related to asymmetries were studi... The asymmetries of factors influencing the return of cryptocurrencies have already been well documented;however,in the case of NFTs,only information asymmetries and hedging properties related to asymmetries were studied.Therefore,the present study examines factors affecting NFT returns,from market-related factors(cryptomarket index return and stock market index return)to the Amihud illiquidity ratio and Google search trends during different market conditions.The wavelet coherences-based methodology was applied separately during the boom,bust,normal,and turbulent periods identified by structural breakpoints.Based on 14 NFT projects between April 2019 and July 2022,results show two fundamental asymmetries influencing these NFT returns.First,there is an asymmetry in the behavior of the factors in different periods;second,there is an asymmetry in how illiquidity manifests itself over NFTs that do or do not possess cash flow-generating potential. 展开更多
关键词 Non-fungible tokens Partial wavelet coherence Multiple wavelet coherence Multiple endogenous structural breaks
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基于深度卷积-Tokens降维优化视觉Transformer的分心驾驶行为实时检测 被引量:8
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作者 赵霞 李朝 +2 位作者 付锐 葛振振 王畅 《汽车工程》 EI CSCD 北大核心 2023年第6期974-988,1009,共16页
针对基于端到端深度卷积神经网络的驾驶行为检测模型缺乏全局特征提取能力以及视觉Transformer(vision transformer,ViT)模型不擅长捕捉底层特征和模型参数量较大的问题,本文提出一种基于深度卷积和Tokens降维的ViT模型用于驾驶人分心... 针对基于端到端深度卷积神经网络的驾驶行为检测模型缺乏全局特征提取能力以及视觉Transformer(vision transformer,ViT)模型不擅长捕捉底层特征和模型参数量较大的问题,本文提出一种基于深度卷积和Tokens降维的ViT模型用于驾驶人分心驾驶行为实时检测,并通过开展与其他模型的对比试验、所提模型的消融试验和模型注意力区域的可视化试验充分验证了所提模型的优越性。本文所提模型的平均分类准确率和精确率分别为96.93%和96.95%,模型参数量为21.22 M,基于真实车辆平台在线推理速度为23.32 fps,表明所提模型能够实现实时分心驾驶行为检测。研究结果有利于人机共驾系统的控制策略制定和分心预警。 展开更多
关键词 汽车工程 分心驾驶行为检测模型 视觉Transformer 多头注意力机制 卷积神经网络 tokens降维
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Non‑fungible tokens:a bubble or the end of an era of intellectual property rights
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作者 Elli Kraizberg 《Financial Innovation》 2023年第1期777-796,共20页
The viability of exponentially growing non-fungible token(NFT)market is evaluated by identifying potential value-generating mechanisms that can be rationalized.After identifying the value-generating mechanisms underly... The viability of exponentially growing non-fungible token(NFT)market is evaluated by identifying potential value-generating mechanisms that can be rationalized.After identifying the value-generating mechanisms underlying the positive values of NFTs,this study establishes a pricing model for NFTs that follows a continuous-time financial framework.As NFTs are claimed to securitize“ownership rights short of use”,and as such they may potentially serve as a substitute for the need to rely replace the reliance on the legal protection provided by intellectual property rights(IPRs).Considering this issue,this study evaluates the likelihood that NFTs will replace existing mechanisms that protect producers’rightful claim to use their assets or the need to apply the legal code that governs IPRs.The financial condition for this potential shift is derived for a category of assets whose use or consumption does not reduce supply as the notion of scarcity does not apply. 展开更多
关键词 Non-fungible tokens Intellectual property rights STATUS
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Computational Results on Quadratic Functional Model for the Tokens of Nuclear Safety
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作者 Joseph Olorunju Omolehin Lukuman Aminu Kamilu Rauf 《American Journal of Computational Mathematics》 2013年第1期6-15,共10页
In this work, Nuclear Reactor safety was modeled inform of quadratic functional. The nuclear tokens are structured and used as elements of the control matrix operator in our quadratic functional. The numerical results... In this work, Nuclear Reactor safety was modeled inform of quadratic functional. The nuclear tokens are structured and used as elements of the control matrix operator in our quadratic functional. The numerical results obtained through Conjugate Gradient Method (CGM) algorithm identify the optimal level of safety required for Nuclear Reactor construction at any particular situation. 展开更多
关键词 CONTROL OPERATOR NUCLEAR tokens CGM ALGORITHM OPTIMAL
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Tokenomics in the Metaverse:understanding the lead-lag effect among emerging crypto tokens
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作者 Chong Guan Wenting Liu +1 位作者 Yinghui Yu Ding Ding 《Financial Innovation》 2024年第1期1539-1557,共19页
The convergence of blockchain and immersive technologies has resulted in the popularity of Metaverse platforms and their cryptocurrencies,known as Metaverse tokens.There has been little research into tokenomics in the... The convergence of blockchain and immersive technologies has resulted in the popularity of Metaverse platforms and their cryptocurrencies,known as Metaverse tokens.There has been little research into tokenomics in these emerging tokens.Building upon the information dissemination theory,this research examines the role of trading volume in the returns of these tokens.An empirical study was conducted using the trading volumes and returns of 197 Metaverse tokens over 12 months to derive the latent grouping structure with spectral clustering and to determine the relationships between daily returns of different token clusters through augmented vector autoregression.The results show that trading volume is a strong predictor of lead-lag patterns,which supports the speed of adjustment hypothesis.This is the first large-scale study that documented the lead-lag effect among Metaverse tokens.Unlike previous studies that focus on market capitalization,our findings suggest that trade volume contains vital information concerning cross-correlation patterns. 展开更多
关键词 Tokenomics Lead-lag Metaverse tokens Trade volume Daily returns
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Return and volatility spillovers between non-fungible tokens and conventional currencies:evidence from the TVP-VAR model
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作者 Imran Yousaf Manel Youssef Mariya Gubareva 《Financial Innovation》 2024年第1期1974-1995,共22页
This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens(NFTs)and conventional currencies using the time-varying parameter vector autoregressions approach.We reveal t... This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens(NFTs)and conventional currencies using the time-varying parameter vector autoregressions approach.We reveal that the total connectedness between these markets is weak,implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs.We also find that NFTs are net transmitters of both return and volatility spillovers;however,in the case of return spillovers,the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions.The dynamic exercise reveals that the returns and volatility spillovers vary over time,largely increasing during the onset of the Covid-19 crisis,which deeply affected the relationship between NFTs and the conventional currencies markets.Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises. 展开更多
关键词 Non-fungible tokens Conventional currencies Static connectedness Dynamic return and volatility spillovers TVP-VAR model Covid-19
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Extreme connectedness between cryptocurrencies and non-fungible tokens:portfolio implications
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作者 Waild Mensi Mariya Gubareva +2 位作者 Khamis Hamed Al-Yahyaee Tamara Teplova Sang Hoon Kang 《Financial Innovation》 2024年第1期1604-1630,共27页
We analyze the connectedness between major cryptocurrencies and nonfungible tokens(NFTs)for different quantiles employing a time-varying parameter vector autoregression approach.We find that lower and upper quantile s... We analyze the connectedness between major cryptocurrencies and nonfungible tokens(NFTs)for different quantiles employing a time-varying parameter vector autoregression approach.We find that lower and upper quantile spillovers are higher than those at the median,meaning that connectedness augments at extremes.For normal,bearish,and bullish markets,Bitcoin Cash,Bitcoin,Ethereum,and Litecoin consistently remain net transmitters,while NFTs receive innovations.However,spillover topology at both extremes becomes simpler—from cryptocurrencies to NFTs.We find no markets useful for mitigating BTC risks,whereas BTC is capable of reducing the risk of other digital assets,which is a valuable insight for market players and investors. 展开更多
关键词 Cryptocurrencies Nonfungible tokens Extreme quantile connectedness Time-varying parameter vector autoregression TVP-VAR approach
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Love Tokens of Tibetan Herdsmen
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作者 Ye Yuling 《China's Tibet》 2008年第1期29-33,共5页
Tibet is a large,isolated land with a harsh climate.Previously,herdsmen lived in scattered remote areas.Although cultural
关键词 Love tokens of Tibetan Herdsmen
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Empirical evidence on the ownership and liquidity of real estate tokens 被引量:1
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作者 Laurens Swinkels 《Financial Innovation》 2023年第1期1246-1274,共29页
To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financi... To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices. 展开更多
关键词 Blockchain Cryptocurrency Real estate TOKENIZATION
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一种面向地图综合建筑多边形化简的Transformer模型
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作者 刘鹏程 成晓强 +2 位作者 肖天元 杨敏 艾廷华 《测绘学报》 北大核心 2026年第1期124-137,共14页
针对地图综合中建筑多边形化简方法依赖人工规则、自动化程度低且难以利用已有化简成果的问题,本文提出了一种基于Transformer机制的建筑多边形化简模型。该模型首先把建筑多边形映射至一定范围的网格空间,将建筑多边形的坐标串表达为... 针对地图综合中建筑多边形化简方法依赖人工规则、自动化程度低且难以利用已有化简成果的问题,本文提出了一种基于Transformer机制的建筑多边形化简模型。该模型首先把建筑多边形映射至一定范围的网格空间,将建筑多边形的坐标串表达为网格序列,从而获取建筑多边形化简前后的Token序列,构建出建筑多边形化简样本对数据;随后采用Transformer架构建立模型,基于样本数据利用模型的掩码自注意力机制学习点序列之间的依赖关系,最终逐点生成新的简化多边形,从而实现建筑多边形的化简。在训练过程中,模型使用结构化的样本数据,设计了忽略特定索引的交叉熵损失函数以提升化简质量。试验设计包括主试验与泛化验证两部分。主试验基于洛杉矶1∶2000建筑数据集,分别采用0.2、0.3和0.5 mm 3种网格尺寸对多边形进行编码,实现了目标比例尺为1∶5000与1∶10000的化简。试验结果表明,在0.3 mm的网格尺寸下模型性能最优,验证集上的化简结果与人工标注的一致率超过92.0%,且针对北京部分区域的建筑多边形数据的泛化试验验证了模型的迁移能力;与LSTM模型的对比分析显示,在参数规模相近的条件下,LSTM模型无法形成有效收敛,并生成可用结果。本文证实了Transformer在处理空间几何序列任务中的潜力,且能够有效复用已有化简样本,为智能建筑多边形化简提供了具有工程实用价值的途径。 展开更多
关键词 地图综合 建筑多边形化简 TOKENIZATION Transformer模型 上下文工程
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CMPTA:预训练大模型在多模态情感分析任务中的应用研究
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作者 李志豪 智宇 陈昂 《计算机科学与应用》 2026年第1期281-294,共14页
大语言模型(LLMs)在自然语言处理领域取得了显著进展,但将其有效迁移至多模态情感分析(MSA)任务仍面临巨大挑战。主要难点在于如何弥合异构模态(如视觉、音频)特征与预训练文本大模型语义空间之间的鸿沟。现有方法多依赖复杂的深度融合... 大语言模型(LLMs)在自然语言处理领域取得了显著进展,但将其有效迁移至多模态情感分析(MSA)任务仍面临巨大挑战。主要难点在于如何弥合异构模态(如视觉、音频)特征与预训练文本大模型语义空间之间的鸿沟。现有方法多依赖复杂的深度融合网络或昂贵的全量微调,难以充分利用大模型的推理与泛化能力。为此,本文提出了一种轻量级的跨模态伪Token适配器(Cross-Modal Pseudo-Token Adapter, CMPTA)。该方法并不破坏大模型的原有参数,而是通过高效的注意力机制,将非文本模态特征转化为LLM可理解的“伪Token”(Pseudo-Tokens),并以软提示(Soft Prompts)的形式注入文本输入序列,从而实现多模态信息与文本语义的深度对齐。此外,本文还系统探究了伪Token数量对模型语义对齐效果的影响规律。实验结果表明,CMPTA能够有效激发大模型的多模态情感理解能力,其性能优于当前的先进基线方法,验证了该框架的有效性与泛化能力。 展开更多
关键词 多模态情感分析 大语言模型 伪Token 参数高效微调 跨模态适配器
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A Transformer-Based Deep Learning Framework with Semantic Encoding and Syntax-Aware LSTM for Fake Electronic News Detection
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作者 Hamza Murad Khan Shakila Basheer +3 位作者 Mohammad Tabrez Quasim Raja`a Al-Naimi Vijaykumar Varadarajan Anwar Khan 《Computers, Materials & Continua》 2026年第1期1024-1048,共25页
With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contex... With the increasing growth of online news,fake electronic news detection has become one of the most important paradigms of modern research.Traditional electronic news detection techniques are generally based on contextual understanding,sequential dependencies,and/or data imbalance.This makes distinction between genuine and fabricated news a challenging task.To address this problem,we propose a novel hybrid architecture,T5-SA-LSTM,which synergistically integrates the T5 Transformer for semantically rich contextual embedding with the Self-Attentionenhanced(SA)Long Short-Term Memory(LSTM).The LSTM is trained using the Adam optimizer,which provides faster and more stable convergence compared to the Stochastic Gradient Descend(SGD)and Root Mean Square Propagation(RMSProp).The WELFake and FakeNewsPrediction datasets are used,which consist of labeled news articles having fake and real news samples.Tokenization and Synthetic Minority Over-sampling Technique(SMOTE)methods are used for data preprocessing to ensure linguistic normalization and class imbalance.The incorporation of the Self-Attention(SA)mechanism enables the model to highlight critical words and phrases,thereby enhancing predictive accuracy.The proposed model is evaluated using accuracy,precision,recall(sensitivity),and F1-score as performance metrics.The model achieved 99%accuracy on the WELFake dataset and 96.5%accuracy on the FakeNewsPrediction dataset.It outperformed the competitive schemes such as T5-SA-LSTM(RMSProp),T5-SA-LSTM(SGD)and some other models. 展开更多
关键词 Fake news detection tokenization SMOTE text-to-text transfer transformer(T5) long short-term memory(LSTM) self-attention mechanism(SA) T5-SA-LSTM WELFake dataset FakeNewsPrediction dataset
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Trade Tokens
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作者 By CHEN WEN 《Beijing Review》 2006年第18期14-15,共2页
In the pursuit of balanced trade with the U.S., China pours it on where it counts A week ahead of Chinese President Hu Jintao's first state visit to the United States, Beijing and Washington reached a series of ag... In the pursuit of balanced trade with the U.S., China pours it on where it counts A week ahead of Chinese President Hu Jintao's first state visit to the United States, Beijing and Washington reached a series of agreements intended to ease the bilateral trade imbalance, including resuming trade in U.S. beef, increasing Chinese market access to U.S. medical devices, telecom services and express delivery, and cracking down on intellectual property rights infringements. 展开更多
关键词 Trade tokens JCC
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Tokenomics and blockchain tokens: A design-oriented morphological framework 被引量:2
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作者 Pierluigi Freni Enrico Ferro Roberto Moncada 《Blockchain(Research and Applications)》 2022年第1期80-95,共16页
Blockchain technology has been around for more than ten years,nevertheless,the knowledge about its economic and business implications is still fragmented and heterogeneous.The present article intends to tackle this is... Blockchain technology has been around for more than ten years,nevertheless,the knowledge about its economic and business implications is still fragmented and heterogeneous.The present article intends to tackle this issue with a twofold contribution.The first is an analysis of the shift from economics to tokenomics highlighting the central role played by tokens within blockchain-based ecosystems.The second is a framework for tokens design leveraging a morphological analysis deeply grounded in the literature.As blockchain becomes a mainstream phenomenon,the value of the work proposed lies in lowering the cognitive barriers and in clarifying the space of available options for private and public actors willing to leverage tokenization in their daily operations. 展开更多
关键词 Blockchain TOKENIZATION Tokenomics Classification framework Token design
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THE MEANING OF FROZEN TOKENS IN LIVE NETS
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作者 陆维明 A.MERCERON 《Science China Mathematics》 SCIE 1989年第4期459-469,共11页
A concurrent system can be modeled by a Petri net. A live Petri net may have fro-zen tokens. It is showed that such tokens can be deleted if they are superfluous, and, whilethey are useful, can be defrozen if they bec... A concurrent system can be modeled by a Petri net. A live Petri net may have fro-zen tokens. It is showed that such tokens can be deleted if they are superfluous, and, whilethey are useful, can be defrozen if they became frozen due to unfair occurrences of tran-sitions, and, finaloy, some frozen tokens lead to more processes. 展开更多
关键词 FROZEN TOKEN LIVE net UNFAIR occurrence.
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DeepSeek-R1是怎样炼成的? 被引量:85
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作者 张慧敏 《深圳大学学报(理工版)》 北大核心 2025年第2期226-232,共7页
简述DeepSeek系列模型在大模型训练中的创新和优化.DeepSeek系列模型的突破主要体现在模型架构、算法创新、软硬件协同优化及整体训练效率的提升.DeepSeek-V3模型采用混合专家(mixture of experts,MoE)模型架构,通过细粒度设计和共享专... 简述DeepSeek系列模型在大模型训练中的创新和优化.DeepSeek系列模型的突破主要体现在模型架构、算法创新、软硬件协同优化及整体训练效率的提升.DeepSeek-V3模型采用混合专家(mixture of experts,MoE)模型架构,通过细粒度设计和共享专家策略,实现计算资源的高效利用;MoE模型架构中的稀疏激活机制和无损负载均衡策略显著提高了模型训练的效率和性能;多头潜在注意力(multi-head latent attention,MLA)机制通过减少内存使用和加速推理过程,降低了模型训练和推理成本;通过引入多token预测(multi-token prediction,MTP)和8位浮点数(floating point 8-bit,FP8)混合精度训练技术,提升了模型的上下文理解能力和训练效率;采用优化并行线程执行(parallel thread execution,PTX)代码显著提高了图形处理器(graphics processing unit,GPU)的计算效率;所提群体相对策略优化(group relative policy optimization,GRPO)对DeepSeek-R1-Zero模型进行纯强化学习训练,跳过了传统的监督微调和人类反馈阶段,显著提升了模型的推理能力.总体而言,DeepSeek系列模型通过多项创新,在人工智能领域取得了显著优势,树立了行业新标杆. 展开更多
关键词 人工智能 DeepSeek 大语言模型 混合专家模型 多头潜在注意力机制 多token预测 混合精度训练 群体相对策略优化
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Markets in crypto‑assets regulation:Does it provide legal certainty and increase adoption of crypto‑assets? 被引量:1
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作者 Tina van der Linden Tina Shirazi 《Financial Innovation》 2023年第1期509-538,共30页
This study discusses the European Union’s proposal for a Regulation on Markets in Crypto-Assets,now subject to formal approval by the European Parliament.The objective is to explore whether it will positively impact ... This study discusses the European Union’s proposal for a Regulation on Markets in Crypto-Assets,now subject to formal approval by the European Parliament.The objective is to explore whether it will positively impact the adoption of crypto-assets in the financial sector.The use of crypto-assets is growing.However,some stakeholders in the financial service sector remain skeptical and hesitant to adopt assets that are yet to be defined and have an unclear legal status.This regulatory uncertainty has been identified as the primary reason for the reluctant adoption.The proposed regulation(part of the EU’s Digital Finance Strategy)aims to provide this legal certainty for currently unregulated crypto-assets.This study investigates whether or not the proposed regulation can be expected to have the intended effect by reviewing the proposed regulation itself,the opinions and reactions of the various stakeholders,and secondary literature.Findings reveal that such regulation will most likely not accelerate the adoption of crypto-assets in the EU financial services sector,at least not sufficiently or as intended.Some suggestions are made to improve the proposal. 展开更多
关键词 MiCA regulation Crypto-assets Legal certainty Blockchain Distributed ledger technology Utility tokens Stablecoins Asset-referenced tokens e-money tokens
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抑制非目标干扰的单流纯Transformer跟踪算法
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作者 顾龙雨 张伟 高赟 《计算机应用》 北大核心 2025年第S1期60-66,共7页
针对单流纯Transformer跟踪算法搜索区域中的相似信息或混乱背景等非目标信息的干扰会影响相关性计算的问题,提出一种抑制非目标干扰的单流纯Transformer跟踪算法。首先,构建抑制非目标干扰模块,该模块采用高相似token合并策略,当高相似... 针对单流纯Transformer跟踪算法搜索区域中的相似信息或混乱背景等非目标信息的干扰会影响相关性计算的问题,提出一种抑制非目标干扰的单流纯Transformer跟踪算法。首先,构建抑制非目标干扰模块,该模块采用高相似token合并策略,当高相似token包含目标信息时,合并操作将保留目标信息,当高相似token包含混乱背景或相似目标干扰信息时,合并操作将降低这些干扰信息的注意力权重;其次,将该模块添加到单流纯Transformer骨干网络中,以抑制干扰多头注意力的计算结果;最后,将抑制干扰后的特征送进跟踪头,从而完成对目标的跟踪。在5个基准数据集上的测试结果表明:与OSTrack(One Stream Tracking)算法相比,在GOT-10k基准数据集AO指标提升1.1个百分点,在NFS、UAV123、TNL2K基准数据集AUC指标分别提升1.6、1.0、1.1个百分点,同时所提算法的跟踪推理速度即每秒帧数(FPS)可达166,证明所提算法成功抑制了非目标的干扰,提升了单流纯Transformer跟踪算法的鲁棒性并且能够保证跟踪的实时性。 展开更多
关键词 目标跟踪 视觉Transformer 干扰抑制 逐层合并的高相似token 多头注意力
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