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写在《科技之魅》的前面Preface
to
the
Charm
of
Science
and
Technology科技的魅力在于创新,从“万物互联”到“万物智联”,科技发展赋能经济社会生产生活,引领人类迈向数字世界,不断触摸前沿科技发展脉动,创造美好的数字未来。The
charm
of
technology
lies
in
innovation.
From
the
"Internet
of
Everything"
to
the
"ArtificialIntelligence
of
Everything",
technological
advances
empower
the
economic
and
social
aspectsof
production
and
life,
leading
human
society
into
the
digital
world.
It
touches
the
pulse
of
cut-ting-edgetechnologicaldevelopment,creatingapromisingdigitalfuture.当前,以互联网为代表的新一轮科技革命和产业变革深入演进,6G、人工智能、量子计算等新兴技术进入发展快车道,数字化、网络化、智能化进程全面提速。在此时代背景下,“世界互联网领先科技成果发布活动”升级为“世界互联网大会领先科技奖”,在展现全球互联网领域最新科技成果、彰显互联网从业者的创造性贡献、搭建全方位的创新交流平台等方面将发挥更加重要的作用。A
new
wave
of
technological
revolution
and
industrial
transformation
is
unfolding,
with
theInternet
serving
as
a
key
driver.
Emerging
technologies
such
as
6G,
artificial
intelligence,
andquantum
computing
are
advancing
rapidly.
The
processes
of
digitization,
networking,
and
intel-ligence
is
accelerating
at
an
unprecedented
pace.
In
this
context,
"the
Release
Ceremony
forWorld
Leading
Internet
Scientific
and
Technological
Achievements"
has
been
upgraded
to
"theWorld
Internet
Conference
Awards
for
Pioneering
Science
and
Technology".
This
upgrade
aimsto
play
a
more
significant
role
in
showcasing
the
latest
technological
accomplishments
in
theglobal
Internet
field,
highlighting
the
creative
contributions
of
Internet
practitioners,
and
foster-ingacomprehensiveplatformforinnovationexchanges.作为世界互联网大会领先科技奖评审委员会主席,我欣喜看到本年度成果征集持续得到全球范围的广泛关注和积极响应。今年成果首次区分基础研究、关键技术与工程研发三种类型。在基础研究组主任委员美国互联网先驱戴夫·法伯先生,关键技术组主任委员中国工程院院士吴建平先生,工程研发组主任委员韩国互联网之父全吉男教授等
40
位中外专家的支持下,我们共征集到来自中国、美国、俄罗斯、英国、意大利、日本、韩国、阿联酋等多个国家及地区的领先科技成果
246
项,涵盖
人工智能、5G、6G、大数据、网络安全、高性能芯片、工业互联网等众多前沿科技领域。经过专家推荐,57
项优秀成果,收录于本年度《科技之魅》成果手册。我们相信,这些成果的不断转化落地,将更好地推动经济社会韧性发展,为构建网络空间命运共同体、推动人类文明进步提供更多可能。As
the
chairman
of
the
World
Internet
Conference
Awards
for
Pioneering
Science
and
Tech-nology
Review
Committee,
I
am
thrilled
to
see
the
global
attention
and
positive
responses
thisyear's
collection
of
achievements
has
received.
This
year,
for
the
first
time,
the
achievements世界互联网大会领先科技奖评审委员会World
Internet
ConferenceAwards
for
Pioneering
Science
andTechnology
Review
Committeehave
been
categorized
into
three
types:
Basic
Research,
Key
Technology,
and
EngineeringResearch
and
Development.
With
the
support
of
40
experts
from
all
over
the
world,
includingMr.
David
Farber,
an
American
Internet
pioneer
and
the
Director
of
the
Basic
Research;
Mr.
WuJianping,
an
Academician
of
the
Chinese
Academy
of
Engineering
and
the
Director
of
the
KeyTechnology;
and
Professor
Chon
Kilnam,
the
Father
of
the
Korean
Internet
and
the
Director
ofthe
Engineering
Research
and
Development,
we
have
collected
a
total
of
246
achievementsfrom
countries
and
regions,
such
as
China,
the
United
States,
Russia,
the
United
Kingdom,Germany,
Italy,
Japan,
Korea,
and
the
United
Arab
Emirates.
These
achievements
cover
a
widerange
of
cutting-edge
technological
fields,
including
artificial
intelligence,
5G,
6G,
big
data,
cy-bersecurity,
high-performance
chips,
and
the
industrial
Internet.
After
thorough
review
by
theexperts,
57
leading
achievements
have
been
selected
and
compiled
into
a
publication
called"The
Charm
of
Science
and
Technology".
We
firmly
believe
that
the
continued
implementationof
these
achievements
will
better
promote
resilient
economic
and
social
development,
offermore
possibilities
for
building
community
with
a
shared
future
in
cyberspace
and
advance
hu-mancivilization.邬贺铨WU,Hequan主席
Chair中国工程院院士AcademicianoftheChinese
AcademyofEngineering戴夫·法伯FARBER,David基础研究组主任委员
DirectorofBasicResearch星燧贸迁,晷刻渐移。伴随着世界互联网大会国际组织的发展,《科技之魅》将持续记录互联网科技创新的非凡成就。希望《科技之魅》持续传递互联网创新发展的智慧与力量,美国互联网先驱、日本庆应义塾大学荣誉教授和网络文明研究中心联席主席引领未来互联网技术发展方向,为国际交流互鉴和科技成果转化拓展更为广阔
的空间。Pioneerofthe
AmericanInternetDistinguishedProfessorandco-directoroftheCyberCivilizationResearchCenteratKeioUniversityWith
the
passage
of
time
and
the
evolution
of
the
World
Internet
Conference,
the
Charm
ofScience
and
Technology
will
continue
to
document
the
extraordinary
achievements
of
Internettechnological
innovation.
We
aspire
for
this
publication
to
consistently
transmit
the
wisdom
andpower
of
Internet
innovative
development,
guide
the
future
direction
of
Internet
technology
andprovide
a
broader
space
for
international
exchange,
mutual
learning,
and
the
transformation
oftechnologicalachievements.吴建平WU,Jianping关键技术组主任委员
DirectorofKey
Technology中国工程院院士、清华大学教授AcademicianofChinese
AcademyofEngineeringProfessorof
Tsinghua
University全吉男CHON,Kilnam工程研发组主任委员
DirectorofEngineeringResearchandDevelopment韩国互联网之父、韩国科学技术院荣誉教授FatheroftheKoreanInternetProfessorEmeritusoftheKorea
AdvancedInstituteofScienceand
Technology目录世界互联网大会领先科技奖获奖成果CONTENTSLeading
Achievementsof
World
InternetConference
Awards
forPioneeringScienceand
Technology基础研究组
Basic
ResearchIBM
生成式人工智能
watsonx:企业级
AI
的未来060IBMwatsonx:
TheGenerative
AIforBusiness多层次多元知识融通的自然语言深度学习基础方法002Multi-Level
Multi-Type
Knowledge
Fused
Deep
Learning
FundamentalMethodsforNaturalLanguages工程研发组
Engineering
Research
and
Development视觉媒体的层次化内容感知008012ARGO:机车车辆的自主检查机器人066068072HierarchicalContentPerceptionofVisualMediaARGO:
AutonomousInspectionofRollingStocks5G
移动通信系统高能效机理研究卡巴斯基汽车安全网关(基于卡巴斯基操作系统)Research
on
High-Efficiency
Mechanisms
in
5G
Mobile
CommunicationSystemKaspersky
AutomotiveSecureGateway(basedonKasperskyOSoperatingsystem)腾讯觅影数智医疗影像平台关键技术组
Key
TechnologyTencent
AIMISMedicalImagingPlatformofDigitalIntelligenceC-V2X
车联网通信关键技术研究与应用018Research
and
Application
of
Key
Cellular
Vehicle-to-Everything
(C-V2X)TechnologiesGaussDB:分布式数据库024034GaussDB:DistributedDatabase知识增强大语言模型关键技术TheKey
TechnologiesofKnowledge-enhancedLargeLanguageModel4G/5G
移动通信共建共享关键技术创新与产业化038Technological
Innovation
and
IndustrialApplications
of
4G-5G
Co-constructionandSharing中国联通全光底座关键技术创新与应用044048052All-OpticalInfrastructureInnovationand
ApplicationofChinaUnicom智慧油田工业物联网
WIA-PA
技术与系统IIoT
WIA-PA
Technology
andSystemofIntelligentOilfield全球首个
5GAdvanced-ready
调制解调器及射频系统TheWorld'sFirst5G
Advanced-ReadyModem-RFSystem大规模云网融合系统内容高效可靠分发与主动防御技术研发及产业化056Research
and
Development
and
Industrialization
of
Efficient,
Reliable
Distrib-uted
Content
and
Proactive
Defense
Technologies
for
Large-scale
Cloud-net-workConvergenceSystems目录《科技之魅》收录成果CONTENTSCharmof
Scienceand
Technology
Collection基础研究组
Basic
Research面向体育赛事
8K
高清视频转播应用的太赫兹高速无线通信系统128132Terahertz
High-speed
Wireless
Communication
Systems
for
8K
High-definition低剂量
CT
智能成像理论与方法VideoBroadcastingandSportsEvents078082AliOSDrive
智能驾驶操作系统TheoryandMethodsofIntelligentLow-DoseCT
Imaging跨空间大数据关联表征学习理论与方法AliOSDriveOperatingSystemsfor
AutonomousVehiclesTheory
and
Method
of
Cross-space
Big
Data
Correlational
RepresentationalLearningZDNS
下一代互联网基础资源寻址关键技术、国际标准及应用136ZDNS
Key
Technologies,
International
Standards
and
Applications
of
Next-现代处理器重
大漏洞发现Generation
AddressingSystemforInternet086ExposingtheMajorVulnerabilitiesinModernProcessors超高清国产技术标准及低延迟视频云化直播制播技术创新及应用140面向全生命周
期的可信数据管理理论与方法092096Innovation
and
Application
of
UHD
Technology
Standards
and
Low-latencyVideoCloud-basedLiveBroadcasting
TechnologyFullLifecycle
TrustedDataManagement:
TheoryandMethod智感波束技术多模态情感脑机接口的情绪表征机理研究144148InterferenceSensingResearch
on
Emotion
Representation
Mechanisms
for
Multimodal
AffectiveBrain-ComputerInterfaces趣链区块链平台面向复杂场景视觉理解的高效率神经网络方法Technological
Achievement:Hyperchain100Efficient
Neural
Network
Approaches
for
Visual
Understanding
in
ComplexScenes面向通感算传泛在融合的视联算力系统创新与应用面向复杂决策的核空间和因果推理方法152Innovation
and
Application
of
Internet
of
Video
Things
Computing
(IoVTC)104System
for
Ubiquitous
Integration
of
Communication,
Sensing,
Computation,and
TransmissionKernelSpaceandCausalReasoningMethodsforComplexDecision-Making面向知识工作者的个性化轻量大语言模型大象
GPT关键技术组
Key
Technology156EverGPT:
A
Personalized
Lightweight
Large
Language
Model
for
KnowledgeWorkers华为云盘古大模型5G-TSN
协同组网及关键技术110114118160164168HuaweiCloudPanguModelsKey
Technologiesfor5G-TSNCooperationNetwork大型
IPv6
单栈网络技术创新与规模部署多链云端集成
IDELargeIPv6-onlyNetwork
Technology
InnovationandScaleDeploymentCloud-basedMulti-chainIDE讯飞星火认知大模型生物数据隐私计算平台IFLYTEK
SPARK
CognitiveLargeLanguageModelBiodataPrivacyComputationPlatform基于
B5G
融合感知的城市数字道路关键技术研究及示范应用面向数控装备的工业互联网一体化解决方案
iNC-Cloud124172Key
Technology
Research
and
Applications
of
Urban
Digital
Road
Based
onB5GFusionPerceptionIndustrialInternetIntegrationSolutionforCNCEquipment-iNC-Cloud目录《科技之魅》收录成果Charmof
Scienceand
Technology
CollectionCONTENTS数据活化的关键技术及其智慧城市应用安全可溯源的
VoWiFi
技术创新及应用示范176224Key
TechnologiesofDataVitalizationand
Their
ApplicationsinSmartCitySecureand
TraceableVoWiFiTechnology
Innovationand
ApplicationDemonstration空间超大规模卫星网络仿真验证系统工程研发组
Engineering
Research
and
Development228232234TheSimulationandVerificationSystemforMega-scaleSatelliteNetwork5G
光芯片曙光
ParaStor
液冷存储系统1821845GOpticalChipSugonParaStorLiquid-CooledStorageSystem“星火·链网”数据服务网络崖山数据库系统XinghuoBIFDataServiceNetworkYashanDBNEC:基于先进的“因果数据分析”引擎技术的
AI
健康管理系统云地协同的新一代人工智能安全引擎238188Next-generationCloud-localCollaborative
AISecurityEngineNEC:
AI
Health
Management
System
Based
on
Advanced
Causality
AnalysisEngine
Technology云边端协同的视联网技术创新与超大规模应用实践高精度动态地图基础平台242192198202InnovationinIoVT
(InternetofVideo
Things)
TechnologyandUltra-Large-ScaleApplicationEnabledbyCloud-Edge-DeviceCollaborationHDDynamicMapBasicPlatform基于忆阻器的存算一体
SoC
芯片及计算引擎福瑞泰克
ODIN
智能驾驶数智底座246250TheReRAM-BasedCompute-In-MemorySoCandSoftwareEngineFreetechODINIntelligentDrivingPlatformTheranica:数字疼痛
治疗管理设备
Nerivio隐私运营及管理中台Theranica:DigitalPain
TreatmentManagementEquipmentNerivioPrivacyOperationandManagementHub(POH)“源图”开源软件供应链重
大基础设施206Open
Source
Map:
A
Major
Infrastructure
for
Open
Source
Software
SupplyChain锂电池储能系统安全防控成套装备研制及其工程化212Development
and
Engineering
of
Safety
and
Control
Complete
Equipment
forLithiumBatteryEnergyStorageSystem新一代
AGI
基础设施:商汤大装置
SenseCore
与商汤日日新
SenseNova大模型体系216Next-generation
AGI
Infrastructure:
SenseCore
AI
Infrastructure
andSenseNovaFoundationModelSet翼龙平台220Yilong世界互联网大会Collectionof
Shortlisted
Achievements
ofWorld
Internet
Conference
Awards
forPioneering
Science
and
Technology领先科技奖收录成果集世界互联网大会领先科技奖获奖成果Leading
Achievements
of
World
Internet
ConferenceAwards
forPioneeringScienceandTechnology基础研究组BasicResearch科技之魅Charm
of
Science
and
Technology多层次多元知识融通的自然语言深度法、实体嵌入桥接的知识增强型句of
deep
learning
in
NLP,
significantly
enhancing
the
fundamental
capabilities
of
NLPmodels.学习基础方法级语言建模方法以及多粒度注意力机制驱动的语言模型与知识系统协同方法,突破了自然语言深度学习ӮኴᎣᦩᶆ᠍ᔰސԧಯလ௶ዐܻᡩᛘየዐዤጱෛ᪠ஆ̶ਙऩᑍӮኴጱḮ̶ŏŏᓤᒍ੶的若干重要瓶颈制约,显著提升了Multi-Level
Multi-Type
Knowledge
Fused
Deep
Learning
Funda-mentalMethodsforNaturalLanguagesᛘየࢩᔰ自然语言处理模型的基本能力。���ಪګ��!ᤉኞᇔં"$'()ᶆ᠍ᔰސԧಯလ௶ዐܻᡩᛘየዐዤጱෛ᪠ஆ̶ਙऩᑍӮኴጱḮ̶���ݙ੶This
project
addresses
three
profoundchallenges:
the
insufficient
ability
ofword-level
embedding
representations
toutilize
linguistic
knowledge
comprehen-sively,
the
inadequate
proactive
aware-nessofworldknowledgebysentence-lev-el
language
models,
and
the
insufficientabilityoflanguagemodelstodeeplyutilizeknowledge
systems.
A
relatively
completemulti-level
multi-type
knowledge
fuseddeep
learning
fundamental
methods
fornatural
languages
has
been
established.This
includes
the
word-level
embeddingmethod
integrating
multi-level
linguisticknowledge
of
senses,
morphemes,
andtopics;
the
knowledge-enhanced
sen-#$%&������Ꭳᦩ੶ᶆ᠍ᔰ
ŏ
ಯလ
ŏ
ዐዤ
ŏ
᪠ஆ
ŏ
Ḯ4567<=>?!"#!$%&'()*+,-./01234567MethodologySystemMulti-level
Multi-type
Knowledge
Fused
Deep
Learning
Fundamental
Methodsfor
Natural
Languageᔰ੶
ᶆ
᠍
ᔰ
ಯ
လ
ዐ
ዤ$+0RS$+0$!$+M,-0Z[ELTԎᶱ੶ېဩ
᭲᪠
᪠ᕚ
ᛔ᨟
ᛔᨮ)*TUV!TW/TUXYTStructuralHierarchyandAmbiguityofLanguageSemanticCombinabilityandOpennessofLanguageInteractionbetweenLanguageandKnowledgeKey
Features自然语言的多层次及多元知识123456\$+,-]/^_`Hab@2$+B?\cd,-&Le,`Hab$+B?\,-NOfD^_`HabInsufficientCapabilityofWord-levelEmbeddingstoComprehensivelyUtilizeLinguisticKnowledgeInsufficientProactiveAwarenessofWorldKnowledgeinSentence-levelLanguageModels89:;InsufficientCapabilityofLanguageModelstoDeeplyUtilizeKnowledgeSystemsTechnicalChallengesWorld
KnowledgeDocumentLevelᶆ᠍ᔰސԧಯလ௶ዐܻᡩᛘየዐዤጱෛ᪠ஆ̶ਙऩᑍӮኴጱḮ̶ŏŏ!"#$%#&'(2345
)*$+,-./09:34;<0,-=>?@2$+AB78(CDEFGHIJKL0$+B?M,-NOPQ78Word-levelEmbeddingMethodIntegratingMulti-levelLinguisticKnowledgeofSenses,Morphemes,andTopicsKnowledge-enhancedSentence-levelLanguageModelingthroughEntityEmbeddingBridgingCollaborationofLanguageModelandKnowledgeSystem
DrivenbyMulti-granularityMutualAttentionMechanismಪګinhibitthᛘeraየpeuticࢩfacᔰtor�����(malaria)(Artemisinin)ᤉኞᇔderivativeattrંibuteBasicAlgorithms12345678SentenceLevelᶆ᠍ᔰސԧಯလ௶ዐܻᡩᛘየዐዤጱෛ᪠ஆ̶ਙऩᑍӮኴጱḮ̶���(Plasmodium)Multiple
Levelsof
LanguageMultiple-TypeKnowledge多层次多元知识融通的自然语言深度学习基础方法体系架构��(disease)����(ArtemisininEster)The
Systematized
Framework
of
Multi-Level
Multi-Type
KnowledgeFusedDeepLearningFundamentalMethodsforNaturalLanguagestence-level
language
modeling
throughentity
embedding
bridging;
and
the
col-laboration
of
language
model
and
knowl-edge
system
driven
by
multi-granularitymutual
attention
mechanism.
significantbottlenecks
restricting
the
advancementLangᎣuaᦩge
KnowledgeWordLevelᶆ᠍ᔰŏಯလŏዐዤŏ
᪠ஆŏ
ḮMorphemeLevelᶆ᠍ᔰಯလዐ
ዤ多层次多元知识融通的自然语言深度学习基础方法体系框架Sense
Levelېဩ
᭲᪠
᪠ᕚ
ᛔ᨟
ᛔᨮThe
Systematized
Framework
of
Multi-Level
Multi-Type
Knowledge
Fused
Deep
Learning
FundamentalMethodsforNaturalLanguagesMultipleLevelsofNaturalLanguageandMulti-typeKnowledge清华大学TsinghuaUniversity华为技术有限公司HuaweiTechnologiesCo.,Ltd.引言自然语言处理是人工智能重
大前沿领域。清华大学与华为技术有限公A
world-class
multi-level
multi-type司多年来研究并建立了一套多层次多元知识融通的自然语言深度学习基础knowledge
fused
deep
learningfundamental
method
for
natural
lan-词典定义使能的词义表示与排歧一体化义项嵌入方法方法体系,在该方向学术创新和开源共享方面取得了具有国际领先性和影guageInputSentence响力的成果。本项目针对词级嵌入表示对K-nearestNeighborsinEmbedding
Spacebank(word)语言知识综合利用能力不足、句级Sense-levelPredictionIntroduction语言模型对世界知识主动感知能力Natural
Language
Processing
(NLP)
is
a
cutting-edge
research
field
in
artificial
intelli-gence.TsinghuaUniversityandHuaweiTechnologiesCoLtd.havedevotedasignificantattention
to
research
and
establishment
of
the
multi-level
multi-type
knowledge
fuseddeep
learning
fundamental
methods
for
natural
languages
in
the
past
years,
achievinginternationally
advanced
and
influential
outcomes
in
academic
innovation
and
open-sourcesharing.Word-levelPrediction不足以及语言模型对知识系统深度bank1
(sense)利用能力不足这三个深刻挑战,建Word
&
SenseFusionPredictionWordNet
definition:立了较为完整的多层次多元知识融SpatialProjectionbank2
(sense)通的自然语言深度学习基础方法体具有国际一流水平的多层次多元知识融通的自然语言深度学习系,包括义项、语素、主题多层次ObjectiveFunctionCentralWord基础方法语言知识融合的词级嵌入表示方Dictionary-enabledSenseRepresentationandDisambiguationIntegratedSenseEmbeddingMethod002003PAGEPAGE科技之魅Charm
of
Science
and
TechnologyScholar,
the
highest
single
paper
beingcited
1,250
times.
For
example,
one
of
therepresentative
papers
from
this
achieve-ments
stood
out
prominently
in
terms
ofacademic
influence
among
over
660
pa-pers
published
in
the
top
conference
ACL2019.
Li
Fei-Fei,
a
fellow
of
the
Americanacademies,
pointed
out
in
her
significantpaper
that
our
achievement
had
the
bestperformance
in
semantic
evaluation
atthe
time.
Tomas
Mikolov,
the
proponentof
the
renowned
Word2Vec
model,
alsomentioned
our
achievement
in
his
seminalwork.
The
team
of
Peter
Szolovits,
Fellowof
the
National
Academy
of
Medicine
anda
professor
at
Massachusetts
Institute
ofTechnology
(MIT),
adopted
one
of
ourachievements,
ERNIE,
as
the
foundationalframework
for
their
research.
They
fullyintegrated
it
with
medical
knowledgebases,
resulting
in
the
development
of
thec-ERNIE
medical
model
and
the
medicaldomain
intelligent
question-answeringsystem
M-cERNIE.
Other
notable
citersinclude
Dan
Jurafsky,
a
fellow
of
theAmerican
Academy
of
Arts
and
Sciencesand
a
professor
at
Stanford
University;Hinrich
Schütze,
the
chair
of
ACL2020and
a
chaired
professor
at
the
Universityof
Munich;
Christopher
Manning,
an
ACM/AAAI
fellow
and
director
of
the
StanfordArtificial
Intelligence
Laboratory
(SAIL);and
Yuji
Matsumoto,
an
ACL
fellow
and
arenownedNLPscholarinJapan.ERNIE0VWXYZ[\]1382
!"267“$%”ERNIE&'()*+!#!"ST./0TU5678&ERNIE899
!"202,-./012345678&K-BERT655!"94DEF.FGH&IJK/@ABCRIKEN78&LUKE352!"539!:;<=>?@ABCAI278&KnowBERT62!"12LMF.NOBPQ34RP78&HittER本成果之一
ERNIE
的开源影响知识增强的句级语言建模方法
ERNIEComparisonofERNIEwithSimilar
Open-SourceModelsRepresentativeOrganizations“forking”ERNIEInternationalDomestic1382stars
267forksERNIE,jointlyreleasedbyTsinghuaUniversityandHuawei899stars
202forksK-BERT,
co-releasedbyPekingUniversityandTencent655stars
94forksLUKE,releasedbyRIKEN,Japan’sappliedscienceresearchinstitute352stars
53forksKnowBERT,
releasedbyAllenInstitutefor
AI(AI2)62stars12forksHittER,releasedbyMicrosoftResearchTheOpen-sourceImpactofOneofThisAchievements,ERNIE具有国际认可度的语言与知识融通系列学术论文Knowledge-enhancedSentence-levelLanguageModelingMethodERNIEA
series
of
internationally
recognized
academic
papers
on
the
fusion
of
lan-guageandknowledge具有国际影响力的语言与知识融通开源系统本成果5
篇代表性论文得到了国际学术界较为广泛的关注,GoogleAn
internationally
influential
open-source
system
for
the
fusion
of
languageScholar
引用共
2697
次(最高单篇引用1250
次)。如:本成果的代表性the
world's
leading
influences
in
the
fieldandknowledgeof
deep
learning
for
natural
language论文之一在国际顶会
ACL
2019
发表的
660
余篇论文中学术影响力名列前基于该方法体系,我们在最具影响的国际开源平台
GitHub
上发布integration
with
knowledge.
Notably,
theforkers
include
tech
giants
like
Google,Microsoft,
Alibaba,
Tencent,
JD.com,
and茅;美国三院院士
Li
Fei-Fei
在其重要论文中指出本成果取得了当时语义了
4
个开源代码,形成了一套语言与知识融通的深度学习开源系统。共获评测的最好性能;著名
Word2Vec
模型的提出者Tomas
Mikolov
也在其2000
多个星标,500
余次复刻,在语言与知识融通的自然语言深度学习Baidu.
Our
achievement
has
been
suc-重要论文中提及本成果;美国国家医学院院士、MIT
教授
Peter
Szolovits方向上的开源影响居世界领先之列,复刻者包括谷歌、微软、阿里巴巴、cessfully
implemented
in
Huawei
Cloud,serving
over
150
countries
and
regionswith
significant
results
(Currently,
HuaweiCloud
holds
the
second-largest
marketshare
in
China
and
ranks
fifth
globally.It
serves
more
than
150
countries
andregions,
boasts
over
30,000
partnersworldwide,
accommodates
2.6
million
de-velopers,
and
has
listed
more
than
6,100applications
in
its
cloud
marketplace,making
it
highly
influential
on
the
globalstage).腾讯、京东、百度等科技公司。本成果己成功应用于华为云,服务
150
余知识库全面对接,发展出
c-ERNIE
医学模型和医学领域智能问答系统个国家和地区,取得良好效果(华为云目前市场份额中国排第二、世界排M-cERNIE。引用者还包括美国文学与科学院院士、斯坦福大学教授
Dan第五,服务
150
多个国家和地区,全球有超过
3
万家合作伙
伴,260
万Jurafsky,ACL2020
主席
、慕尼黑大学讲席
教授
Hinrich
Schütze,ACM/开发者,云市场上架应用超过6100个,在全球范围
具有较大影响力)。AAAI
会士、斯坦福
SAIL
实验室主任
Christopher
Manning,ACL
会士、日本著名
NLP
学者Yuji
Matsumoto
等。Based
on
this
algorithmic
framework,
we
have
released
4
open-source
software
onGitHub,themostinfluentialinternationalopen-sourceplatform,constitutingadeeplearn-ing
open-source
system
for
the
integration
of
language
and
knowledge.
This
system
hasgarnered
over
2,000
stars
and
has
been
forked
more
than
500
times,
ranking
it
amongThe
five
representative
papers
of
this
achievement
have
garnered
considerable
attentionfrom
the
international
academic
community,
with
a
total
of
2,697
citations
on
Google004005PAGEPAGE科技之魅Charm
of
Science
and
TechnologyPeter
Szolovits!""#$%&&'AAAI('!"$%)*%&+,-.·/012345678
9
:
;
<
%
=
IBM
>
?
@
A
BBioNLP2020
C
D
E
F
G
H
I
JERNIE
B%KLMNOPERNIEQRSTUVBWXYZN=$%[\]^_`aNbcA$%c-ERNIEdM-cERNIENe6f2BERTBghijklCDmnnopqrstERNIEN17uvw
ERNIENxycERNIEzM-cERNIE
{vw
43ukcERNIEB|}~Ä]EÅÇ`ÉÑÖmERNIEÜáJàâ本成果典型引用Peter
SzolovitsFellowoftheNationalAcademyofMedicine,AAAIFellow,The
AmericanMedicalInformatics
Association's"MorrisF.
Collen
Award
ofExcellence"In
the
BioNLP2020
paper
jointlyreleased
by
MIT
and
IBM,
they
highlypraised
ERNIE.
They
adopted
ERNIEas
the
foundationalframework
fortheirresearch,
fully
integrated
it
withmedical
knowledge
bases,
resulting
inthe
development
of
the
medical
c-ERNIE
and
M-cERNIE,
achievingexperimental
results
surpassing
BERT.The
paper
dedicated
an
entire
chapterto
detailing
ERNIE,
mentioning
it
17times,
and
with
the
inclusion
ofcERNIE
and
M-cERNIE,
ERNIE
wasreferencedatotalof43times.The
open-source
repository
for
cERNIEprovides
specific
instructions
on
how
touseERNIE.ATypicalCitationofThisAchievement006007PAGEPAGE科技之魅Charm
of
Science
and
Technology视觉媒体的层次化内容感知北京交通大学数字媒体信息处理团队和南开大学媒体计算实验室围object?
What
categories
do
these
pixelsbelong
to?
How
can
these
categoriesbe
further
subdivided?"
The
scope
ofthe
research
encompasses
image-levelmulti-object
perception,
object-level
spa-绕视觉媒体的层次化内容感知项目,以视觉媒体为主要研究对象,系统深入地研究了视觉内容层次化感知的相关理论和方法,形成了从图像级、物HierarchicalContentPerceptionofVisualMedia体级到像素级粗粒度及细粒度的递进感知理论和解决方案,回答了“图像有何物体,物体有何像素,像素是何类别,类别如何细分”的系列问题。tial
perception,
pixel-level
coarse-grainedperception,
and
pixel-level
fine-grained所涉及的研究内容包括图像级多物体感知、物体级位置感知、像素级粗粒度感知、像素级细粒度感知等。8
篇代表性论文成果均发表在国际顶级期刊
/
会议上,Google
引用超
6000
多次,部分论文为各自研究方向的早perception.
Eight
seminal
papers
havebeen
published
in
international
journalsandconferences,amassingover6,000ci-tations
on
Scholar.
Some
of
these期开拓性研究成果,并对相关方向的后续发展具有重要引领作用。成果papers
represent
pioneering
contributions得到了图灵奖获得者及
100
多位国际电气与电子工程师协会会士(IEEEintheirrespectiveresearchdirectionsandhave
significantly
influenced
subsequentdevelopments
in
related
fields.
The
workhas
garnered
attention
from
Turing
Awardwinners
and
over
100
IEEE
Fellows.
Ad-ditionally,
some
of
the
technologies
havebeen
integrated
as
standard
The
capa-bilities
in
hundreds
of
millions
of
Huaweismartphones.Fellow)
的关注,部分技术作为标配功能运行于上亿部华为旗舰手机上。The
Digital
Media
Information
Processing
Team
at
Beijing
Jiaotong
University,
in
partner-ship
with
the
Media
Computing
Laboratory
at
Nankai
University,
centered
their
researchon
hierarchical
content
perception
in
visual
media.
The
initiative
delves
systematicallyinto
the
theories
and
methodologies
related
to
hierarchical
perception
of
visual
content,establishingaprogressiveframeworkthatspansfromimage-levelandobject-leveltopix-el-level
perception,
both
in
coarse
and
fine-grained
resolutions.
This
research
addressesa
series
of
questions
such
as
"What
objects
are
in
the
image?
What
pixels
constitute
the图像级、物体级到像素级的递进层次化视觉内容感知理论和解决方案TheoreticalandPracticalApproachesto
ProgressiveHierarchicalVisualContentPerception:
FromImage-LeveltoObject-LeveltoPixel-Level北京交通大学BeijingJiaotongUniversity课题组研究成果系统性地回答了“图像有何物体,物体有The
research
outcomes
from
the
project
systematically
addressfundamental
questions
in
computer
vision
research,
such
as
"What
objects何像素,像素是何类别,类别如何细分”这一系列计算机南开大学视觉研究的基础问题are
present
in
the
image?
What
pixels
make
up
these
objects?
To
whichcategories
do
these
pixels
belong?
How
can
these
categories
be
furthersubdivided?"NankaiUniversity本研究揭示了不同层次化视觉内容理解任务的内在关联,促进进一步地,在像素级粗粒度感引言了视觉感知研究的发展知层面,揭示了图像级语义信息同如何模拟大脑的认知机制,实现高效且层次化的视觉内容感知一直是计
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