Xiangyu Zhang
E367296
Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Xiangyu Zhang canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T3542951 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xiangyu Zhang Context triple: [ResNet, developedBy, Xiangyu Zhang]
-
A.
Xiaodong Chen
Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
-
B.
Yuhuai Wu
Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
-
C.
Jun-Yan Zhu
Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
-
D.
Xindong Wu
Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
-
E.
Wei Liu
Wei Liu is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work on object detection.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xiangyu Zhang Target entity description: Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
-
A.
Xiaodong Chen
Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
-
B.
Yuhuai Wu
Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
-
C.
Jun-Yan Zhu
Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
-
D.
Xindong Wu
Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
-
E.
Wei Liu
Wei Liu is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work on object detection.
- F. None of above. chosen
Statements (40)
| Predicate | Object |
|---|---|
| instanceOf |
computer vision researcher
ⓘ
deep learning researcher ⓘ person ⓘ |
| countryOfCitizenship | China ⓘ |
| fieldOfWork |
computer vision
ⓘ
deep learning ⓘ machine learning ⓘ |
| hasAffiliation |
Chinese Academy of Sciences
ⓘ
MEGVII (Face++) ⓘ Microsoft Research Asia ⓘ |
| hasRole |
author of scientific papers
ⓘ
research scientist ⓘ |
| influencedBy | deep residual networks ⓘ |
| knownFor |
ResNeXt architecture
ⓘ
linked to:
ResNeXt
ShuffleNet architecture ⓘ
linked to:
ShuffleNetV2
convolutional neural network architectures ⓘ deep residual networks research ⓘ efficient CNN architectures ⓘ large-scale visual recognition ⓘ |
| language |
Chinese
ⓘ
English ⓘ |
| notableConcept |
aggregated residual transformations
ⓘ
channel shuffle operation ⓘ |
| notableWork |
Deep Residual Learning for Image Recognition (co-author)
ⓘ
linked to:
ResNet
ResNeXt: Aggregated Residual Transformations for Deep Neural Networks ⓘ
linked to:
ResNeXt
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices ⓘ |
| publicationVenue |
CVPR
ⓘ
ECCV ⓘ
linked to:
European Conference on Computer Vision
ICCV ⓘ ICLR ⓘ ICML ⓘ NeurIPS ⓘ |
| researchInterest |
convolutional neural networks
ⓘ
efficient neural networks ⓘ large-scale image recognition ⓘ mobile vision models ⓘ network architecture design ⓘ |
| worksOn |
image classification
ⓘ
object detection ⓘ visual recognition at scale ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Xiangyu Zhang Description of subject: Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.