Xin Wang

Affiliations:
  • Microsoft Research, Redmond, WA, USA
  • University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, Berkeley, CA, USA (PhD 2020)


According to our database1, Xin Wang authored at least 37 papers between 2017 and 2024.

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Bibliography

2024
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
CoRR, 2024

When Do We Not Need Larger Vision Models?
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Textbooks Are All You Need.
CoRR, 2023

Controllable Text-to-Image Generation with GPT-4.
CoRR, 2023

Refocusing Is Key to Transfer Learning.
CoRR, 2023

Gorilla: Large Language Model Connected with Massive APIs.
CoRR, 2023

Scaling Novel Object Detection with Weakly Supervised Detection Transformers.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Understanding Zero-shot Adversarial Robustness for Large-Scale Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Top-Down Visual Attention from Analysis by Synthesis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Doubly Right Object Recognition: A Why Prompt for Visual Rationales.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Visual Attention Emerges from Recurrent Sparse Reconstruction.
Proceedings of the International Conference on Machine Learning, 2022

Context-Aware Streaming Perception in Dynamic Environments.
Proceedings of the Computer Vision - ECCV 2022, 2022

Neural-Sim: Learning to Generate Training Data with NeRF.
Proceedings of the Computer Vision - ECCV 2022, 2022

Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Robust Contrastive Learning against Noisy Views.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

DETReg: Unsupervised Pretraining with Region Priors for Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty.
Proceedings of the Conference on Robot Learning, 2022

2021
Instance-Aware Predictive Navigation in Multi-Agent Environments.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Wanderlust: Online Continual Object Detection in the Real World.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Robust Object Detection via Instance-Level Temporal Cycle Confusion.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
The Design of Dynamic Neural Networks for Efficient Learning and Inference
PhD thesis, 2020

Frustratingly Simple Few-Shot Object Detection.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning Saliency Propagation for Semi-Supervised Instance Segmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Domain-Aware Dynamic Networks.
CoRR, 2019

Task-Aware Deep Sampling for Feature Generation.
CoRR, 2019

Deep Mixture of Experts via Shallow Embedding.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

ACE: Adapting to Changing Environments for Semantic Segmentation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Few-Shot Object Detection via Feature Reweighting.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Accel: A Corrective Fusion Network for Efficient Semantic Segmentation on Video.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Deep Mixture of Experts via Shallow Embedding.
CoRR, 2018

IDK Cascades: Fast Deep Learning by Learning not to Overthink.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

SkipNet: Learning Dynamic Routing in Convolutional Networks.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
SkipNet: Learning Dynamic Routing in Convolutional Networks.
CoRR, 2017

IDK Cascades: Fast Deep Learning by Learning not to Overthink.
CoRR, 2017

Clipper: A Low-Latency Online Prediction Serving System.
Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, 2017


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