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08/31/2023
3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation
In 3D Referring Expression Segmentation (3D-RES), the earlier approach a...
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08/22/2023
M3PS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization in E-commerce
Given the long textual product information and the product image, Multi-...
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08/06/2023
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation
In recent years, 3D representation learning has turned to 2D vision-lang...
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03/28/2023
X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidance
Text-driven 3D stylization is a complex and crucial task in the fields o...
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02/13/2023
Towards Local Visual Modeling for Image Captioning
In this paper, we study the local visual modeling with grid features for...
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01/09/2023
Towards Real-Time Panoptic Narrative Grounding by an End-to-End Grounding Network
Panoptic Narrative Grounding (PNG) is an emerging cross-modal grounding ...
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02/16/2022
A flexible approach for causal inference with multiple treatments and clustered survival outcomes
When drawing causal inferences about the effects of multiple treatments ...
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10/19/2021
CIMTx: An R package for causal inference with multiple treatments using observational data
CIMTx provides efficient and unified functions to implement modern metho...
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09/27/2021
Joint marginal structural models to estimate the causal effects of multiple longitudinal treatments in continuous time with application to COVID-19
To draw real-world evidence about the comparative effectiveness of compl...
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04/06/2021
Variable selection with missing data in both covariates and outcomes: Imputation and machine learning
The missing data issue is ubiquitous in health studies. Variable selecti...
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01/16/2021
Dual-Level Collaborative Transformer for Image Captioning
Descriptive region features extracted by object detection networks have ...
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12/13/2020
Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network
Transformer-based architectures have shown great success in image captio...
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12/11/2020
A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome
In the absence of a randomized experiment, a key assumption for drawing ...
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08/17/2020
Estimating Heterogeneous Survival Treatment Effect via Machine/Deep Learning Methods in Observational Studies
The rise of personalized medicine necessitates improved causal inference...
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01/17/2020
Estimation of Causal Effects of Multiple Treatments in Observational Studies with a Binary Outcome
There is a dearth of robust methods to estimate the causal effects of mu...
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10/09/2019