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Found 12 papers, 4 papers with code
MLVU: A Comprehensive Benchmark for Multi-Task Long Video Understanding
To address the above problems, we propose a new benchmark, called MLVU (Multi-task Long Video Understanding Benchmark), for the comprehensive and in-depth evaluation of LVU.
VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval
Thirdly, we introduce a multi-stage training algorithm, which first aligns the visual token embedding with the text encoder using massive weakly labeled data, and then develops multi-modal representation capability using the generated composed image-text data.
Tumor Micro-environment Interactions Guided Graph Learning for Survival Analysis of Human Cancers from Whole-slide Pathological Images
However most of the prevalent methods only worked on the sampled patches in specifically or randomly selected tumor areas of WSIs which has very limited capability to capture the complex interactions between tumor and its surrounding micro-environment components.
TextDiff: Mask-Guided Residual Diffusion Models for Scene Text Image Super-Resolution
Moreover, our proposed MRD module is plug-and-play that effectively sharpens the text edges produced by SOTA methods.
DocDiff: Document Enhancement via Residual Diffusion Models
Removing degradation from document images not only improves their visual quality and readability, but also enhances the performance of numerous automated document analysis and recognition tasks.
Effort Discrimination and Curvature of Contest Technology in Conflict Networks
When the contest technology in each battle is of Tullock form, a surprising neutrality result holds within the class of semi-symmetric conflict network structures: both the aggregate actions and equilibrium payoffs under two regimes are the same.
SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation
In this paper, we propose the Size-Aware Transformer (SAT) that can tailor effective receptive fields for objects of different sizes.
Ranked #11 on
Semantic Segmentation
on S3DIS Area5
Welfare and Distributional Effects of Joint Intervention in Networks
We show that the welfare effect of joint intervention is shaped by the principal eigenvalue, while the distributional effect is captured by the dispersion of the corresponding eigenvalues, i. e., the eigen-centralities.
Unsignalized Intersection Management Strategy for Mixed Autonomy Traffic Streams
In the HPQ algorithm, a vehicle priority management model considering the difference between CAVs, CHVs, and HVs, is built to design the right of way management for different types of vehicles.
Research on the Inverse Kinematics Prediction of a Soft Biomimetic Actuator via BP Neural Network
After training with sample data, the BP neural network model can represent the relation between the manipulator tip position and the pressure applied to the chambers.
Multi-activity Influence and Intervention
Using a general network model with multiple activities, we analyse a planner's welfare maximising interventions taking into account within-activity network spillovers and cross-activity interdependence.
Structural Interventions in Networks
Two types of interventions are commonly implemented in networks: characteristic intervention, which influences individuals' intrinsic incentives, and structural intervention, which targets the social links among individuals.
