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Found 9 papers, 6 papers with code
Can 3D Vision-Language Models Truly Understand Natural Language?
To test the language understandability of 3D-VL models, we first propose a language robustness task for systematically assessing 3D-VL models across various tasks, benchmarking their performance when presented with different language style variants.
Weiss-Weinstein bound of frequency estimation error for very weak GNSS signals
Tightness remains the center quest in all modern estimation bounds.
Compositional Generalization for Multi-label Text Classification: A Data-Augmentation Approach
Our experiments show that this data augmentation approach significantly improves the compositional generalization capabilities of classification models on our benchmarks, with both generation models surpassing other text generation baselines.
Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes
There is growing concern that the potential of black box AI may exacerbate health-related disparities and biases such as gender and ethnicity in clinical decision-making.
MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds
Unlike the single-scan-based semantic segmentation task, this task requires distinguishing the motion states of points in addition to their semantic categories.
GO-LDA: Generalised Optimal Linear Discriminant Analysis
Linear discriminant analysis (LDA) has been a useful tool in pattern recognition and data analysis research and practice.
Large-Scale Traffic Congestion Prediction based on Multimodal Fusion and Representation Mapping
With the progress of the urbanisation process, the urban transportation system is extremely critical to the development of cities and the quality of life of the citizens.
Weakly Supervised Real-time Image Cropping based on Aesthetic Distributions
In order to tackle this problem, a weakly supervised cropping frame- work is proposed, where the distribution dissimilarity between high quality images and cropped images is used to guide the coordinate predictor’s training and the ground truths of cropping windows are not required by the proposed method.
Mining Functional Modules by Multiview-NMF of Phenome-Genome Association
In particular, the hierarchical structure of ontology has not been sufficiently utilized in clustering genes while functionally related genes are consistently associated with phenotypes on the same path in the phenotype ontology.
