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Found 13 papers, 7 papers with code
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets
This paper proposes GDPNet, the first hybrid Generative and Discriminative PointNet that extends JEM for point cloud classification and generation.
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
In this work, we propose a simple yet effective training strategy MoE-Tuning for LVLMs.
Ranked #54 on
Visual Question Answering
on MM-Vet
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
In this work, we unify visual representation into the language feature space to advance the foundational LLM towards a unified LVLM.
Ranked #2 on
Zero-Shot Video Question Answer
on TGIF-QA
Urban Drone Navigation: Autoencoder Learning Fusion for Aerodynamics
Drones are vital for urban emergency search and rescue (SAR) due to the challenges of navigating dynamic environments with obstacles like buildings and wind.
W-procer: Weighted Prototypical Contrastive Learning for Medical Few-Shot Named Entity Recognition
Contrastive learning has become a popular solution for few-shot Name Entity Recognization (NER).
Improved Trust in Human-Robot Collaboration with ChatGPT
A human-subject experiment showed that incorporating ChatGPT in robots significantly increased trust in human-robot collaboration, which can be attributed to the robot's ability to communicate more effectively with humans.
Robot-Enabled Construction Assembly with Automated Sequence Planning based on ChatGPT: RoboGPT
To expand the ability of the current robot system in sequential understanding, this paper introduces RoboGPT, a novel system that leverages the advanced reasoning capabilities of ChatGPT, a large language model, for automated sequence planning in robot-based assembly applied to construction tasks.
APSNet: Attention Based Point Cloud Sampling
Traditional task-agnostic sampling methods, such as farthest point sampling (FPS), do not consider downstream tasks when sampling point clouds, and thus non-informative points to the tasks are often sampled.
A Hierarchical N-Gram Framework for Zero-Shot Link Prediction
Thus, in this paper, we propose a Hierarchical N-Gram framework for Zero-Shot Link Prediction (HNZSLP), which considers the dependencies among character n-grams of the relation surface name for ZSLP.
Impacts of export restrictions on the global personal protective equipment trade network during COVID-19
The threshold model captures the shortage contagion on the global PPE trade network.
Physics and Society
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More
We show that our Generative MMC (GMMC) can be trained discriminatively, generatively, or jointly for image classification and generation.
Adversarial Privacy Preserving Graph Embedding against Inference Attack
In this paper, we propose Adversarial Privacy Graph Embedding (APGE), a graph adversarial training framework that integrates the disentangling and purging mechanisms to remove users' private information from learned node representations.
Sparse Graph Attention Networks
Among the variants of GNNs, Graph Attention Networks (GATs) learn to assign dense attention coefficients over all neighbors of a node for feature aggregation, and improve the performance of many graph learning tasks.
