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Found 16 papers, 8 papers with code
Deep Sparse Latent Feature Models for Knowledge Graph Completion
Recent progress in knowledge graph completion (KGC) has focused on text-based approaches to address the challenges of large-scale knowledge graphs (KGs).
JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery from Large-Scale Human-LLM Conversational Datasets
To tackle these challenges, we introduce JailbreakHunter, a visual analytics approach for identifying jailbreak prompts in large-scale human-LLM conversational datasets.
IGFNet: Illumination-Guided Fusion Network for Semantic Scene Understanding using RGB-Thermal Images
However, current state-of-the-art methods simply use networks to fuse features on multi-modality inexplicably, rather than designing a fusion method based on the intrinsic characteristics of RGB images and thermal images.
Ranked #9 on
Thermal Image Segmentation
on MFN Dataset
Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI Collaboration
Data storytelling is powerful for communicating data insights, but it requires diverse skills and considerable effort from human creators.
KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation
Knowledge graph completion (KGC) revolves around populating missing triples in a knowledge graph using available information.
Ranked #1 on
Link Prediction
on WN18RR
Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling
Data storytelling plays an important role in data workers' daily jobs since it boosts team collaboration and public communication.
ImMesh: An Immediate LiDAR Localization and Meshing Framework
This voxel-wise meshing operation is delicately designed for the purpose of efficiency; it first performs a dimension reduction by projecting 3D points to a 2D local plane contained in the voxel, and then executes the meshing operation with pull, commit and push steps for incremental reconstruction of triangle facets.
Doubly-Iterative Sparsified MMSE Turbo Equalization for OTFS Modulation
Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios.
A microstructure estimation Transformer inspired by sparse representation for diffusion MRI
Thus, the METSC is composed with three stages, an embedding stage, a sparse representation stage, and a mapping stage.
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoning
Link prediction for knowledge graphs is the task aiming to complete missing facts by reasoning based on the existing knowledge.
An original model for multi-target learning of logical rules for knowledge graph reasoning
In this paper, we study the problem of learning logical rules for reasoning on knowledge graphs for completing missing factual triplets.
Can CAV Reduce Non-Recurrent Urban Road Congestion?
A well-designed resilient and sustainable urban transportation system can recover quickly from the non-recurrent road congestion (NRC), which is often caused by en-route events (e. g., road closure due to car collisions).
A Switched View of Retinex: Deep Self-Regularized Low-Light Image Enhancement
The generated reflectance, which is assumed to be irrelevant of illumination by Retinex, is treated as enhanced brightness.
Natural Graph Wavelet Packet Dictionaries
We introduce a set of novel multiscale basis transforms for signals on graphs that utilize their "dual" domains by incorporating the "natural" distances between graph Laplacian eigenvectors, rather than simply using the eigenvalue ordering.
Peer-inspired Student Performance Prediction in Interactive Online Question Pools with Graph Neural Network
Specifically, we model the relationship between students and questions using student interactions to construct the student-interaction-question network and further present a new GNN model, called R^2GCN, which intrinsically works for the heterogeneous networks, to achieve generalizable student performance prediction in interactive online question pools.
VommaNet: an End-to-End Network for Disparity Estimation from Reflective and Texture-less Light Field Images
The precise combination of image sensor and micro-lens array enables lenslet light field cameras to record both angular and spatial information of incoming light, therefore, one can calculate disparity and depth from light field images.
