Search Results for author:
Found 7 papers, 3 papers with code
UECA-Prompt: Universal Prompt for Emotion Cause Analysis
To address the first two problems, this paper proposes a universal prompt tuning method to solve different ECA tasks in the unified framework.
Ranked #1 on
Emotion-Cause Pair Extraction
on ECPE
Enhancing Hyperspectral Images via Diffusion Model and Group-Autoencoder Super-resolution Network
Existing hyperspectral image (HSI) super-resolution (SR) methods struggle to effectively capture the complex spectral-spatial relationships and low-level details, while diffusion models represent a promising generative model known for their exceptional performance in modeling complex relations and learning high and low-level visual features.
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality Assessment
Firstly, we devise a new diffusion restoration network that leverages the produced enhanced image and noise-containing images, incorporating nonlinear features obtained during the denoising process of the diffusion model, as high-level visual information.
Momentum Gradient-based Untargeted Attack on Hypergraph Neural Networks
We use a momentum gradient mechanism to choose the attack node features in the feature selection module.
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
In this paper, we propose a tailored learning approach to distill such reasoning ability to smaller LMs to facilitate the democratization of the exclusive reasoning ability.
Coherent ray-wave structured light based on (helical) Ince-Gaussian modes
The topological evolution of classic eigenmodes including Hermite-Laguerre-Gaussian and (helical) InceGaussian modes is exploited to construct coherent state modes, which unifies the representations of travelingwave (TW) and standing-wave (SW) ray-wave structured light for the first time and realizes the TW-SW unified ray-wave geometric beam with topology of raytrajectories splitting effect, breaking the boundary of TW and SW structured light.
Optics
Sparse and Low-Rank High-Order Tensor Regression via Parallel Proximal Method
Recently, tensor data (or multidimensional array) have been generated in many modern applications, such as functional magnetic resonance imaging (fMRI) in neuroscience and videos in video analysis.
