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Found 18 papers, 5 papers with code
Accelerating Evolution: Integrating PSO Principles into Real-Coded Genetic Algorithm Crossover
This study introduces an innovative crossover operator named Particle Swarm Optimization-inspired Crossover (PSOX), which is specifically developed for real-coded genetic algorithms.
Interpretable Zero-shot Learning with Infinite Class Concepts
This paper redefines class semantics in ZSL with a focus on transferability and discriminability, introducing a novel framework called Zero-shot Learning with Infinite Class Concepts (InfZSL).
Is Temporal Prompting All We Need For Limited Labeled Action Recognition?
Recent advancements in visual-language models, especially based on contrastive pretraining, have shown remarkable generalization in zero-shot tasks, helping to overcome this dependence on labeled datasets.
Improved Feature Generating Framework for Transductive Zero-shot Learning
This paper delves into the pivotal influence of unseen class priors within the framework of transductive ZSL (TZSL) and illuminates the finding that even a marginal prior bias can result in substantial accuracy declines.
Template-Driven LLM-Paraphrased Framework for Tabular Math Word Problem Generation
In this paper, we propose a Template-driven LLM-paraphrased (TeLL) framework for generating high-quality TMWP samples with diverse backgrounds and accurate tables, questions, answers, and solutions.
Twin Trigger Generative Networks for Backdoor Attacks against Object Detection
Furthermore, the triggers for most existing backdoor attacks on object detection are manually generated, requiring prior knowledge and consistent patterns between the training and inference stages.
Target-driven Attack for Large Language Models
To solve this problem, we propose our target-driven black-box attack method to maximize the KL divergence between the conditional probabilities of the clean text and the attack text to redefine the attack's goal.
When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments
The StockAgent allows users to evaluate the impact of different external factors on investor trading and to analyze trading behavior and profitability effects.
Multi-task Prompt Words Learning for Social Media Content Generation
Furthermore, in the absence of effective and objective evaluation criteria in the field of content generation, we use the ChatGPT tool to evaluate the results generated by the algorithm, making large-scale evaluation of content generation algorithms possible.
Exploring Data Efficiency in Zero-Shot Learning with Diffusion Models
For class-level effectiveness, we design a two-branch generation structure that consists of a Diffusion-based Feature Generator (DFG) and a Diffusion-based Representation Generator (DRG).
Ranked #1 on
Zero-Shot Learning
on AwA2
Goal-guided Generative Prompt Injection Attack on Large Language Models
Although there is currently a large amount of research on prompt injection attacks, most of these black-box attacks use heuristic strategies.
Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities
Large language models (LLMs) have been applied in many fields and have developed rapidly in recent years.
Reimagining Reality: A Comprehensive Survey of Video Inpainting Techniques
This paper offers a comprehensive analysis of recent advancements in video inpainting techniques, a critical subset of computer vision and artificial intelligence.
Watt For What: Rethinking Deep Learning's Energy-Performance Relationship
Deep learning models have revolutionized various fields, from image recognition to natural language processing, by achieving unprecedented levels of accuracy.
Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning
Generalized zero-shot learning (GZSL) aims to recognize samples from both seen and unseen classes using only seen class samples for training.
A Simple and Effective Baseline for Attentional Generative Adversarial Networks
Synthesising a text-to-image model of high-quality images by guiding the generative model through the Text description is an innovative and challenging task.
Image Blending Algorithm with Automatic Mask Generation
In recent years, image blending has gained popularity for its ability to create visually stunning content.
Rebalanced Zero-shot Learning
Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes.
