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Found 9 papers, 0 papers with code
Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understanding
The dataset is created with GPT-4 to extend the abstract concept to a scene and concrete objects.
LLM-Ensemble: Optimal Large Language Model Ensemble Method for E-commerce Product Attribute Value Extraction
Product attribute value extraction is a pivotal component in Natural Language Processing (NLP) and the contemporary e-commerce industry.
Character-based Outfit Generation with Vision-augmented Style Extraction via LLMs
The outfit generation problem involves recommending a complete outfit to a user based on their interests.
LLMs with User-defined Prompts as Generic Data Operators for Reliable Data Processing
Although the UDF design pattern introduces flexibility, reusability and scalability, the increasing demand on machine learning pipelines brings three new challenges to this design pattern -- not low-code, not dependency-free and not knowledge-aware.
LLM-TAKE: Theme Aware Keyword Extraction Using Large Language Models
We call our LLM-based framework Theme-Aware Keyword Extraction (LLM TAKE).
GNN-GMVO: Graph Neural Networks for Optimizing Gross Merchandise Value in Similar Item Recommendation
Similar item recommendation is a critical task in the e-Commerce industry, which helps customers explore similar and relevant alternatives based on their interested products.
Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs
Knowledge Graphs (KGs) play a crucial role in enhancing e-commerce system performance by providing structured information about entities and their relationships, such as complementary or substitutable relations between products or product types, which can be utilized in recommender systems.
NEAT: A Label Noise-resistant Complementary Item Recommender System with Trustworthy Evaluation
On the other hand, the model evaluation will not be trustworthy if the labels for evaluation are not reflecting the true complementary relatedness.
GAN-based Recommendation with Positive-Unlabeled Sampling
Recommender systems are popular tools for information retrieval tasks on a large variety of web applications and personalized products.
