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Found 7 papers, 0 papers with code
Debiasing Machine Unlearning with Counterfactual Examples
This bias emerges from two main sources: (1) data-level bias, characterized by uneven data removal, and (2) algorithm-level bias, which leads to the contamination of the remaining dataset, thereby degrading model accuracy.
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.
Chaining text-to-image and large language model: A novel approach for generating personalized e-commerce banners
Recent literature has surveyed the use of text-to-image models for enhancing the work of many creative artists.
Seller-side Outcome Fairness in Online Marketplaces
This paper aims to investigate and achieve seller-side fairness within online marketplaces, where many sellers and their items are not sufficiently exposed to customers in an e-commerce platform.
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.
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Considering the influence of historical purchases on users' future interests, the user and item representations can be viewed as unobserved confounders in the causal diagram.
