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Found 6 papers, 1 papers with code
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.
On the special role of class-selective neurons in early training
Finally, in causal experiments where we regularize against class selectivity at different points in training, we show that the presence of class-selective neurons early in training is critical to the successful training of the network; in contrast, class-selective neurons can be suppressed later in training with little effect on final accuracy.
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.
Error Diagnosis of Deep Monocular Depth Estimation Models
To address errors in depth estimation, we introduce a novel Depth Error Detection Network (DEDN) that spatially identifies erroneous depth predictions in the monocular depth estimation models.
Vision: A Deep Learning Approach to provide walking assistance to the visually impaired
Blind people face a lot of problems in their daily routines.
