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Found 9 papers, 7 papers with code
Are Large Language Models a Good Replacement of Taxonomies?
Unfortunately, there lacks a comprehensive benchmark that evaluates the LLMs over a wide range of taxonomies from common to specialized domains and at levels from root to leaf so that we can draw a confident conclusion.
CRAG -- Comprehensive RAG Benchmark
To bridge this gap, we introduce the Comprehensive RAG Benchmark (CRAG), a factual question answering benchmark of 4, 409 question-answer pairs and mock APIs to simulate web and Knowledge Graph (KG) search.
KGLink: A column type annotation method that combines knowledge graph and pre-trained language model
By leveraging the strengths of KGLink, we successfully surmount challenges related to type granularity and valuable context issues, establishing it as a robust solution for the semantic annotation of tabular data.
Multi-level Multiple Instance Learning with Transformer for Whole Slide Image Classification
Whole slide image (WSI) refers to a type of high-resolution scanned tissue image, which is extensively employed in computer-assisted diagnosis (CAD).
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation
Thus a novel weight-based method is proposed to end-to-end estimate the importance of attention heads, while the self-attention maps are adaptively fused for high-quality CAM results that tend to have more complete objects.
Attacking and Defending Machine Learning Applications of Public Cloud
Adversarial attack breaks the boundaries of traditional security defense.
Advbox: a toolbox to generate adversarial examples that fool neural networks
In recent years, neural networks have been extensively deployed for computer vision tasks, particularly visual classification problems, where new algorithms reported to achieve or even surpass the human performance.
Joint Embeddings of Chinese Words, Characters, and Fine-grained Subcharacter Components
Word embeddings have attracted much attention recently.
Subjective Knowledge Acquisition and Enrichment Powered By Crowdsourcing
In our work, we propose a system, called crowdsourced subjective knowledge acquisition (CoSKA), for subjective knowledge acquisition powered by crowdsourcing and existing KBs.
