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Found 4 papers, 1 papers with code
RotateCT: Knowledge Graph Embedding by Rotation and Coordinate Transformation in Complex Space
Knowledge graph embedding, which aims to learn representations of entities and relations in knowledge graphs, finds applications in various downstream tasks.
SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention
Our SCSA consists of two parts: the Shareable Multi-Semantic Spatial Attention (SMSA) and the Progressive Channel-wise Self-Attention (PCSA).
YAYI 2: Multilingual Open-Source Large Language Models
As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artificial general intelligence.
Rational Sensibility: LLM Enhanced Empathetic Response Generation Guided by Self-presentation Theory
However, the rationality information within the conversation is restricted, and previous methods of extending knowledge are subject to semantic conflict and single-role view.
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