3 accepted papers
Recent advancements in large language models (LLMs) have demonstrated their impressive generative capabilities, primarily due to their extensive parameterization, which enables them to encode vast knowledge. However, effectively integrating new knowledge into LLMs remains a major challenge. Current…
Topic modeling aims to discover the distribution of topics within a corpus. The advanced comprehension and generative capabilities of large language models (LLMs) have introduced new avenues for topic modeling, particularly by prompting LLMs to generate topics and refine them by merging similar ones…
Knowledge graph reasoning (KGR) aims to infer new factual triples from existing knowledge graphs (KGs). Recently, a new category of methods, possessing both transductive and inductive reasoning capabilities, has been proposed to tackle this task via learning entity-independent representations from l…