Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …

The recent surge in Large Language Models (LLMs) has garnered significant attention
across numerous fields. Fine-tuning is often required to fit general LLMs for a specific …

Solving geospatial tasks generally requires multiple geospatial tools and steps, ie, tool-use
chains. Automating the geospatial task solving process can effectively enhance the …

Knowledge editing has been increasingly adopted to correct the false or outdated
knowledge in Large Language Models (LLMs). Meanwhile, one critical but under-explored …

The knowledge within large language models (LLMs) may become outdated quickly. While
in-context editing (ICE) is currently the most effective method for knowledge editing (KE), it is …

Query expansion, pivotal in search engines, enhances the representation of user
information needs with additional terms. While existing methods expand queries using …

Large Language Models (LLMs) suffer from hallucinations, referring to the non-factual
information in generated content, despite their superior capacities across tasks. Meanwhile …

The impressive capabilities of large language models (LLMs) have attracted extensive
interests of applying LLMs to medical field. However, the complex nature of clinical …

Abstract Recently, few-shot Named Entity Recognition (NER) has attracted significant
attention due to the high cost of obtaining high-quality labeled data. Decomposition-based …

The lack of training data gives rise to the system cold-start problem in recommendation
systems, making them struggle to provide effective recommendations. To address this …