Large language models (LLMs) have demonstrated remarkable generalizability, such as
understanding arbitrary entities and relations. Instruction tuning has proven effective for …

Information extraction (IE) aims to extract structural knowledge (such as entities, relations,
and events) from plain natural language texts. Recently, generative Large Language Models …

Large language models (LLMs) have demonstrated promising in-context learning
capabilities, especially with instructive prompts. However, recent studies have shown that …

Large Language Models (LLMs) demonstrate remarkable potential across various domains;
however, they exhibit a significant performance gap in Information Extraction (IE). Note that …

Large Language Models (LLMs) have demonstrated impressive capabilities for generalizing
in unseen tasks. In the Named Entity Recognition (NER) task, recent advancements have …

As the significance of data continues to grows, so does the importance of data analysis
methods. Various models are currently being applied, and new models are being proposed …

Re-identification (ReID) is a critical field in com-puter vision. In previous studies, ReID
models have primarily focused on identifying specific objects, such as persons or vehi-cles …

In many instances, traffic supervisors, drivers, or autonomous driving systems need to
search for and pinpoint specific traffic targets. Relying on human visual location is …