The development of emotion recognition in dialogue (ERC) has been consistently hindered
by the complexity of pipeline designs, leading to ERC models that often overfit to specific …

The objective of few-shot named entity recognition is to identify named entities with limited
labeled instances. Previous works have primarily focused on optimizing the traditional token …

Knowledge Base Question Answering (KBQA) aims to answer natural language questions
with factual information such as entities and relations in KBs. However, traditional Pre …

With the increasing capabilities of large language models (LLMs), these high-performance
models have achieved state-of-the-art results on a wide range of natural language …

Emotion Recognition in Conversation (ERC) has attracted widespread attention in the
natural language processing field due to its enormous potential for practical applications …

E-commerce platforms rely heavily on the attribute values of their products as they play a
crucial role in various retail functions such as product search, recommendations, and …

In e-commerce, accurately extracting product attribute values from multimodal data is crucial
for improving user experience and operational efficiency of retailers. However, previous …

E-commerce platforms should provide detailed product descriptions (attribute values) for
effective product search and recommendation. However, attribute value information is …

Existing datasets for attribute value extraction (AVE) predominantly focus on explicit attribute
values while neglecting the implicit ones, lack product images, are often not publicly …

Abstract Information extraction aims to automatically extract structured information from
unstructured texts. Supervised information extraction requires large quantities of labeled …