The year 2023 marked a significant surge in the exploration of applying large language
model chatbots, notably Chat Generative Pre‐trained Transformer (ChatGPT), across …

Retrieval-Augmented Generation (RAG) is a technique that enhances the capabilities of
large language models (LLMs) by incorporating external knowledge sources. This method …

The rise of Multimodal Large Language Models (MLLMs) has become a transformative force
in the field of artificial intelligence, enabling machines to process and generate content …

Model editing aims to precisely alter the behaviors of large language models (LLMs) in
relation to specific knowledge, while leaving unrelated knowledge intact. This approach has …

In this paper, we propose a novel method for joint entity and relation extraction from
unstructured text by framing it as a conditional sequence generation problem. In contrast to …

There has been increasing interest in exploring the capabilities of advanced large language
models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related …

As the demand for more personalized recommendation grows and a dramatic boom in
commercial scenarios arises, the study on multi-scenario recommendation (MSR) has …

While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …

In the realm of e-commerce search, the significance of semantic matching cannot be
overstated, as it directly impacts both user experience and company revenue. Along this …

Automatic taxonomy induction is crucial for web search, recommendation systems, and
question answering. Manual curation of taxonomies is expensive in terms of human effort …