Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the
sequence-to-sequence framework for building knowledge graphs, which is flexible and can …

Large language models (LLMs) have demonstrated great success in various fields,
benefiting from their huge amount of parameters that store knowledge. However, LLMs still …

In-context learning (ICL), teaching a large language model (LLM) to perform a task with few-
shot demonstrations rather than adjusting the model parameters, has emerged as a strong …

Existing video-audio understanding models are trained and evaluated in an intra-domain
setting, facing performance degeneration in real-world applications where multiple domains …

Conversational Recommender Systems (CRSs) leverage natural language dialogues to
provide tailored recommendations. Traditional methods in this field primarily focus on …

Large Language Models (LLMs) have shown extraordinary capabilities in understanding
and generating text that closely mirrors human communication. However, a primary …

Reasoning over knowledge graphs (KGs) is a challenging task that requires a deep
understanding of the complex relationships between entities and the underlying logic of their …

Smart contracts are software programs that enable diverse business activities on the
blockchain. Recent research has identified new classes of “machine un-auditable” bugs that …

The rise of code pre-trained models has significantly enhanced various coding tasks, such
as code completion, and tools like GitHub Copilot. However, the substantial size of these …

Recent advances in fine-tuning large language models (LLMs) have greatly enhanced their
usage in domain-specific tasks. Despite the success, fine-tuning continues to rely on …