Large language models (LLMs) have not only revolutionized the field of natural language
processing (NLP) but also have the potential to bring a paradigm shift in many other fields …

Prompting is a mainstream paradigm for adapting large language models to specific natural
language processing tasks without modifying internal parameters. Therefore, detailed …

Anomaly detection (AD) is an important machine learning task with many real-world uses,
including fraud detection, medical diagnosis, and industrial monitoring. Within natural …

Large language models (LLMs) have demonstrated prominent reasoning capabilities in
recommendation tasks by transforming them into text-generation tasks. However, existing …

In this paper, we present a systematic effort to design, evaluate, and implement a realistic
conversational recommender system (CRS). The objective of our system is to allow users to …

Recent advances in Large Language Models (LLMs) have demonstrated promising
performance in sequential recommendation tasks, leveraging their superior language …

Large language models (LLMs) are utilized in various studies, and they also demonstrate a
potential to function independently as a recommendation model. Nevertheless, training …

The bottleneck associated with the key-value (KV) cache presents a significant challenge
during the inference processes of large language models. While depth pruning accelerates …

Large language models (LLMs) for recommendation, aka LLM4Rec, has attracted
increasing attention due to their advanced knowledge and powerful reasoning ability …