Prompting large language models for recommender systems: A comprehensive framework and empirical analysis

L Xu, J Zhang, B Li, J Wang, M Cai, WX Zhao… - arxiv preprint arxiv …, 2024 - arxiv.org
Recently, large language models such as ChatGPT have showcased remarkable abilities in
solving general tasks, demonstrating the potential for applications in recommender systems …

Agentohana: Design unified data and training pipeline for effective agent learning

J Zhang, T Lan, R Murthy, Z Liu, W Yao, M Zhu… - arxiv preprint arxiv …, 2024 - arxiv.org
Autonomous agents powered by large language models (LLMs) have garnered significant
research attention. However, fully harnessing the potential of LLMs for agent-based tasks …

Towards next-generation llm-based recommender systems: A survey and beyond

Q Wang, J Li, S Wang, Q **ng, R Niu, H Kong… - arxiv preprint arxiv …, 2024 - arxiv.org
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 …

A survey of generative search and recommendation in the era of large language models

Y Li, X Lin, W Wang, F Feng, L Pang, W Li, L Nie… - arxiv preprint arxiv …, 2024 - arxiv.org
With the information explosion on the Web, search and recommendation are foundational
infrastructures to satisfying users' information needs. As the two sides of the same coin, both …

When search engine services meet large language models: visions and challenges

H **ong, J Bian, Y Li, X Li, M Du… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Combining Large Language Models (LLMs) with search engine services marks a significant
shift in the field of services computing, opening up new possibilities to enhance how we …

Agentlite: A lightweight library for building and advancing task-oriented llm agent system

Z Liu, W Yao, J Zhang, L Yang, Z Liu, J Tan… - arxiv preprint arxiv …, 2024 - arxiv.org
The booming success of LLMs initiates rapid development in LLM agents. Though the
foundation of an LLM agent is the generative model, it is critical to devise the optimal …

Coral: Collaborative retrieval-augmented large language models improve long-tail recommendation

J Wu, CC Chang, T Yu, Z He, J Wang, Y Hou… - Proceedings of the 30th …, 2024 - dl.acm.org
The long-tail recommendation is a challenging task for traditional recommender systems,
due to data sparsity and data imbalance issues. The recent development of large language …

Conditional denoising diffusion for sequential recommendation

Y Wang, Z Liu, L Yang, PS Yu - … on Knowledge Discovery and Data Mining, 2024 - Springer
Contemporary attention-based sequential recommendations often encounter the
oversmoothing problem, which generates indistinguishable representations. Although …