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Prompting large language models for recommender systems: A comprehensive framework and empirical analysis
Recently, large language models such as ChatGPT have showcased remarkable abilities in
solving general tasks, demonstrating the potential for applications in recommender systems …
solving general tasks, demonstrating the potential for applications in recommender systems …
Agentohana: Design unified data and training pipeline for effective agent learning
Autonomous agents powered by large language models (LLMs) have garnered significant
research attention. However, fully harnessing the potential of LLMs for agent-based tasks …
research attention. However, fully harnessing the potential of LLMs for agent-based tasks …
Towards next-generation llm-based recommender systems: A survey and beyond
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 …
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
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 …
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
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 …
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
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 …
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
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 …
due to data sparsity and data imbalance issues. The recent development of large language …
Conditional denoising diffusion for sequential recommendation
Contemporary attention-based sequential recommendations often encounter the
oversmoothing problem, which generates indistinguishable representations. Although …
oversmoothing problem, which generates indistinguishable representations. Although …