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Found 4 papers, 0 papers with code
RecMind: Large Language Model Powered Agent For Recommendation
While the recommendation system (RS) has advanced significantly through deep learning, current RS approaches usually train and fine-tune models on task-specific datasets, limiting their generalizability to new recommendation tasks and their ability to leverage external knowledge due to model scale and data size constraints.
Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting
The application of machine learning models to financial time series comes with several challenges, including the difficulty in cross-sequence reasoning and inference, the hurdle of incorporating multi-modal signals from historical news, financial knowledge graphs, etc., and the issue of interpreting and explaining the model results.
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding
This paper presents our "Collaborative Query Rewriting" approach, which specifically addresses the task of rewriting new user interactions that have not been previously observed in the user's history.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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PALR: Personalization Aware LLMs for Recommendation
Then we adopt a LLM-based ranking model to generate recommended items.
