3 papers
cs.LG2025
Forecasting Time Series with LLMs via Patch-Based Prompting and Decomposition
Mayank Bumb, Anshul Vemulapalli, Sri Harsha Vardhan Prasad Jella +7
Recent advances in Large Language Models (LLMs) have demonstrated new possibilities for accurate and efficient time series analysis, but prior work often required heavy fine-tuning…
cs.LG2025
Efficient Model Selection for Time Series Forecasting via LLMs
Wang Wei, Tiankai Yang, Hongjie Chen +4
Model selection is a critical step in time series forecasting, traditionally requiring extensive performance evaluations across various datasets. Meta-learning approaches aim to au…
cs.CV2024
Personalized Multimodal Large Language Models: A Survey
Junda Wu, Hanjia Lyu, Yu Xia +24
Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…