ICLR "meta-learning" Papers
6 papers found
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
Minyoung Kim, Timothy Hospedales
ICLR 2025poster
1
citations
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.
ICLR 2025posterarXiv:2410.05454
MetaOOD: Automatic Selection of OOD Detection Models
Yuehan Qin, Yichi Zhang, Yi Nian et al.
ICLR 2025posterarXiv:2410.03074
16
citations
PersonalLLM: Tailoring LLMs to Individual Preferences
Thomas Zollo, Andrew Siah, Naimeng Ye et al.
ICLR 2025posterarXiv:2409.20296
27
citations
PIED: Physics-Informed Experimental Design for Inverse Problems
Apivich Hemachandra, Gregory Kang Ruey Lau, See-Kiong Ng et al.
ICLR 2025posterarXiv:2503.07070
1
citations
Why In-Context Learning Models are Good Few-Shot Learners?
Shiguang Wu, Yaqing Wang, Quanming Yao
ICLR 2025poster