Summary of Metallm: a High-performant and Cost-efficient Dynamic Framework For Wrapping Llms, by Quang H. Nguyen et al.
MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMsby Quang H. Nguyen, Duy C.…
MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMsby Quang H. Nguyen, Duy C.…
Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equationsby Wei Zhou, Y.F.…
Learning to Unlearn for Robust Machine Unlearningby Mark He Huang, Lin Geng Foo, Jun LiuFirst…
Evaluating Model Bias Requires Characterizing its Mistakesby Isabela Albuquerque, Jessica Schrouff, David Warde-Farley, Taylan Cemgil,…
Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learningby Ziyan Wang, Yaxuan…
Physics-Informed Machine Learning for Smart Additive Manufacturingby Rahul Sharma, Maziar Raissi, Y.B. GuoFirst submitted to…
psifx – Psychological and Social Interactions Feature Extraction Packageby Guillaume Rochette, Matthew J. Vowels, Mathieu…
An Interpretable Neural Network for Vegetation Phenotyping with Visualization of Trait-Based Spectral Featuresby William Basener,…
Proper losses regret at least 1/2-orderby Han Bao, Asuka TakatsuFirst submitted to arxiv on: 15…
Deflated Dynamics Value Iterationby Jongmin Lee, Amin Rakhsha, Ernest K. Ryu, Amir-massoud FarahmandFirst submitted to…