1 code implementation • 7 Mar 2024 • Aneta Koleva, Martin Ringsquandl, Ahmed Hatem, Thomas Runkler, Volker Tresp
Finally, we propose a prompting framework for evaluating the newly developed large language models (LLMs) on this novel TI task.
no code implementations • 31 Aug 2023 • Ahmed Hatem, Yiming Qian, Yang Wang
During meta-testing, the trained model is fine-tuned with a few gradient updates to produce a unique set of network parameters for each test instance.
no code implementations • ICCV 2023 • Ahmed Hatem, Yiming Qian, Yang Wang
This could be sub-optimal since it is difficult for the same model to handle all the variations during testing.