papers
Publications (2)
cs.CL2024
Context-aware Prompt Tuning: Advancing In-Context Learning with Adversarial Methods
Tsachi Blau, Moshe Kimhi, Yonatan Belinkov +2
Fine-tuning Large Language Models (LLMs) typically involves updating at least a few billions of parameters. A more parameter-efficient approach is Prompt Tuning (PT), which updates…
cs.CV2020
StarNet: towards Weakly Supervised Few-Shot Object Detection
Leonid Karlinsky, Joseph Shtok, Amit Alfassy +8
Few-shot detection and classification have advanced significantly in recent years. Yet, detection approaches require strong annotation (bounding boxes) both for pre-training and fo…