Unlearnable Algorithms for In-context Learning
Authors: Andrei Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot | Published: 2024-02-01
Few-Shot Learning
Towards LLM-based Fact Verification on News Claims with a Hierarchical Step-by-Step Prompting Method
Authors: Xuan Zhang, Wei Gao | Published: 2023-09-30
Few-shot Weakly-supervised Cybersecurity Anomaly Detection
Authors: Rahul Kale, Vrizlynn L. L. Thing | Published: 2023-04-15
On the Efficacy of Differentially Private Few-shot Image Classification
Authors: Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Beguelin, Richard E Turner, Antti Honkela | Published: 2023-02-02 | Updated: 2023-12-19
Alignment with human representations supports robust few-shot learning
Authors: Ilia Sucholutsky, Thomas L. Griffiths | Published: 2023-01-27 | Updated: 2023-10-29
Few-shot Instruction Prompts for Pretrained Language Models to Detect Social Biases
Authors: Shrimai Prabhumoye, Rafal Kocielnik, Mohammad Shoeybi, Anima Anandkumar, Bryan Catanzaro | Published: 2021-12-15 | Updated: 2022-04-15
Towards Few-Shot Fact-Checking via Perplexity
Authors: Nayeon Lee, Yejin Bang, Andrea Madotto, Madian Khabsa, Pascale Fung | Published: 2021-03-17
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations
Authors: Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu | Published: 2020-09-29 | Updated: 2022-08-17
Distilled One-Shot Federated Learning
Authors: Yanlin Zhou, George Pu, Xiyao Ma, Xiaolin Li, Dapeng Wu | Published: 2020-09-17 | Updated: 2021-06-06
Simultaneous Perturbation Stochastic Approximation for Few-Shot Learning
Authors: Andrei Boiarov, Oleg Granichin, Olga Granichina | Published: 2020-06-09