Timo Schick
Publications by Year
Research Areas
Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning, Text Readability and Simplification
Most-Cited Works
- → Toolformer: Language Models Can Teach Themselves to Use Tools(2023)370 cited
- → Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP(2021)206 cited
- → Atlas: Few-shot Learning with Retrieval Augmented Language Models(2022)196 cited
- → Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification(2020)154 cited
- → Augmented Language Models: a Survey(2023)140 cited
- → Few-Shot Text Generation with Natural Language Instructions(2021)100 cited
- → Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor(2023)87 cited
- → It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners(2021)75 cited
- → Few-Shot Text Generation with Pattern-Exploiting Training(2020)74 cited
- → Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference(2021)74 cited