Timo Schick

According to our database, Timo Schick authored at least 33 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Improving Wikipedia verifiability with AI.

Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel

Nat. Mac. Intell., October, 2023

Atlas: Few-shot Learning with Retrieval Augmented Language Models.

Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave

J. Mach. Learn. Res., 2023

Evaluation of Faithfulness Using the Longest Supported Subsequence.

Anirudh Mittal, Timo Schick, Mikel Artetxe, Jane Dwivedi-Yu

CoRR, 2023

Self-Alignment with Instruction Backtranslation.

Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, Mike Lewis

CoRR, 2023

LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction.

Abdullatif Köksal, Timo Schick, Anna Korhonen, Hinrich Schütze

CoRR, 2023

Augmented Language Models: a Survey.

Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom

CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.

Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom

CoRR, 2023

Semantic-Oriented Unlabeled Priming for Large-Scale Language Models.

Yanchen Liu, Timo Schick, Hinrich Schütze

Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.

Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PEER: A Collaborative Language Model.

Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick S. H. Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Active Learning Principles for In-Context Learning with Large Language Models.

Katerina Margatina, Timo Schick, Nikolaos Aletras, Jane Dwivedi-Yu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

MEAL: Stable and Active Learning for Few-Shot Prompting.

Abdullatif Köksal, Timo Schick, Hinrich Schütze

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor.

Or Honovich, Thomas Scialom, Omer Levy, Timo Schick

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Task-aware Retrieval with Instructions.

Akari Asai, Timo Schick, Patrick S. H. Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, Wen-tau Yih

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Few-Shot Learning mit Sprachmodellen.

Timo Schick

Ausgezeichnete Informatikdissertationen, 2022

True Few-Shot Learning With Prompts - A Real-World Perspective.

Timo Schick, Hinrich Schütze

Trans. Assoc. Comput. Linguistics, 2022

EditEval: An Instruction-Based Benchmark for Text Improvements.

Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick S. H. Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni

CoRR, 2022

Few-shot Learning with Retrieval Augmented Language Models.

Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave

CoRR, 2022

Improving Wikipedia Verifiability with AI.

Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel

CoRR, 2022

Leveraging QA Datasets to Improve Generative Data Augmentation.

Dheeraj Mekala, Tu Vu, Timo Schick, Jingbo Shang

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

CoDA21: Evaluating Language Understanding Capabilities of NLP Models With Context-Definition Alignment.

Lütfi Kerem Senel, Timo Schick, Hinrich Schütze

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021

Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP.

Timo Schick, Sahana Udupa, Hinrich Schütze

Trans. Assoc. Comput. Linguistics, 2021

It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners.

Timo Schick, Hinrich Schütze

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Generating Datasets with Pretrained Language Models.

Timo Schick, Hinrich Schütze

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Few-Shot Text Generation with Natural Language Instructions.

Timo Schick, Hinrich Schütze

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference.

Timo Schick, Hinrich Schütze

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020

Few-Shot Text Generation with Pattern-Exploiting Training.

Timo Schick, Hinrich Schütze

CoRR, 2020

Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification.

Timo Schick, Helmut Schmid, Hinrich Schütze

Proceedings of the 28th International Conference on Computational Linguistics, 2020

BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance.

Timo Schick, Hinrich Schütze

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking.

Timo Schick, Hinrich Schütze

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts.

Timo Schick, Hinrich Schütze

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Learning Semantic Representations for Novel Words: Leveraging Both Form and Context.

Timo Schick, Hinrich Schütze

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017

Transition-Based Generation from Abstract Meaning Representations.

Timo Schick

CoRR, 2017