Schütze, Hinrich

Introduction to information retrieval

Manning, C. D., Raghavan, P., & Schütze, H. (2009) · Choice Reviews Online

Information Retrieval and Search BehaviorAlgorithms and Data Compression

Cited by 12,278

Introduction to Information Retrieval

Manning, C. D., Raghavan, P., & Schütze, H. (2008) · Cambridge University Press eBooks

Information Retrieval and Search BehaviorAlgorithms and Data Compression

Cited by 11,288

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

Schick, T., & Schütze, H. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1,305

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

Schick, T., & Schütze, H. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 747

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

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

Schick, T., Udupa, S., & Schütze, H. (2021) · Transactions of the Association for Computational Linguistics

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 227

Measuring and improving consistency in pretrained language models

Elazar, Y., Kassner, N., Ravfogel, S., Ravichander, A., Hovy, E., Schütze, H., & Goldberg, Y. (2021) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 220

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

Schick, T., Schmid, H., & Schütze, H. (2020) · Proceedings of the 28th International Conference on Computational Linguistics

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 184

Position Information in Transformers: An Overview

Dufter, P., Schmitt, M., & Schütze, H. (2022) · Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 175

E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT

Poerner, N., Waltinger, U., & Schütze, H. (2019) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 149

E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT

Poerner, N., Waltinger, U., & Schütze, H. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Topic ModelingMultimodal Machine Learning Applications

Cited by 146

Generating Datasets with Pretrained Language Models

Schick, T., & Schütze, H. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 122

Few-Shot Text Generation with Natural Language Instructions

Schick, T., & Schütze, H. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 107

Placing language in an integrated understanding system: Next steps toward human-level performance in neural language models

McClelland, J. L., Hill, F., Rudolph, M., Baldridge, J., & Schütze, H. (2020) · Proceedings of the National Academy of Sciences

Neurobiology of Language and BilingualismTopic Modeling

Cited by 91

RET-LLM: Towards a General Read-Write Memory for Large Language Models

Modarressi, A., Imani, A., Fayyaz, M., & Schütze, H. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 8

Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models

Röttger, P., Hofmann, V., Pyatkin, V., Hinck, M., Kirk, H. R., Schütze, H., & Hovy, D. (2024) · arXiv

Ethics and Social Impacts of AISentiment Analysis and Opinion Mining

Cited by 7

NoLiMa: Long-Context Evaluation Beyond Literal Matching

Modarressi, A., Deilamsalehy, H., Dernoncourt, F., Bui, T., Rossi, R. A., Yoon, S., & Schütze, H. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory

Modarressi, A., Köksal, A., Imani, A., Fayyaz, M., & Schütze, H. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

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

Schick, T., Udupa, S., & Schütze, H. (2021) · arXiv

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 1