Stenetorp, Pontus

Convolutional 2D Knowledge Graph Embeddings

Dettmers, T., Minervini, P., Stenetorp, P., & Riedel, S. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Advanced Graph Neural NetworksTopic Modeling

Cited by 2,486

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Lu, Y., Bartolo, M., Moore, A., Riedel, S., & Stenetorp, P. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 615

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Lu, Y., Bartolo, M., Moore, A., Riedel, S., & Stenetorp, P. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 610

Dynabench: Rethinking Benchmarking in NLP

Kiela, D., Bartolo, M., Nie, Y., Kaushik, D., Geiger, A., Wu, Z., Vidgen, B., Prasad, G., Singh, A., Ringshia, P., et al. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 254

Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets

Lewis, P., Stenetorp, P., & Riedel, S. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Topic ModelingInformation Retrieval and Search Behavior

Cited by 145

UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)

Yoneda, T., Mitchell, J., Welbl, J., Stenetorp, P., & Riedel, S. (2018) · Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)

Topic ModelingInformation Retrieval and Search Behavior

Cited by 101

Convolutional 2D Knowledge Graph Embeddings

Dettmers, T., Minervini, P., Stenetorp, P., & Riedel, S. (2017) · arXiv

Advanced Graph Neural NetworksTopic Modeling

Cited by 30

What the DAAM: Interpreting Stable Diffusion Using Cross Attention

Tang, R., Liu, L., Pandey, A., Jiang, Z., Yang, G., Kumar, K., Stenetorp, P., Lin, J., & Ture, F. (2022) · arXiv

Explainable Artificial Intelligence (XAI)Generative Adversarial Networks and Image Synthesis

Cited by 4

Improving Language Plasticity via Pretraining with Active Forgetting

Chen, Y., Marchisio, K., Raileanu, R., Adelani, D., Stenetorp, P. L. E. S., Riedel, S., & Artetxe, M. (2023) · Advances in Neural Information Processing Systems 36

Domain Adaptation and Few-Shot LearningNatural Language Processing Techniques

Cited by 3

Quantifying Variance in Evaluation Benchmarks

Madaan, L., Singh, A. K., Schaeffer, R., Poulton, A., Koyejo, S., Stenetorp, P., Narang, S., & Hupkes, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

AIRA_2: Overcoming Bottlenecks in AI Research Agents

Hambardzumyan, K., Baldwin, N., Toledo, E., Hazra, R., Kuchnik, M., Omari, B. A., Foster, T. S., Protopopov, A., Gagnon-Audet, J.-C., Mediratta, I., et al. (2026) · arXiv

Artificial Intelligence ApplicationsScientific Computing and Data Management

Cited by 1

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench

Toledo, E., Hambardzumyan, K., Josifoski, M., Hazra, R., Baldwin, N., Audran-Reiss, A., Kuchnik, M., Magka, D., Jiang, M., Lupidi, A. M., et al. (2025) · arXiv

Machine Learning and Data ClassificationEvolutionary Algorithms and Applications

Cited by 0