McAleese, Nat

Red Teaming Language Models with Language Models

Perez, E., Huang, S., Song, F., Cai, T., Ring, R., Aslanides, J., Glaese, A., McAleese, N., & Irving, G. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 363

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., Aslanides, J., Henderson, S., Ring, R., Young, S., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 235

Improving alignment of dialogue agents via targeted human judgements

Glaese, A., McAleese, N., Trębacz, M., Aslanides, J., Firoiu, V., Ewalds, T., Rauh, M., Weidinger, L., Chadwick, M., Thacker, P., et al. (2022) · arXiv

Speech and dialogue systemsIntelligent Tutoring Systems and Adaptive Learning

Cited by 134

Open-Ended Learning Leads to Generally Capable Agents

Open Ended Learning Team, Stooke, A., Mahajan, A., Barros, C., Deck, C., Bauer, J., Sygnowski, J., Trebacz, M., Jaderberg, M., Mathieu, M., et al. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 56

Teaching language models to support answers with verified quotes

Menick, J., Trebacz, M., Mikulik, V., Aslanides, J., Song, F., Chadwick, M., Glaese, M., Young, S., Campbell-Gillingham, L., Irving, G., et al. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 53

LLM Critics Help Catch LLM Bugs

McAleese, N., Pokorny, R. M., Uribe, J. F. C., Nitishinskaya, E., Trebacz, M., & Leike, J. (2024) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 10

Competitive Programming with Large Reasoning Models

OpenAI, :, El-Kishky, A., Wei, A., Saraiva, A., Minaiev, B., Selsam, D., Dohan, D., Song, F., Lightman, H., et al. (2025) · arXiv

Teaching and Learning ProgrammingAI-based Problem Solving and Planning

Cited by 6

Prover-Verifier Games improve legibility of LLM outputs

Kirchner, J. H., Chen, Y., Edwards, H., Leike, J., McAleese, N., & Burda, Y. (2024) · arXiv

Adversarial Robustness in Machine LearningExplainable Artificial Intelligence (XAI)

Cited by 2