Michalewski, Henryk

PaLM: Scaling Language Modeling with Pathways

Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2,590

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Model-Based Reinforcement Learning for Atari

Kaiser, L., Babaeizadeh, M., Milos, P., Osinski, B., Campbell, R. H., Czechowski, K., Erhan, D., Finn, C., Kozakowski, P., Levine, S., et al. (2019) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 467

Program Synthesis with Large Language Models

Austin, J., Odena, A., Nye, M., Bosma, M., Michalewski, H., Dohan, D., Jiang, E., Cai, C., Terry, M., Le, Q., et al. (2021) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 388

Solving Quantitative Reasoning Problems with Language Models

Lewkowycz, A., Andreassen, A., Dohan, D., Dyer, E., Michalewski, H., Ramasesh, V., Slone, A., Anil, C., Schlag, I., Gutman-Solo, T., et al. (2022) · arXiv

Mathematics Education and PedagogyTopic Modeling

Cited by 358

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Gemma: Open Models Based on Gemini Research and Technology

Gemma Team, Mesnard, T., Hardin, C., Dadashi, R., Bhupatiraju, S., Pathak, S., Sifre, L., Rivière, M., Kale, M. S., Love, J., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 284

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Chen, X., Choromanski, K., Ding, T., Driess, D., Dubey, A., Finn, C., et al. (2023) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 276

Show Your Work: Scratchpads for Intermediate Computation with Language Models

Nye, M., Andreassen, A. J., Gur-Ari, G., Michalewski, H., Austin, J., Bieber, D., Dohan, D., Lewkowycz, A., Bosma, M., Luan, D., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 144

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Reinforcement Learning of Theorem Proving

Kaliszyk, C., Urban, J., Michalewski, H., & Olšák, M. (2018) · arXiv

AI-based Problem Solving and PlanningLogic, programming, and type systems

Cited by 68

Multi-Game Decision Transformers

Lee, K.-H., Nachum, O., Yang, M. (., Lee, L., Freeman, D., Guadarrama, S., Fischer, I., Xu, W., Jang, E., Michalewski, H., et al. (2022) · Advances in Neural Information Processing Systems 35

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 54

Promptbreeder: Self-Referential Self-Improvement via Prompt Evolution

Fernando, C., Banarse, D., Michalewski, H., Osindero, S., & Rocktäschel, T. (2023) · arXiv

Topic ModelingEvolutionary Algorithms and Applications

Cited by 31

Language Model Cascades

Dohan, D., Xu, W., Lewkowycz, A., Austin, J., Bieber, D., Lopes, R. G., Wu, Y., Michalewski, H., Saurous, R. A., Sohl-dickstein, J., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 22

Towards Finding Longer Proofs

Zombori, Z., Csiszárik, A., Michalewski, H., Kaliszyk, C., & Urban, J. (2021) · Lecture Notes in Computer Science

Logic, programming, and type systemsAI-based Problem Solving and Planning

Cited by 22

Olympiad-level formal mathematical reasoning with reinforcement learning

Hubert, T., Mehta, R., Sartran, L., Horváth, M. Z., Žužić, G., Wieser, E., Huang, A., Schrittwieser, J., Schroecker, Y., Masoom, H., et al. (2026) · Nature

Artificial Intelligence ApplicationsMathematics, Computing, and Information Processing

Cited by 19

Focused Transformer: Contrastive Training for Context Scaling

Tworkowski, S., Staniszewski, K., Pacek, M., Wu, Y., Michalewski, H., & Milos, P. (2023) · Advances in Neural Information Processing Systems 36

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 18

Towards Robust Mathematical Reasoning

Luong, T., Hwang, D., Nguyen, H. H., Ghiasi, G., Chervonyi, Y., Seo, I., Kim, J., Bingham, G., Lee, J., Mishra, S., et al. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 4