Brown, Adam R.

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

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

Second law of quantum complexity

Brown, A. R., & Susskind, L. (2018) · Physical Review D

Black Holes and Theoretical PhysicsComputability, Logic, AI Algorithms

Cited by 292

The Python’s Lunch: geometric obstructions to decoding Hawking radiation

Brown, A. R., Gharibyan, H., Penington, G., & Susskind, L. (2020) · Journal of High Energy Physics

Black Holes and Theoretical PhysicsQuantum many-body systems

Cited by 124

Complexity of Jackiw-Teitelboim gravity

Brown, A. R., Gharibyan, H., Lin, H. W., Susskind, L., Thorlacius, L., & Zhao, Y. (2019) · Physical Review D

Black Holes and Theoretical PhysicsNoncommutative and Quantum Gravity Theories

Cited by 88

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