Rawat, Ankit Singh

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

Modifying Memories in Transformer Models

Zhu, C., Rawat, A. S., Zaheer, M., Bhojanapalli, S., Li, D., Yu, F., & Kumar, S. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 48

Large Language Models with Controllable Working Memory

Li, D., Rawat, A. S., Zaheer, M., Wang, X., Lukasik, M., Veit, A., Yu, F., & Kumar, S. (2023) · Findings of the Association for Computational Linguistics: ACL 2023

Topic ModelingNatural Language Processing Techniques

Cited by 46

Low-Rank Bottleneck in Multi-head Attention Models

Bhojanapalli, S., Yun, C., Rawat, A. S., Reddi, S. J., & Kumar, S. (2020) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 46

DistillSpec: Improving Speculative Decoding via Knowledge Distillation

Zhou, Y., Lyu, K., Rawat, A. S., Menon, A. K., Rostamizadeh, A., Kumar, S., Kagy, J.-F., & Agarwal, R. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 9

Language Model Cascades: Token-level uncertainty and beyond

Gupta, N., Narasimhan, H., Jitkrittum, W., Rawat, A. S., Menon, A. K., & Kumar, S. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3

Think before you speak: Training Language Models With Pause Tokens

Goyal, S., Ji, Z., Rawat, A. S., Menon, A. K., Kumar, S., & Nagarajan, V. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2