Saunshi, Nikunj

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors

Khodak, M., Saunshi, N., Liang, Y., Ma, T., Stewart, B., & Arora, S. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 111

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

A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks

Saunshi, N., Malladi, S., & Arora, S. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 32

Reasoning with Latent Thoughts: On the Power of Looped Transformers

Saunshi, N., Dikkala, N., Li, Z., Kumar, S., & Reddi, S. J. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Task-Specific Skill Localization in Fine-tuned Language Models

Panigrahi, A., Saunshi, N., Zhao, H., & Arora, S. (2023) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 2