5 papers
MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings
Laxman Dhulipala, Majid Hadian, Rajesh Jayaram +2
Neural embedding models have become a fundamental component of modern information retrieval (IR) pipelines. These models produce a single embedding per data-po…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
Massively Parallel Minimum Spanning Tree in General Metric Spaces
Amir Azarmehr, Soheil Behnezhad, Rajesh Jayaram +3
We study the minimum spanning tree (MST) problem in the massively parallel computation (MPC) model. Our focus is particularly on the *strictly sublinear* regime of MPC where the sp…
Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe
Chong You, Rajesh Jayaram, Ananda Theertha Suresh +3
Dual encoder (DE) models, where a pair of matching query and document are embedded into similar vector representations, are widely used in information retrieval due to their simpli…
CRISP: Clustering Multi-Vector Representations for Denoising and Pruning
João Veneroso, Rajesh Jayaram, Jinmeng Rao +3
Multi-vector models, such as ColBERT, are a significant advancement in neural information retrieval (IR), delivering state-of-the-art performance by representing queries and docume…