Customer-obsessed science
Research areas
-
September 26, 20259 min readTo transform scientific domains, foundation models will require physical-constraint satisfaction, uncertainty quantification, and specialized forecasting techniques that overcome data scarcity while maintaining scientific rigor.
-
-
September 2, 20253 min read
-
-
August 21, 20257 min read
Featured news
-
2025Large Language Models (LLMs) have emerged as powerful tools for generating coherent text, understanding context, and performing reasoning tasks. However, they struggle with temporal reasoning, which requires processing time-related information such as event sequencing, durations, and inter-temporal relationships. These capabilities are critical for applications including question answering, scheduling,
-
2025When serving a single base LLM with several different LoRA adapters simultaneously, the adapters cannot simply be merged with the base model’s weights as the adapter swapping would create overhead and requests using different adapters could not be batched. Rather, the LoRA computations have to be separated from the base LLM computations, and in a multi-device setup the LoRA adapters can be sharded in a
-
NeurIPS 2025 Workshop on Continual and Compatible Foundation Model Updates2025Command-lines are a common attack surface in cybersecurity. Yet they often contain sensitive user information, creating a dual challenge: systems must detect suspicious commands accurately while protecting user privacy. Existing approaches typically tackle one challenge without the other. To address this gap, we present PASTRAL, a practical framework for privacy-preserving detection of suspicious command-lines
-
NeurIPS 2025 Workshop on Continual and Compatible Foundation Model Updates2025Continual Learning (CL) is a vital requirement for deploying large language models (LLMs) in today’s dynamic world. Existing approaches seek to acquire task-specific knowledge via parameter efficient fine-tuning (PEFT) with reduced compute overhead. However, sequential FT often sacrifices performance retention and forward transfer, especially under replay-free constraints. We introduce ELLA, a novel CL
-
AES Show 20252025Surround sound systems commonly distribute loudspeakers along standardized layouts for multichannel audio reproduction. However in less controlled environments, practical layouts vary in loudspeaker quantity, placement, and listening locations / areas. Deviations from standard layouts introduce sound-field errors that degrade acoustic timbre, imaging, and clarity of audio content reproduction. This work
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all