Customer-obsessed science
-
September 30, 2024From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.
-
September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
-
September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
-
-
September 29 - October 4, 2024
-
October 21 - 25, 2024
-
September 25, 2024
Now open until November 6, Amazon Research Awards will be seeking proposals in the following research areas: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography, and Sustainability.
-
NeurIPS 20232023We present a framework for transfer learning that efficiently adapts a large basemodel by learning lightweight cross-attention modules attached to its intermediate activations. We name our approach InCA (Introspective-Cross-Attention) and show that it can efficiently survey a network’s representations and identify strong performing adapter models for a downstream task. During training, InCA enables training
-
KDD 2024, NeurIPS 2023 Workshop on Distribution Shifts (DistShifts)2023Pre-trained language models (PLMs) have seen tremendous success in text classification (TC) problems in the context of Natural Language Processing (NLP). In many real-world text classification tasks, the class definitions being learned do not remain constant but rather change with time - this is known as concept shift. Most techniques for handling concept shift rely on retraining the old classifiers with
-
NeurIPS 20232023Earth system forecasting has traditionally relied on complex physical models that are computationally expensive and require significant domain expertise. In the past decade, the unprecedented increase in spatiotemporal Earth observation data has enabled data-driven forecasting models using deep learning techniques. These models have shown promise for diverse Earth system forecasting tasks. However, they
-
NeurIPS 20232023Ordinal classification (OC), i.e., labeling instances along classes with a natural ordering, is common in multiple applications such as disease severity labeling and size or budget based recommendations. Often in practical scenarios, it is desirable to obtain a small set of likely classes with a guaranteed high chance of including the true class. Recent works on conformal prediction (CP) address this problem
-
NeurIPS 20232023Deep learning methods have achieved state-of-the-art performance in most modeling tasks involving images, text and audio, however, they typically underperform tree-based methods on tabular data. In this paper, we hypothesize that a significant contributor to this performance gap is the interaction between irregular target functions resulting from the heterogeneous nature of tabular feature spaces, and the
Resources
-
We look for talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
-
We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
-
Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.