Customer-obsessed science


Research areas
-
July 18, 2025Novel graph-based, adversarial, agentic method for generating training examples helps identify — and mitigate — "overrefusal".
Featured news
-
2024With recent rapid growth in online shopping, AI-powered Engagement Surfaces (ES) have become ubiquitous across retail services. These engagement surfaces perform an increasing range of functions, including recommending new products for purchase, remind-ing customers of their orders and providing delivery notifications. Understanding the causal effect of engagement surfaces on value driven for customers
-
2024Understanding user intentions is essential for improving product recommendations, navigation suggestions, and query reformula-tions. However, user intentions can be intricate, involving multiple sessions and attribute requirements connected by logical operators such as And, Or, and Not. For instance, a user may search for Nike or Adidas running shoes across various sessions, with a preference for purple
-
2024Recommender systems are widely used to suggest engaging content, and Large Language Models (LLMs) have given rise to generative recommenders. Such systems can directly generate items, including for open-set tasks like question suggestion. While the world knowledge of LLMs enable good recommendations, improving the generated content through user feedback is challenging as continuously fine-tuning LLMs is
-
2024Graph machine learning (GML) is effective in many business applications. However, making GML easy to use and applicable to industry applications with massive datasets remain challenging. We developed GraphStorm, which provides an end-to-end solution for scalable graph construction, graph model training and inference. GraphStorm has the following desirable properties: (a) Easy to use: it can perform graph
-
ACL Findings 20242024Leveraging external knowledge is crucial for achieving high performance in knowledge-intensive tasks, such as question answering. The retrieve-and-read approach is widely adopted for integrating external knowledge into a language model. However, this approach suffers from increased computational cost and latency due to the long context length, which grows proportionally with the number of retrieved knowledge
Academia
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all