The submission opens October 1 and closes on November 12, 2025
New technologies are helping vulnerable communities produce maps that integrate topographical, infrastructural, seasonal, and real-time data — an essential tool for many humanitarian endeavors.
Amazon vice president and distinguished engineer Marc Brooker explains how agentic systems work under the hood — and how AWS’s new AgentCore framework implements their essential components.
In-context learning enables a model that can solve forecasting tasks with an arbitrary number of dimensions in a zero-shot manner.
A new dataset with over 238,000 images challenges and advances the state of the art in visual defect detection for complex retail applications.
Customer-obsessed science
Research areas
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November 6, 2025A new approach to reducing carbon emissions reveals previously hidden emission “hotspots” within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints. -
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Featured news
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
The collaboration will advance research in generative AI, robotics, natural language processing and cloud computing while fostering innovation in foundational and emerging technologies.
University teams battle to harden and hack AI coding assistants in head-to-head tournament
David Chang/Getty Images/iStockphoto
Led by David Luan and Pieter Abbeel, the lab will focus on developing new foundational capabilities for enabling useful AI agents.
The company's new state-of-the-art foundation models deliver frontier intelligence and industry-leading price performance.
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2025For an e-commerce domain, the address is the single most important piece of data for ensuring accurate and reliable deliveries. In this two-part study, we first outline the construction of a language model to assist customers with address standardization and in the latter part, we detail a novel Pareto-ensemble multi-task prediction algorithm that derives critical insights from addresses to minimize operational
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2025We introduce a novel, training free cascade for auto-prompting Large Language Models (LLMs) to assess product quality in e-commerce. Our system requires no training labels or model fine-tuning, instead automatically generating and refining prompts for evaluating attribute quality across tens of thousands of product category–attribute pairs. Starting from a seed of human-crafted prompts, the cascade progressively
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NeurIPS 2025 Workshop on Multi-Turn Interactions in Large Language Models2025Simulating step-wise human behavior with Large Language Models (LLMs) has become an emerging research direction, enabling applications in various practical domains. While prior methods, including prompting, supervised fine-tuning (SFT), and reinforcement learning (RL), have shown promise in modeling step-wise behavior, they primarily learn a population-level policy without conditioning on a user's persona
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2025Recent advancements in large language models (LLMs) have enabled their successful application to a broad range of tasks. However, in information-intensive tasks, the prompt length can grow fast, leading to increased computational requirements, performance degradation, and induced biases from irrelevant or redundant information. Recently, various prompt compression techniques have been introduced to optimize
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2025Retrieval-Augmented Generation (RAG) has significantly mitigated the hallucinations of Large Language Models (LLMs) by grounding the generation with external knowledge. Recent extensions of RAG to graph-based retrieval offer a promising direction, leveraging the structural knowledge for multi-hop reasoning. However, existing graph RAG typically decouples retrieval and reasoning processes, which prevents
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
