Customer-obsessed science
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September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
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September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
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September 10, 2024Automated reasoning and optimizations specific to CPU microarchitectures improve both performance and assurance of correct implementation.
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September 29 - October 4, 2024
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November 12 - 16, 2024
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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.
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ICSE 20242024Identifying correct and complete taint specifications is critical for detecting vulnerabilities in the ever-changing landscape of software security, and an automated scalable and practical solution remains elusive in the field. In this paper, we report our semi-automated scheme for inferring and maintaining taint specifications at industrial scale. Knowledge graph is adopted as the core engine to represent
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2024As embodied agents learn to interact, it is crucial for them to understand when, what, and to whom they should respond. While advances in natural-language processing and speech technologies have enabled conversational agents to focus on what to respond, they still struggle to determine when and to whom they should respond. In this paper, we address the addressee detection (Talking-To-Me, TTM) problem under
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IAAE 2023, Research Methods and Applications on Macroeconomic Forecasting2024We propose a simple yet robust framework to nowcast recession risk at a monthly frequency in both the United States and the Euro Area. Our nowcast leverages both macroeconomic and financial conditions, and is available the first business day after the reference month closes. In particular, we argue that financial conditions are not only useful to predict future downturns–as emphasized by the existing literature–but
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ICIPACV 20242024Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data
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EACL 20242024We present ParrotTTS, a modularized text-to-speech synthesis model leveraging disentangled self-supervised speech representations. It can train a multi-speaker variant effectively using transcripts from a single speaker. ParrotTTS adapts to a new language in low resource setup and generalizes to languages not seen while training the self-supervised back-bone. Moreover, without training on bilingual or parallel
Resources
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We look for talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
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We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
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Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.