Using ensembles of agents to generate and refine interactions annotated with chains of thought improves performance on a battery of benchmarks by an average of 29%.
Language models inspired by specialized processing regions in the brain offer significant time and cost savings.
An ensemble of models, weighted according to their reluctance to flag anomalies, outperforms its predecessors.
Unique end-of-arm tools with three-dimensional force sensors and innovative control algorithms enable robotic arms to “pick” items from and “stow” items in fabric storage pods.
We present Amazon Nova Premier, our most capable multimodal foundation model and teacher for model distillation.
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Research areas
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July 29, 2025New cost-to-serve-software metric that accounts for the full software development lifecycle helps determine which software development innovations provide quantifiable value.
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Created for students keen to build their career in machine learning, the fifth edition of the program is now open for all eligible students from recognized institutes in India.
University teams battle to harden and hack AI coding assistants in head-to-head tournament
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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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ECIR 20252024Training sequential recommenders such as SASRec with uniform sample weights achieves good overall performance but can fall short on specific user groups. One such example is popularity bias, where mainstream users receive better recommendations than niche content viewers. To improve recommendation quality across diverse user groups, we explore three Distributionally Robust Optimization(DRO) methods: Group
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ASEE 20242024Many students choose to major in engineering to join the community of professional engineers and gain exposure to the field through their college experience [1]. However, research suggests that engineering graduates may not be adequately prepared for the workplace due to the complexities of engineering work [2]. Engineering work involves complexity, ambiguity, and contradictions [3], and developing innovation
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Incomplete tabular datasets are ubiquitous in many applications for a number of reasons such as human error in data collection or privacy considerations. One would expect a natural solution for this is to utilize powerful generative models such as diffusion models, which have demonstrated great potential across image and continuous domains. However, vanilla diffusion models often exhibit sensitivity to
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IGARSS 20242024The ever-increasing demand for digital maps in various do-mains amplifies the importance of having accurate and up-to-date maps. To address this, the proposed system pervasively conflates large volume of sign detections recorded by a transportation fleet of vehicles into map database. Detected and geo-localized sign objects collected from the fleet over a time period are passed through a context-aware clustering
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IWSM 20242024In this paper several mathematical models for end-to-end network delay are derived, where exponential wait times at intermediate network routers are assumed. The feasibility of using these models to extract parameters related to the routers is investigated by performing closure tests using synthetic data generated from the models themselves. Data from an experimental test bed is used to compare the different
Academia
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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.
