Customer-obsessed science
Research areas
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July 30, 20268 min readInstead of compromising among parameter updates dictated by different training objectives, ControlG allocates computational capacity to objectives sequentially and dynamically. -
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July 9, 202610 min read
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The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
The Antibody Developability Benchmark is powered by one of the most diverse antibody datasets in public literature, enabling transparent performance evaluation for AI-guided antibody design.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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IISE Expo 20232023Construction auditing is a vital step in designing new sites in fulfillment centers (FCs). The audits include inspection processes for newly launched buildings which ensure that the buildings meet workplace standards. In current practice the process of scheduling construction audits and prioritizing the checklists when launching new buildings is highly manual, and requires going over lengthy textual data
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SIGIR 20232023The substitute-based recommendation is widely used in E-commerce to provide better alternatives to customers. However, existing re-search typically uses customer behavior signals like co-view and view-but-purchase-another to capture the substitute relationship. Despite its intuitive soundness, such an approach might ignore the functionality and characteristics of products. In this paper, we adapt substitute
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ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models2023Despite their high levels of robustness, Contrastive Language-Image Models (CLIP) still require some form of downstream adaptation when applied to tasks sufficiently out-of-domain with respect to their training set. Recent methods propose light-weight adapters on the model features, primarily focused on the few-shot domain. All such approaches however, require per-task hyperparameter tuning which necessitates
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SIGIR 20232023In this paper we introduce SimTDE, a simple knowledge distillation framework to compress sentence embeddings transformer models with minimal performance loss and significant size and latency reduction. SimTDE effectively distills large and small transformers via a compact token embedding block and a shallow encoding block, connected with a projection layer, relaxing dimension match requirement. SimTDE simplifies
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CVPR 2023 Workshop on Computer Vision for Fashion, Art, and Design2023This paper presents Shape of You (SoY), an approach to improve the accuracy of 3D body shape estimation for vision-based clothing recommendation systems. While existing methods have successfully estimated 3D poses, there remains a lack of work in precise shape estimation, particularly for diverse human bodies. To address this gap, we propose two loss functions that can be readily integrated into parametric
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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
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