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July 10, 20265 min readHydroShear, a new physics-based simulator, teaches robots how to use their sense of touch to perform complex manipulation tasks, in a way that transfers seamlessly to the real world. -
July 9, 202610 min read -
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Hosted by Danielle Perszyk, cognitive scientist at Amazon, the podcast features researchers tackling the hardest problems in agentic AI — from building reliable perception systems to designing training environments that mirror human learning.
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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NAACL 2022 Workshop on Semantic Evaluation2022We present the findings of SemEval-2022 Task 11 on Multilingual Complex Named Entity Recognition MULTICONER. Divided into 13 tracks, the task focused on methods to identify complex named entities (like media titles, products, and groups) in 11 languages in both monolingual and multi-lingual scenarios. Eleven tracks were for building monolingual NER models for individual languages, one track focused on multilingual
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SIGIR 2022 Workshop on eCommerce2022Recently, gradient based multi-objective optimization methods have been developed to find models that are aligned with preference directions (MOO-PD) in machine learning community. Most of the methods are tuned and tested with multi-task learning problems in computer vision tasks with deep neural networks. While MOO-PD is useful in building a model with user specified MOO criteria, there is no existing
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Interspeech 20222022Conversational agents commonly utilize keyword spotting (KWS) to initiate voice interaction with the user. For user experience and privacy considerations, existing approaches to KWS largely focus on accuracy, which can often come at the expense of introduced latency. To address this tradeoff, we propose a novel approach to control KWS model latency and which generalizes to any loss function without explicit
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L2-GEN: A neural phoneme paraphrasing approach to L2 speech synthesis for mispronunciation diagnosisInterspeech 20222022In this paper, we study the problem of generating mispronounced speech mimicking non-native (L2) speakers learning English as a Second Language (ESL) for the mispronunciation detection and diagnosis (MDD) task. The paper is motivated by the widely observed yet not well addressed data sparsity issue in MDD research where both L2 speech audio and its fine-grained phonetic annotations are difficult to obtain
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ECML-PKDD 20222022Related product recommendation (RPR) is pivotal to the success of any e-commerce service. In this paper, we deal with the problem of recommending related products i.e., given a query product, we would like to suggest top-k products that have high likelihood to be bought together with it. Our problem implicitly assumes asymmetry i.e., for a phone, we would like to recommend a suitable phone case, but for
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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.
