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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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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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WACV 20232023Detecting commercial Ads from a video is important. For example, the commercial break frequency and duration are two metrics to measure the user experience for streaming service providers such as Amazon Freevee. The detection can be done intrusively by intercepting the network traffic and then parsing the service providers data and logs, or non-intrusively by capturing the videos streamed by content providers
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IAAI 20232023Detecting robotic traffc at scale on online ads needs an approach that is scalable, comprehensive, precise, and can rapidly respond to changing traffic patterns. In this paper we describe SLIDR or SLIce-Level Detection of Robots, a realtime deep neural network model trained with weak supervision to identify invalid clicks on online ads. We ensure fairness across different traffc slices by formulating a
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SLT 20222023Regional accents of the same language affect not only how words are pronounced (i.e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intonation. This paper investigates a novel flow-based approach to accent conversion using normalizing flows. The proposed approach revolves around three steps: remapping the phonetic conditioning, to better match the target accent,
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AAAI 2023 Workshop on Artificial Intelligence Safety2023Gradient boosting decision trees (GBDTs) are widely applied on tabular data in real-world ML systems. Quantifying uncertainty in GBDT models is thus essential for decision making and for avoiding costly mistakes to ensure an interpretable and safe deployment of tree-based models. Recently, Bayesian ensemble of GBDT models is used to measure uncertainty by leveraging an algorithm called stochastic gradient
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WSDM 20232023Directed graphs are ubiquitous and have applications across multiple domains including citation, website, social, and traffic networks. Yet, the majority of research involving graph neural networks (GNNs) focus on undirected graphs. In this paper, we deal with the problem of node recommendation in non-attributed directed graphs. Specifically, given a directed graph and query node as input, the goal is to
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Gretchen Ertl
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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
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