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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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Featured news
Hosted by Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, 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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KDD 20232023Pre-trained language models (PLMs) such as BERT, RoBERTa, and DeBERTa have achieved state-of-the-art performance on various downstream tasks. The enormous sizes of PLMs hinder their deployment in resource-constrained scenarios, e.g., on edge and mobile devices. To address this issue, many model compression approaches have been proposed to reduce the number of model parameters. This paper focuses on compressing
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Interspeech 20232023Conformer-based end-to-end automatic speech recognition (ASR) models have gained popularity in recent years due to their exceptional performance at scale. However, there are significant computation, memory and latency costs associated with running inference on such models. With the aim of mitigating these issues, we evaluate the efficacy of pruning Conformer layers while fine-tuning only on 20% of the data
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KDD 2023 Workshop on Mining and Learning with Graphs2023The rise of online marketplaces has led to increased concerns regarding the presence of bad actors involved in counterfeit or engage in fraudulent activities. While efforts are being made by organizations to monitor and address these issues, bad actors persistently find new ways to engage in fraudulent behavior, including creating new accounts using different credentials, account hijacking etc. To combat
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ACL Findings 20232023Recommending a diversity of product types (PTs) is important for a good shopping experience when customers are looking for products around their high-level shopping interests (SIs) such as hiking. However, the SI-PT connection is typically absent in e-commerce product catalogs and expensive to construct manually due to the volume of potential SIs, which prevents us from establishing a recommender with easily
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KDD 2023 Workshop on Mining and Learning with Graphs2023Graph Neural Networks (GNNs) have gained popularity in various fields, such as recommendation systems, social network analysis and fraud detection. However, despite their effectiveness, the topological nature of GNNs makes it challenging for users to understand the model predictions. To address this challenge, we built a user-friendly UI to visualize the most important relationships for both homogeneous
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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.
