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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, 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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ICLR 2026 Workshop on Algorithmic Fairness Across Alignment Procedures and Agentic Systems2026When an AI assistant remembers that Sarah is a single mother working two jobs, does it interpret her stress differently than if she were a wealthy executive? As personalized AI systems increasingly incorporate long-term user memory, understanding how this memory shapes emotional reasoning is critical. We investigate how user memory affects emotional intelligence in large language models (LLMs) by evaluating
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ECML-PKDD 20262026Real-time bidding (RTB) in sponsored search advertising has been extensively studied, yet a critical gap remains: how should advertisers set optimal bids in Manual Targeting (MT) campaigns where bids must be specified upfront without real-time adjustment? Unlike Automated Targeting campaigns that dynamically modify bids based on auction context, MT campaigns, which account for nearly 30% of advertisers
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2026Direct Preference Optimization (DPO) has emerged as a simple and effective approach for aligning models with human preferences. However, existing DPO-based methods suffer from 3 key drawbacks: they rely on only a single positive-negative preference pair per question, restricting the diversity and richness of feedback; they often emphasize minimizing negative preference scores while neglecting to strengthen
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ACM BuildSys 20262026Modeling building thermal dynamics is essential for energy optimization, yet building heterogeneity and non-stationary dynamics demand per-building customization that typically requires expert intervention. Automated scientific discovery workflows powered by Large Language Models (LLM) could significantly decrease the human expertise requirements for generating custom thermal models at scale, but their
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arXiv2026We show that the standard basis of transformer hidden states already provides a training-free, architecture-general feature basis. Individual dimensions encode semantic content via their signs (±1) and confidence via their magnitudes, functioning as independent binary registers. A feature is simply a subset of dimensions with a consistent sign pattern, readable by counting sign agreements with no learned
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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.
