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August 26, 20265 min readDiscounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives. -
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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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WSDM 2026 Generative AI for Streaming Media (GenAI4SM)2026Collaborative filtering is a foundational component of music recommender systems, powering a variety of recommendation tasks from retrieving the most relevant tracks, albums, artists, and podcasts for a given user to more nuanced objectives such as content discovery, familiar listening, and new release recommendation. To enable scalable, low-latency inference, content-retrieval models compute latent user
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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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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.
