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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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Featured news
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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WSC 20252025Stochastic discrete event simulation is a vital tool across industries. However, the high dimensionality and complexity of real-world systems make it challenging to develop simulations that accurately model and predict business metrics for users when faced with inaccurate input and model fidelity limitations. Addressing this challenge is critical for improving the effectiveness of industrial simulations
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KDD 2025 Workshop on Prompt Optimization2025Length control in Large Language Models (LLMs) is a crucial but under-addressed challenge, with applications ranging from voice interfaces requiring concise responses to research summaries needing comprehensive outputs. Current approaches to length control, including Regularized DPO, Length-Instruction Fine-Tuning, and tool-augmented methods, typically require expensive model retrain-ing or complex inference-time
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IROS 20252025With the advancement of robot manipulator technologies, developing custom-made low-cost manipulator arms has gained increasing popularity in the field of robotics. However, these low-cost systems often lack precise sensing and control capabilities, making reliable collision detection particularly critical to ensure safe operation. Popular methods of collision detection, which estimate external disturbances
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KDD 2025 Workshop on Online and Adaptive Recommender Systems2025Traditional recommendation systems (RecSys) face critical challenges, including limited semantic understanding of user preferences, lack of explainability, and poor adaptability to evolving user needs. These limitations hinder their ability to provide personalized, context-aware recommendations and can erode user trust. Recent work has explored the use of Large Language Models (LLMs) to address these challenges
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SIGIR GENNEXT 20252025Multilingual information retrieval has emerged as powerful tools for expanding knowledge sharing across languages. On the other hand, resources on high quality knowledge base are often scarce and in limited languages, therefore an effective embedding model to transform sentences from different languages into a feature vector space same as the knowledge base language becomes the key ingredient for cross
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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.
