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ASSET Seminar: “Inherent Interpretability via Language Model Guided Bottleneck Design” (Mark Yatskar, Penn)

ABSTRACT: As deep learning systems improve, their applicability to critical domains is hampered because of a lack of transparency. Post-hoc explanations attempt to address this concern but they provide no […]

ASSET Seminar: “What Constitutes a Good Explanation?” (Lyle Ungar, Penn)

ABSTRACT:  Shapley values and similar methods are widely used to explain the importance of features in model predictions. Clarity in the semantics of these feature importances is subtle, but crucial: […]

ASSET Seminar: “The Future of Algorithm Auditing is Sociotechnical” (Danaë Metaxa, Penn)

ABSTRACT:  Algorithm audits are powerful tools for studying black-box systems without direct knowledge of those systems’ inner workings. While they have been effectively deployed to identify harms and biases in […]

ASSET Seminar: “Copyright, Machine Learning Research, and the Generative-AI Supply Chain” (A. Feder Cooper, Cornell University)

ABSTRACT: “Does generative AI infringe copyright?” is an urgent question. It is also a difficult question, for two reasons. First, “generative AI” is not just one product from one company. […]

ASSET Seminar: “Towards a Design Flow for Verified AI-Based Autonomy” (Sajit A. Seshia, University of California, Berkeley)

ABSTRACT: Verified artificial intelligence (AI) is the goal of designing AI-based systems that have strong, ideally provable, assurances of correctness with respect to formally specified requirements. This talk will review […]

ASSET Seminar: “Lifelong Learning for Autonomous Systems: Progress and Challenges” (Eric Eaton, Penn)

ABSTRACT:  Research in lifelong or continual machine learning has advanced rapidly over the past few years, primarily focusing on enabling learned models to acquire new tasks over time while avoiding […]

ASSET Seminar: “Towards Code-Aware Code Models” (Baishakhi Ray, Columbia University)

ABSTRACT: The past decade has seen unprecedented growth in Software Engineering— developers spend enormous time and effort to create new products. With such enormous growth comes the responsibility of producing […]

ASSET/IBI Symposium on Trustworthy AI for Health Care

Organizers: Rajeev Alur (Penn Engineering), John Holmes (PSOM), Insup Lee (Penn Engineering), Qi Long (PSOM), Marylyn Richie (PSOM) Event Description: Artificial intelligence and machine learning promise to revolutionize nearly every field, […]

ASSET Seminar: “Getting Computers to Do What We Want: Programming Meets Machine Learning” (Michael Littman, Brown University)

ABSTRACT: It is immensely empowering to delegate information processing and automation work to machines and have them carry out difficult tasks on our behalf. But programming computers is hard. The […]

ASSET Seminar: “Safety through Agility – Safe and Performant Control for Learning-Enabled Autonomous Systems” (Mangharam, Penn)

ABSTRACT: We present three approaches to combine formal methods, control theory, and machine learning for safe and performant autonomous systems.  Safe control for learning-enabled systems: We present our recent progress […]

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