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Abstract: Abstract: In this talk, I will discuss a collection of highlights from our recent work in trustworthy AI. (1) Certifying reasoning explanations with reliability guarantees and aligning with expert […]
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Abstract: We present a unified perspective on test-time thinking as a lens for improving generative AI agents through finer-grained reward modeling, data-centric reasoning, and robust alignment. Beginning with GenARM, we […] |
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Abstract: Today, reasoning is commonly interpreted as large language models generating chains of thought. Yet historically, AI reasoning had a very different meaning: executing algorithms that manipulated symbols to perform […] |
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A full-day event featuring faculty presentations, poster sessions, and networking opportunities that highlight the breadth of artificial intelligence research taking place across Penn. |
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Abstract: A mystery of large language models (LLMs) is their ability to solve novel tasks, notably through a few demonstrations in the prompt (in-context learning). Such tasks often require the […] |
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Abstract: TBD Biography: Dinesh Jayaraman was born in Chennai, India in 1989. He received the B.Tech degree in Electrical Engineering at the Indian Institute of Technology, Madras in 2011 […] |
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