FYI:(rpt)Symbolic Reasoning for Large Language Models
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alex.shkotin
Jun 20, 2024, 12:44:47 AMJun 20
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June, 20 – 5:00PM (CET)
Title: Symbolic Reasoning for Large Language Models
Speaker: Guy Van den Broeck, UCLA, USA
Link Streaming (Live section): https://www.youtube.com/c/AixiaIt
Many expect that AI will solve society’s problems by simply being more intelligent than we are. Implicit in this bullish perspective is the assumption that AI will naturally learn to reason from data: that it can form trains of thought that “make sense”, similar to how a human expert might reason about a case, or more formally, how a mathematician might prove a theorem. This talk will investigate the question whether this behavior can be learned from data, and how we can design the next generation of AI techniques that can achieve such capabilities. It will focus on neurosymbolic reasoning for large language models, both at training and generation time, using probabilistic circuits as the architecture that bridges learning and reasoning.
Title: Symbolic Reasoning for Large Language Models
Speaker: Guy Van den Broeck, UCLA, USA
Link Streaming (Live section): https://www.youtube.com/c/AixiaIt
Many expect that AI will solve society’s problems by simply being more intelligent than we are. Implicit in this bullish perspective is the assumption that AI will naturally learn to reason from data: that it can form trains of thought that “make sense”, similar to how a human expert might reason about a case, or more formally, how a mathematician might prove a theorem. This talk will investigate the question whether this behavior can be learned from data, and how we can design the next generation of AI techniques that can achieve such capabilities. It will focus on neurosymbolic reasoning for large language models, both at training and generation time, using probabilistic circuits as the architecture that bridges learning and reasoning.
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