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个人简介
I mainly work on deep-learning-based reasoning and its applications. I am interested in the following subjects:
Generative models, in particular, induction of compositional structure in generative models and modeling of posteriors over high-dimensional explanatory variables. Much of my recent work is on generative flow networks, or GFlowNets, which are a path towards inference machines that build structured, uncertainty-aware explanations for observed data.
Applications to natural language processing: what large language models can do, what they cannot do, and how to overcome their limitations with inference procedures that induce behaviours more akin to human reasoning.
Generative models, in particular, induction of compositional structure in generative models and modeling of posteriors over high-dimensional explanatory variables. Much of my recent work is on generative flow networks, or GFlowNets, which are a path towards inference machines that build structured, uncertainty-aware explanations for observed data.
Applications to natural language processing: what large language models can do, what they cannot do, and how to overcome their limitations with inference procedures that induce behaviours more akin to human reasoning.
研究兴趣
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ICLR 2023 (2023)
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international geoscience and remote sensing symposiumpp.7046-7049, (2020)
THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCEno. 03 (2020): 2509-2517
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