Seminars

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Sasha Rush (Cornell University) “Pretraining Without Attention” 12:00 pm
Sasha Rush (Cornell University) “Pretraining Without Attention” @ Hackerman Hall B17
Feb 3 @ 12:00 pm – 1:15 pm
Abstract Transformers are essential to pretraining. As we approach 5 years of BERT, the connection between attention as architecture and transfer learning remains key to this central thread in NLP. Other architectures such as CNNs and RNNs[...]
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Sharon Levy (University of California, Santa Barbara) “Responsible AI via Responsible Large Language Models” 12:00 pm
Sharon Levy (University of California, Santa Barbara) “Responsible AI via Responsible Large Language Models” @ Hackerman Hall B17
Feb 6 @ 12:00 pm – 1:15 pm
Abstract While large language models have advanced the state-of-the-art in natural language processing, these models are trained on large-scale datasets, which may include harmful information. Studies have shown that as a result, the models exhibit[...]
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Hanjie Chen (University of Virginia) “Bridging Humans and Machines: Techniques for Trustworthy NLP” 12:00 pm
Hanjie Chen (University of Virginia) “Bridging Humans and Machines: Techniques for Trustworthy NLP” @ Hackerman Hall B17
Feb 20 @ 12:00 pm – 1:15 pm
Abstract Advanced neural language models have grown ever larger and more complex, pushing forward the limits of language understanding and generation, while diminishing interpretability. The black-box nature of deep neural networks blocks humans from understanding[...]
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Wei Xu (Georgia Tech) 12:00 pm
Wei Xu (Georgia Tech) @ Hackerman Hall B17
Feb 24 @ 12:00 pm – 1:15 pm
 
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Saadia Gabriel (University of Washington) “Socially Responsible and Factual Reasoning for Equitable AI Systems” 12:00 pm
Saadia Gabriel (University of Washington) “Socially Responsible and Factual Reasoning for Equitable AI Systems” @ Hackerman Hall B17
Feb 27 @ 12:00 pm – 1:15 pm
Abstract Understanding the implications underlying a text is critical to assessing its impact, in particular the social dynamics that may result from a reading of the text. This requires endowing artificial intelligence (AI) systems with[...]
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Center for Language and Speech Processing