Zobrazeno 1 - 7
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pro vyhledávání: '"Nahian, Md Sultan Al"'
Extractive question answering over clinical text is a crucial need to help deal with the deluge of clinical text generated in hospitals. While encoder models (e.g., BERT) have been popular for this reading comprehension task, recently encoder-decoder
Externí odkaz:
http://arxiv.org/abs/2407.14000
Value alignment is the task of creating autonomous systems whose values align with those of humans. Past work has shown that stories are a potentially rich source of information on human values; however, past work has been limited to considering valu
Externí odkaz:
http://arxiv.org/abs/2212.06048
As more machine learning agents interact with humans, it is increasingly a prospect that an agent trained to perform a task optimally, using only a measure of task performance as feedback, can violate societal norms for acceptable behavior or cause h
Externí odkaz:
http://arxiv.org/abs/2104.09469
Interactive reinforcement learning agents use human feedback or instruction to help them learn in complex environments. Often, this feedback comes in the form of a discrete signal that is either positive or negative. While informative, this informati
Externí odkaz:
http://arxiv.org/abs/2104.01506
In this work, we propose a deep neural architecture that uses an attention mechanism which utilizes region based image features, the natural language question asked, and semantic knowledge extracted from the regions of an image to produce open-ended
Externí odkaz:
http://arxiv.org/abs/2004.10966
Value alignment is a property of an intelligent agent indicating that it can only pursue goals and activities that are beneficial to humans. Traditional approaches to value alignment use imitation learning or preference learning to infer the values o
Externí odkaz:
http://arxiv.org/abs/1912.03553
One of the primary challenges of visual storytelling is developing techniques that can maintain the context of the story over long event sequences to generate human-like stories. In this paper, we propose a hierarchical deep learning architecture bas
Externí odkaz:
http://arxiv.org/abs/1909.12401