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pro vyhledávání: '"Crothers, Evan"'
A common approach to quantifying neural text classifier interpretability is to calculate faithfulness metrics based on iteratively masking salient input tokens and measuring changes in the model prediction. We propose that this property is better des
Externí odkaz:
http://arxiv.org/abs/2308.06795
We apply a large multilingual language model (BLOOM-176B) in open-ended generation of Chinese song lyrics, and evaluate the resulting lyrics for coherence and creativity using human reviewers. We find that current computational metrics for evaluating
Externí odkaz:
http://arxiv.org/abs/2301.05402
Machine generated text is increasingly difficult to distinguish from human authored text. Powerful open-source models are freely available, and user-friendly tools that democratize access to generative models are proliferating. ChatGPT, which was rel
Externí odkaz:
http://arxiv.org/abs/2210.07321
The detection of computer-generated text is an area of rapidly increasing significance as nascent generative models allow for efficient creation of compelling human-like text, which may be abused for the purposes of spam, disinformation, phishing, or
Externí odkaz:
http://arxiv.org/abs/2203.07983
Autor:
Boukouvalas, Zois, Mallinson, Christine, Crothers, Evan, Japkowicz, Nathalie, Piplai, Aritran, Mittal, Sudip, Joshi, Anupam, Adalı, Tülay
Social media has become an important communication channel during high impact events, such as the COVID-19 pandemic. As misinformation in social media can rapidly spread, creating social unrest, curtailing the spread of misinformation during such eve
Externí odkaz:
http://arxiv.org/abs/2006.01284
Publikováno v:
2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), Pittsburgh, PA, USA, 2019, pp. 1-6
The detection of clandestine efforts to influence users in online communities is a challenging problem with significant active development. We demonstrate that features derived from the text of user comments are useful for identifying suspect activit
Externí odkaz:
http://arxiv.org/abs/1908.11030
Akademický článek
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Autor:
Parson, Edward, Lempert, Robert, Armstrong, Ben, Crothers, Evan, DeChant, Chad, Novelli, Nick
The potential societal impacts of artificial intelligence (AI) and related technologiesare so vast, they are often likened to those of past transformative technologicalchanges such as the industrial or agricultural revolutions. They are also deeplyun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::235f7d456fca986d5b990ab4a3289539
https://escholarship.org/uc/item/0xj3356j
https://escholarship.org/uc/item/0xj3356j
Autor:
Armstrong, Ben, Beretta, Megan, Crothers, Evan, Karlin, Michael, Kim, Dongwoo, Longo, Justin, Powell, Lorne, Sanders, Trooper
This workgroup considered whether the policy analysis function in government could be replaced by an artificial intelligence policy analyst (AIPA) that responds directly to requests for information and decision support from political and administrati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::26dc96575f8f652f474bf42fb725575e
https://escholarship.org/uc/item/95735485
https://escholarship.org/uc/item/95735485