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of 23
pro vyhledávání: '"Lam, Michelle S."'
Autor:
Lam, Michelle S., Hohman, Fred, Moritz, Dominik, Bigham, Jeffrey P., Holstein, Kenneth, Kery, Mary Beth
Whether a large language model policy is an explicit constitution or an implicit reward model, it is challenging to assess coverage over the unbounded set of real-world situations that a policy must contend with. We introduce an AI policy design proc
Externí odkaz:
http://arxiv.org/abs/2409.18203
Data analysts have long sought to turn unstructured text data into meaningful concepts. Though common, topic modeling and clustering focus on lower-level keywords and require significant interpretative work. We introduce concept induction, a computat
Externí odkaz:
http://arxiv.org/abs/2404.12259
The standard way to teach models is by feeding them lots of data. However, this approach often teaches models incorrect ideas because they pick up on misleading signals in the data. To prevent such misconceptions, we must necessarily provide addition
Externí odkaz:
http://arxiv.org/abs/2402.03715
Autor:
Grunde-McLaughlin, Madeleine, Lam, Michelle S., Krishna, Ranjay, Weld, Daniel S., Heer, Jeffrey
LLM chains enable complex tasks by decomposing work into a sequence of subtasks. Similarly, the more established techniques of crowdsourcing workflows decompose complex tasks into smaller tasks for human crowdworkers. Chains address LLM errors analog
Externí odkaz:
http://arxiv.org/abs/2312.11681
Autor:
Lam, Michelle S., Pandit, Ayush, Kalicki, Colin H., Gupta, Rachit, Sahoo, Poonam, Metaxa, Danaë
Algorithm audits are powerful tools for studying black-box systems. While very effective in examining technical components, the method stops short of a sociotechnical frame, which would also consider users as an integral and dynamic part of the syste
Externí odkaz:
http://arxiv.org/abs/2308.15768
Publikováno v:
Proceedings of the ACM: Human-Computer Interaction, 8, CSCW1, Article 163 (2024)
Can we design artificial intelligence (AI) systems that rank our social media feeds to consider democratic values such as mitigating partisan animosity as part of their objective functions? We introduce a method for translating established, vetted so
Externí odkaz:
http://arxiv.org/abs/2307.13912
Autor:
Lam, Michelle S., Ma, Zixian, Li, Anne, Freitas, Izequiel, Wang, Dakuo, Landay, James A., Bernstein, Michael S.
Machine learning practitioners often end up tunneling on low-level technical details like model architectures and performance metrics. Could early model development instead focus on high-level questions of which factors a model ought to pay attention
Externí odkaz:
http://arxiv.org/abs/2303.02884
Autor:
Gordon, Mitchell L., Lam, Michelle S., Park, Joon Sung, Patel, Kayur, Hancock, Jeffrey T., Hashimoto, Tatsunori, Bernstein, Michael S.
Whose labels should a machine learning (ML) algorithm learn to emulate? For ML tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, different groups in society may have irreconcilable disagreements about ground
Externí odkaz:
http://arxiv.org/abs/2202.02950
Expert crowdsourcing marketplaces have untapped potential to empower workers' career and skill development. Currently, many workers cannot afford to invest the time and sacrifice the earnings required to learn a new skill, and a lack of experience ma
Externí odkaz:
http://arxiv.org/abs/1602.06634
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