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pro vyhledávání: '"Howe AT"'
Autor:
Phan, Trung V., Li, Shengkai, Howe, Benjamin, Amend, Sarah R., Pienta, Kenneth J., Brown, Joel S., Gatenby, Robert A., Frangakis, Constantine, Austin, Robert H., Keverkidis, Ioannis G.
With the oncologist acting as the ``game leader'', we employ a Stackelberg game-theoretic model involving multiple populations to study prostate cancer. We refine the drug dosing schedule using an empirical Bayes feed-forward analysis, based on clini
Externí odkaz:
http://arxiv.org/abs/2410.16005
Autonomous racing demands safe control of vehicles at their physical limits for extended periods of time, providing insights into advanced vehicle safety systems which increasingly rely on intervention provided by vehicle autonomy. Participation in t
Externí odkaz:
http://arxiv.org/abs/2410.00358
This paper presents a comprehensive study on the scalability challenges and opportunities in quantum communication networks, with the goal of determining parameters that impact networks most as well as the trends that appear when scaling networks. We
Externí odkaz:
http://arxiv.org/abs/2409.08416
We find that the cross-entropy loss curves of neural language models empirically adhere to a scaling law with learning rate (LR) annealing over training steps: $$L(s) = L_0 + A\cdot S_1^{-\alpha} - C\cdot S_2,$$ where $L(s)$ is the validation loss at
Externí odkaz:
http://arxiv.org/abs/2408.11029
This research introduces the Multilevel Embedding Association Test (ML-EAT), a method designed for interpretable and transparent measurement of intrinsic bias in language technologies. The ML-EAT addresses issues of ambiguity and difficulty in interp
Externí odkaz:
http://arxiv.org/abs/2408.01966
Popular and news media often portray teenagers with sensationalism, as both a risk to society and at risk from society. As AI begins to absorb some of the epistemic functions of traditional media, we study how teenagers in two countries speaking two
Externí odkaz:
http://arxiv.org/abs/2408.01961
Multimodal AI models capable of associating images and text hold promise for numerous domains, ranging from automated image captioning to accessibility applications for blind and low-vision users. However, uncertainty about bias has in some cases lim
Externí odkaz:
http://arxiv.org/abs/2408.01959
Equitable urban transportation applications require high-fidelity digital representations of the built environment: not just streets and sidewalks, but bike lanes, marked and unmarked crossings, curb ramps and cuts, obstructions, traffic signals, sig
Externí odkaz:
http://arxiv.org/abs/2408.00932
Autor:
Wen, Bingbing, Yao, Jihan, Feng, Shangbin, Xu, Chenjun, Tsvetkov, Yulia, Howe, Bill, Wang, Lucy Lu
Abstention, the refusal of large language models (LLMs) to provide an answer, is increasingly recognized for its potential to mitigate hallucinations and enhance safety in LLM systems. In this survey, we introduce a framework to examine abstention fr
Externí odkaz:
http://arxiv.org/abs/2407.18418
Autor:
Howe, Nikolaus, McKenzie, Ian, Hollinsworth, Oskar, Zajac, Michał, Tseng, Tom, Tucker, Aaron, Bacon, Pierre-Luc, Gleave, Adam
Language models exhibit scaling laws, whereby increasing model and dataset size yields predictable decreases in negative log likelihood, unlocking a dazzling array of capabilities. This phenomenon spurs many companies to train ever larger models in p
Externí odkaz:
http://arxiv.org/abs/2407.18213