Zobrazeno 1 - 10
of 28 547
pro vyhledávání: '"Petty AS"'
Large language models are increasingly trained on corpora containing both natural language and non-linguistic data like source code. Aside from aiding programming-related tasks, anecdotal evidence suggests that including code in pretraining corpora m
Externí odkaz:
http://arxiv.org/abs/2409.04556
State-space models (SSMs) have emerged as a potential alternative architecture for building large language models (LLMs) compared to the previously ubiquitous transformer architecture. One theoretical weakness of transformers is that they cannot expr
Externí odkaz:
http://arxiv.org/abs/2404.08819
Autor:
Rein, David, Hou, Betty Li, Stickland, Asa Cooper, Petty, Jackson, Pang, Richard Yuanzhe, Dirani, Julien, Michael, Julian, Bowman, Samuel R.
We present GPQA, a challenging dataset of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry. We ensure that the questions are high-quality and extremely difficult: experts who have or are pursuing PhDs in the
Externí odkaz:
http://arxiv.org/abs/2311.12022
Autor:
Michael, Julian, Mahdi, Salsabila, Rein, David, Petty, Jackson, Dirani, Julien, Padmakumar, Vishakh, Bowman, Samuel R.
As AI systems are used to answer more difficult questions and potentially help create new knowledge, judging the truthfulness of their outputs becomes more difficult and more important. How can we supervise unreliable experts, which have access to th
Externí odkaz:
http://arxiv.org/abs/2311.08702
In-context learning (ICL) is now a common method for teaching large language models (LLMs) new tasks: given labeled examples in the input context, the LLM learns to perform the task without weight updates. Do models guided via ICL infer the underlyin
Externí odkaz:
http://arxiv.org/abs/2311.07811
Language models are typically evaluated on their success at predicting the distribution of specific words in specific contexts. Yet linguistic knowledge also encodes relationships between contexts, allowing inferences between word distributions. We i
Externí odkaz:
http://arxiv.org/abs/2311.04900
Autor:
Petty, Jackson, van Steenkiste, Sjoerd, Dasgupta, Ishita, Sha, Fei, Garrette, Dan, Linzen, Tal
To process novel sentences, language models (LMs) must generalize compositionally -- combine familiar elements in new ways. What aspects of a model's structure promote compositional generalization? Focusing on transformers, we test the hypothesis, mo
Externí odkaz:
http://arxiv.org/abs/2310.19956
Autor:
Jessica Mogk, Claire L. Allen, Carly E. Levitz, Kelsey Stefanik-Guizlo, Emily Bourcier, Melissa Trapp Petty, Paula Lozano
Publikováno v:
BMC Primary Care, Vol 25, Iss 1, Pp 1-10 (2024)
Abstract Background Practice facilitation (PF) is an evidence-based multicomponent in-person implementation strategy. COVID-19-related lockdowns caused many implementation initiatives to rapidly shift to virtual settings, but there is limited evidenc
Externí odkaz:
https://doaj.org/article/89679805ad8142f0af7ffadaf73d2526
One of the main challenges autonomous vehicles (AVs) will face is interacting with pedestrians, especially at unmarked midblock locations where the right-of-way is unspecified. This study investigates pedestrian crossing behavior given different road
Externí odkaz:
http://arxiv.org/abs/2303.17717
Interacting with pedestrians is challenging for Autonomous vehicles (AVs). This study evaluates how AV operations /associated signaling and roadway infrastructure affect pedestrian behavior in virtual reality. AVs were designed with different operati
Externí odkaz:
http://arxiv.org/abs/2303.15352