Zobrazeno 1 - 10
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pro vyhledávání: '"Collins, Katherine A."'
Autor:
Qiu, Zeju, Liu, Weiyang, Feng, Haiwen, Liu, Zhen, Xiao, Tim Z., Collins, Katherine M., Tenenbaum, Joshua B., Weller, Adrian, Black, Michael J., Schölkopf, Bernhard
Assessing the capabilities of large language models (LLMs) is often challenging, in part, because it is hard to find tasks to which they have not been exposed during training. We take one step to address this challenge by turning to a new task: focus
Externí odkaz:
http://arxiv.org/abs/2408.08313
Autor:
Collins, Katherine M., Sucholutsky, Ilia, Bhatt, Umang, Chandra, Kartik, Wong, Lionel, Lee, Mina, Zhang, Cedegao E., Zhi-Xuan, Tan, Ho, Mark, Mansinghka, Vikash, Weller, Adrian, Tenenbaum, Joshua B., Griffiths, Thomas L.
What do we want from machine intelligence? We envision machines that are not just tools for thought, but partners in thought: reasonable, insightful, knowledgeable, reliable, and trustworthy systems that think with us. Current artificial intelligence
Externí odkaz:
http://arxiv.org/abs/2408.03943
We can evaluate features of problems and their potential solutions well before we can effectively solve them. When considering a game we have never played, for instance, we might infer whether it is likely to be challenging, fair, or fun simply from
Externí odkaz:
http://arxiv.org/abs/2407.14095
Autor:
Collins, Katherine M., Chen, Valerie, Sucholutsky, Ilia, Kirk, Hannah Rose, Sadek, Malak, Sargeant, Holli, Talwalkar, Ameet, Weller, Adrian, Bhatt, Umang
Language models are transforming the ways that their users engage with the world. Despite impressive capabilities, over-consumption of language model outputs risks propagating unchecked errors in the short-term and damaging human capabilities for cri
Externí odkaz:
http://arxiv.org/abs/2407.12804
Autor:
Collins, Katherine M., Kim, Najoung, Bitton, Yonatan, Rieser, Verena, Omidshafiei, Shayegan, Hu, Yushi, Chen, Sherol, Dutta, Senjuti, Chang, Minsuk, Lee, Kimin, Liang, Youwei, Evans, Georgina, Singla, Sahil, Li, Gang, Weller, Adrian, He, Junfeng, Ramachandran, Deepak, Dvijotham, Krishnamurthy Dj
Human feedback plays a critical role in learning and refining reward models for text-to-image generation, but the optimal form the feedback should take for learning an accurate reward function has not been conclusively established. This paper investi
Externí odkaz:
http://arxiv.org/abs/2406.16807
Autor:
Kapoor, Sanyam, Gruver, Nate, Roberts, Manley, Collins, Katherine, Pal, Arka, Bhatt, Umang, Weller, Adrian, Dooley, Samuel, Goldblum, Micah, Wilson, Andrew Gordon
When using large language models (LLMs) in high-stakes applications, we need to know when we can trust their predictions. Some works argue that prompting high-performance LLMs is sufficient to produce calibrated uncertainties, while others introduce
Externí odkaz:
http://arxiv.org/abs/2406.08391
Autor:
Sucholutsky, Ilia, Collins, Katherine M., Malaviya, Maya, Jacoby, Nori, Liu, Weiyang, Sumers, Theodore R., Korakakis, Michalis, Bhatt, Umang, Ho, Mark, Tenenbaum, Joshua B., Love, Brad, Pardos, Zachary A., Weller, Adrian, Griffiths, Thomas L.
A good teacher should not only be knowledgeable; but should be able to communicate in a way that the student understands -- to share the student's representation of the world. In this work, we integrate insights from machine teaching and pragmatic co
Externí odkaz:
http://arxiv.org/abs/2406.04302
Autor:
Dutta, Senjuti, Chen, Sherol, Mak, Sunny, Ahmad, Amnah, Collins, Katherine, Butryna, Alena, Ramachandran, Deepak, Dvijotham, Krishnamurthy, Pavlick, Ellie, Rajakumar, Ravi
Image generation models are poised to become ubiquitous in a range of applications. These models are often fine-tuned and evaluated using human quality judgments that assume a universal standard, failing to consider the subjectivity of such tasks. To
Externí odkaz:
http://arxiv.org/abs/2403.05576
Model explanations can be valuable for interpreting and debugging predictive models. We study a specific kind called Concept Explanations, where the goal is to interpret a model using human-understandable concepts. Although popular for their easy int
Externí odkaz:
http://arxiv.org/abs/2312.08063
Mathematics is one of the most powerful conceptual systems developed and used by the human species. Dreams of automated mathematicians have a storied history in artificial intelligence (AI). Rapid progress in AI, particularly propelled by advances in
Externí odkaz:
http://arxiv.org/abs/2310.13021