Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Wong, Lionel"'
Autor:
Wong, Lionel Catherine
What do we understand when we understand language? Human language offers a broad window into the landscape of our thoughts. We talk about what we see, believe, and imagine, posing questions and communicating our plans. Language, in turn, stocks our m
Externí odkaz:
https://hdl.handle.net/1721.1/157326
How do people understand and evaluate claims about others' beliefs, even though these beliefs cannot be directly observed? In this paper, we introduce a cognitive model of epistemic language interpretation, grounded in Bayesian inferences about other
Externí odkaz:
http://arxiv.org/abs/2408.12022
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:
Jiang, Guangyuan, Hofer, Matthias, Mao, Jiayuan, Wong, Lionel, Tenenbaum, Joshua B., Levy, Roger P.
One hallmark of human language is its combinatoriality -- reusing a relatively small inventory of building blocks to create a far larger inventory of increasingly complex structures. In this paper, we explore the idea that combinatoriality in languag
Externí odkaz:
http://arxiv.org/abs/2405.06906
Despite the fact that beliefs are mental states that cannot be directly observed, humans talk about each others' beliefs on a regular basis, often using rich compositional language to describe what others think and know. What explains this capacity t
Externí odkaz:
http://arxiv.org/abs/2402.10416
Autor:
Wong, Lionel, Mao, Jiayuan, Sharma, Pratyusha, Siegel, Zachary S., Feng, Jiahai, Korneev, Noa, Tenenbaum, Joshua B., Andreas, Jacob
Effective planning in the real world requires not only world knowledge, but the ability to leverage that knowledge to build the right representation of the task at hand. Decades of hierarchical planning techniques have used domain-specific temporal a
Externí odkaz:
http://arxiv.org/abs/2312.08566
Autor:
Grand, Gabriel, Wong, Lionel, Bowers, Maddy, Olausson, Theo X., Liu, Muxin, Tenenbaum, Joshua B., Andreas, Jacob
While large language models (LLMs) now excel at code generation, a key aspect of software development is the art of refactoring: consolidating code into libraries of reusable and readable programs. In this paper, we introduce LILO, a neurosymbolic fr
Externí odkaz:
http://arxiv.org/abs/2310.19791
Autor:
Ying, Lance, Collins, Katherine M., Wei, Megan, Zhang, Cedegao E., Zhi-Xuan, Tan, Weller, Adrian, Tenenbaum, Joshua B., Wong, Lionel
Human beings are social creatures. We routinely reason about other agents, and a crucial component of this social reasoning is inferring people's goals as we learn about their actions. In many settings, we can perform intuitive but reliable goal infe
Externí odkaz:
http://arxiv.org/abs/2306.14325
Autor:
Wong, Lionel, Grand, Gabriel, Lew, Alexander K., Goodman, Noah D., Mansinghka, Vikash K., Andreas, Jacob, Tenenbaum, Joshua B.
How does language inform our downstream thinking? In particular, how do humans make meaning from language--and how can we leverage a theory of linguistic meaning to build machines that think in more human-like ways? In this paper, we propose rational
Externí odkaz:
http://arxiv.org/abs/2306.12672