Highest Rated Papers
Homeland Empire • EQUATOR
Unknown Author
equator.org·2025
From Venezuela to Minnesota, Trump is creating a borderless American power, collapsing the foreign and the domestic into a single domain of impunity
★ 5.0 (1)
View paper →The Macroeconomist as Scientist and Engineer
N. Gregory Mankiw
Journal of Economic Perspectives·2006·209 citations
<jats:p> The subfield of macroeconomics was born, not as a science, but more as a type of engineering. The problem that gave birth to our field was the Great Depression. God put macroeconomists on earth not to propose and test elegant theories but to solve practical problems. This essay offers a brief history of macroeconomics, together with an evaluation of what we have learned. My premise is that the field has evolved through the efforts of two types of macroeconomists—those who understand the field as a type of engineering and those who would like it to be more of a science. While the early macroeconomists were engineers trying to solve practical problems, the macroeconomists of the past several decades have been more interested in developing analytic tools and establishing theoretical principles. These tools and principles, however, have been slow to find their way into applications. As the field of macroeconomics has evolved, one recurrent theme has been the interaction—sometimes productive and sometimes not— between the scientists and the engineers. John Maynard Keynes (1931) famously opined, “If economists could manage to get themselves thought of as humble, competent people on a level with dentists, that would be splendid.” As we look ahead, “humble” and “competent” remain ideals toward which macroeconomists can aspire. </jats:p>
★ 5.0 (1)
View paper →A blueprint for formalizing the regularity of cographic matroids in Lean4
Cameron Rampell
GitHub·2025
No abstract available
★ 5.0 (1)
View paper →The Problem With Treating VO₂max as a Longevity Score
Chris Masterjohn, PhD
Substack·2025
What the research actually shows about oxygen uptake, treadmill performance, and lifespan.
★ 5.0 (1)
View paper →Is Having a Boyfriend Embarrassing Now? | Vogue
Chanté Joseph
Vogue·2025
“Being partnered doesn’t affirm your womanhood anymore,” writes Chanté Joseph. “It is no longer considered an achievement and, if anything, it’s become more of a flex to pronounce yourself single.”
★ 5.0 (1)
View paper →Self-driving cars aren’t nearly a solved problem
Yarrow Bouchard
Substack·2025
Contrary to popular belief, Waymos aren't actually fully autonomous, and the problem is harder than it may seem
★ 5.0 (1)
View paper →Sick of Doomscrolling? Join This New Research Paper Collective Instead
Kathryn Palmer
Inside Higher Ed | Higher Education News, Events and Jobs·2025
A fresh college graduate who now works as a machine learning engineer recently launched a website designed to make reading and sharing research more fun and accessible. Anuja Uppuluri used to spend a lot of time scrolling social media apps dictated by algorithms designed to keep users glued to their screens no matter how mind-numbing the content. “I always had something else that I could be doing or wanted to be doing, but I was choosing to watch TikTok videos for five hours,” said Uppuluri, who completed a bachelor’s degree in information systems at Carnegie Mellon University in May. “And then by the end of it I couldn't remember anything that I had watched.”
★ 5.0 (1)
View paper →The Costs of Housing Regulation: Evidence From Generative Regulatory Measurement
Alexander Bartik, Arpit Gupta, Daniel Milo
SSRN Electronic Journal·2023·3 citations
No abstract available
★ 5.0 (1)
View paper →Residential Rent Controls - An Evaluation
Anthony Downs
ULI-the Urban Land Institute·1998·1 citations
No abstract available
★ 5.0 (1)
View paper →The Lord of the Rings - Journal #148
Boris Groys
e-flux.com·2024
Boris Groys on the cosmic philosophy of Evald Ilyenkov.
★ 5.0 (1)
View paper →π0: A Vision-Language-Action Flow Model for General Robot Control
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Lucy Xiaoyang Shi, James Tanner, Quan Vuong, Anna Walling, Haohuan Wang, Ury Zhilinsky
Robot learning holds tremendous promise to unlock
the full potential of flexible, general, and dexterous robot systems,
as well as to address some of the deepest questions in artificial
intelligence. However, bringing robot learning to the level of
generality required for effective real-world systems faces major
obstacles in terms of data, generalization, and robustness. In
this paper, we discuss how generalist robot policies (i.e., robot
foundation models) can address these challenges, and how we can
design effective generalist robot policies for complex and highly
dexterous tasks. We propose a novel flow matching architecture built on top of a pre-trained vision-language model (VLM)
to inherit Internet-scale semantic knowledge. We then discuss
how this model can be trained on a large and diverse dataset
from multiple dexterous robot platforms, including single-arm
robots, dual-arm robots, and mobile manipulators. We evaluate
our model in terms of its ability to perform tasks via direct
prompting, follow language instructions from people and from a
high-level VLM policy, and its ability to acquire new skills via
fine-tuning. Our results cover a wide variety of tasks, such as
laundry folding, table cleaning, and assembling boxes.
★ 5.0 (1)
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