Santa Barbara Police Department:
Please avoid the following intersections due to flooding:
-San Andres @ Canon Perdido Street
-00 Calle Cesar Chavez Street
-Shoreline Drive between Castillo and Loma Alta
Por favor, evite los siguientes cruces debido a las inundaciones:
-Calle San Andres con Calle Canon Perdido
-Calle Cesar Chavez (numero 00)
-Zona costera entre Castillo y Loma Alta
📣📣📣 LLM-powered coding mass-produces technical debt. 📣📣📣
The expectations around them are sky-high, but many organizations are falling behind because of them. 📉
WHY IT MATTERS? CTOs lament slowdowns and production issues traced to company-wide rollouts of LLM-powered coding assistants. The AI promise clashes with the reality of technical debt and security issues. 🐛
Read more:
I'm #ActuallyAutistic, and I love this woman deeply. I have been a huge fan of her music, especially my special interest in her song “Loin d’ici” (ESC Version) since May 14, 2016.
But now, watching Taylor Swift, Cœur de Pirate, and other artists slowly take her place feels like an unspoken farewell, like a song fading softly into the distance. It’s as if she herself is tell…
Robust forecast aggregation via additional queries
Rafael Frongillo, Mary Monroe, Eric Neyman, Bo Waggoner
https://arxiv.org/abs/2512.05271 https://arxiv.org/pdf/2512.05271 https://arxiv.org/html/2512.05271
arXiv:2512.05271v1 Announce Type: new
Abstract: We study the problem of robust forecast aggregation: combining expert forecasts with provable accuracy guarantees compared to the best possible aggregation of the underlying information. Prior work shows strong impossibility results, e.g. that even under natural assumptions, no aggregation of the experts' individual forecasts can outperform simply following a random expert (Neyman and Roughgarden, 2022).
In this paper, we introduce a more general framework that allows the principal to elicit richer information from experts through structured queries. Our framework ensures that experts will truthfully report their underlying beliefs, and also enables us to define notions of complexity over the difficulty of asking these queries. Under a general model of independent but overlapping expert signals, we show that optimal aggregation is achievable in the worst case with each complexity measure bounded above by the number of agents $n$. We further establish tight tradeoffs between accuracy and query complexity: aggregation error decreases linearly with the number of queries, and vanishes when the "order of reasoning" and number of agents relevant to a query is $\omega(\sqrt{n})$. These results demonstrate that modest extensions to the space of expert queries dramatically strengthen the power of robust forecast aggregation. We therefore expect that our new query framework will open up a fruitful line of research in this area.
toXiv_bot_toot
RED (Ocassionally) II 🔴
红 (有时) II 🔴
📷 Zeiss IKON Super Ikonta 533/16
🎞️ Harman Red 125 (6x6)
#filmphotography #Photography #blackandwhite
Series C, Episode 04 - Dawn of the Gods
AVON: We will do nothing to counter the force acting upon the Liberator. We then plot the Liberator's course on the main battle computer flight predictor to see exactly how she is behaving. Once we understand how the force is operating we may be some way toward defeating it.
TARRANT: Strange. The Liberator's following a curve. Traction beams produce straight-line motion. Zen, I want a prediction of the Liberator's course based …
RED (Ocassionally) 🔴
红 (有时) 🔴
📷 Zeiss IKON Super Ikonta 533/16
🎞️ Harman Red 125 (6x6)
#filmphotography #Photography #blackandwhite