Tootfinder

Learning to Coordinate Bidders in Non-Truthful Auctions
Hu Fu, Tao Lin
https://arxiv.org/abs/2507.02801 https://arxiv.org/pdf/2507.02…

Learning to Coordinate Bidders in Non-Truthful Auctions
In non-truthful auctions such as first-price and all-pay auctions, the independent strategic behaviors of bidders, with the corresponding equilibrium notion -- Bayes Nash equilibria -- are notoriously difficult to characterize and can cause undesirable outcomes. An alternative approach to designing better auction systems is to coordinate the bidders: let a mediator make incentive-compatible recommendations of correlated bidding strategies to the bidders, namely, implementing a Bayes correlated …

@… yeah — tradeoffs!

This is a nice write-up of some complex and careful decisions and collaboration to navigate hard tradeoffs that in the end got the job done
I wish we also had more open discussions about the opposite scenario: "when the right tool is the wrong choice"
https://tern.sh/blog/pagerduty-cassadr

When the Wrong Tool is the Right Choice: PagerDuty's Cassandra Queue | Tern Blog
In 2011, PagerDuty was using MySQL as a queue. If you just winced, you understand the problem.

Misalignment or misuse? The AGI alignment tradeoff
Max Hellrigel-Holderbaum, Leonard Dung
https://arxiv.org/abs/2506.03755 https://ar…

Misalignment or misuse? The AGI alignment tradeoff
Creating systems that are aligned with our goals is seen as a leading approach to create safe and beneficial AI in both leading AI companies and the academic field of AI safety. We defend the view that misaligned AGI - future, generally intelligent (robotic) AI agents - poses catastrophic risks. At the same time, we support the view that aligned AGI creates a substantial risk of catastrophic misuse by humans. While both risks are severe and stand in tension with one another, we show that - in p…

Time and again, we have protested peacefully, spoken truthfully, and appealed to our shared humanity. We have been met with indifference, hostility, and violence. A leader who governs through hatred and greed is unfit to govern at all.

Improved Bounds on Access-Redundancy Tradeoffs in Quantized Linear Computations
Ching-Fang Li, Mary Wootters
https://arxiv.org/abs/2508.00183 https://arxiv…

Improved Bounds on Access-Redundancy Tradeoffs in Quantized Linear Computations
Consider the problem of computing quantized linear functions with only a few queries. Formally, given $\mathbf{x}\in \mathbb{R}^k$, our goal is to encode $\mathbf{x}$ as $\mathbf{c} \in \mathbb{R}^n$, for $n > k$, so that for any $\mathbf{w} \in A^k$, $\mathbf{w}^T \mathbf{x}$ can be computed using at most $\ell$ queries to $\mathbf{c}$. Here, $A$ is some finite set; in this paper we focus on the case where $|A| = 2$. Prior work \emph{(Ramkumar, Raviv, and Tamo, Trans. IT, 2024)} ha…

Hardware-Aware Data and Instruction Mapping for AI Tasks: Balancing Parallelism, I/O and Memory Tradeoffs
Md Rownak Hossain Chowdhury, Mostafizur Rahman
https://arxiv.org/abs/2509.03846

Hardware-Aware Data and Instruction Mapping for AI Tasks: Balancing Parallelism, I/O and Memory Tradeoffs
We introduce a mapping framework for deep learning inference that takes advantage of predictable neural network behavior to plan both computation and communication ahead of time. The framework generates a unified stream of instructions and data, enabling the hardware to execute operations and route information on its own, without frequent involvement from the host and with minimal off-chip memory use. This naturally reduces reliance on I/O, off-chip memory, and host control. By leveraging fine-…

#LB Eu estava sem saber o que pensar sobre essa história do humorista Leo Jardins. Embora não me restasse dúvidas de que se tratava de um humor escroto e que certas piadas ajudam a eternizar formas de preconceito, eu tendia a achar perigoso e complicado criminalizar o "rir de desgraças alheias" (mesmo sendo de minorias). Mas esse link me ajudou a entender um pouco melhor como a coisa é j…

Time For 9 o'clock #HashTagGames hosted by @… Let's play!
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This https://arxiv.org/abs/2505.13469 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Algorithmic Tradeoffs in Fair Lending: Profitability, Compliance, and Long-Term Impact
As financial institutions increasingly rely on machine learning models to automate lending decisions, concerns about algorithmic fairness have risen. This paper explores the tradeoff between enforcing fairness constraints (such as demographic parity or equal opportunity) and maximizing lender profitability. Through simulations on synthetic data that reflects real-world lending patterns, we quantify how different fairness interventions impact profit margins and default rates. Our results demonst…