arXiv preprints from January 1, 2026 through September 11, 2026 — 07:07:27 EST
Biological neurons combine excitatory and inhibitory (E/I) activity on branched dendrites through shunting, in which inhibition divisively attenuates excitation. Whether this improves population readout over additive E/I integration of the same nonnegative inputs remains unclear. We introduce DendriNet, a trainable framework that...
It has been proposed (Richerson and Boyd, 2008) that human intelligence is underpinned by a ratchet-like process called Cultural Evolution in which ideas, originated by individuals, can selectively spread by social learning and replace older, less fruitful ones. Useful ideas can thus accumulate beyond the lifetime of individuals....
Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD), widely regarded as a distributed network process; whether its signature reduces to a few focal sites has not been tested causally, a question central to targeted neuromodulation. We fit subject-specific, cross-subject-identifiable models whose...
This paper presents the General Theory of Relational Primacy (GTRP), a conceptual and formal framework for understanding stability, crisis, and transition in complex systems. The central thesis is that systems are not defined by their variables but by the relations that organize them. Variables are merely late manifestations of deep...
This note discusses zero-sum games with open-ended innovation, whereby each player may introduce new strategies. The innovation process is modelled as a draw of new strategies form a distribution. It is argued that, under generic conditions, this setting can lead to an everlasting innovation arm race, because the introduction of new...
We study how the similarity of individuals' information shapes collective action. When people draw on a common source of information, such as social media, each becomes more confident about what others have seen and will do. This can help them coordinate, but it can also tempt them to free-ride. We show that which force prevails...
This paper develops an inference procedure for average functionals of random-coefficient distributions, such as mean willingness-to-pay and average elasticities, when the distribution is estimated nonparametrically using the penalized fixed-grid estimator of Heiss, Hetzenecker, and Osterhaus (2022). We establish asymptotic normality...
Synthetic control (SC) matches a treated unit's pre-treatment trajectory to a weighted combination of donor units. We study Spectral SC, which instead matches the treated unit in coordinates defined by the leading temporal singular vectors of the donor panel, and a hybrid estimator that places separately tunable weight on retained and...
This paper studies the long-run alignment of interactive agents, including AI systems, teams, firms, and governments, with human welfare. It develops a farming game in which a population of agents makes planting, trading, and expansion decisions. Agents must allocate final output between transfers to humans and investment in their own...
Immediate Acceptance (IA, also known as the Boston mechanism) is commonly used to assign students to schools because it produces a Pareto-efficient matching if parents report their preferences over schools truthfully, unlike student-proposing Deferred Acceptance (DA). In this paper, we ask: does IA produce meaningfully better average...
We develop a general framework of identification and estimation for automatic debiased machine learning (DML) where the parameter of interest $θ_0$ is identified by a moment condition involving a nuisance $γ_0$ that may be high dimensional. DML leverages machine learning to estimate $γ_0$ while correcting for regularization and...
Market design research in economics naturally focusses on how to improve market efficiency. Our objective here is exactly the opposite - how to design interventions that make a market less efficient. Our research is inspired by the growth of illicit markets online where reducing their efficiency may reduce societal harm. Using a...
Large language models (LLMs) are increasingly used to generate data for research. Typical use cases are classifications, annotations, information extraction, and generation of numerical scores. Unlike conventional measurements, LLM outputs can vary across repeated requests even when the prompt and apparent model settings remain...
The Gini index remains the most important measure of economic inequality worldwide, and accurate estimates of this index are essential for effective public policies. Yet, Gini estimates for the same country and year vary considerably across data sources, a problem that remains largely unresolved. The paper reviews the largest global...
Causal inference is often focused on average effects, which can hide important aspects of the effect distributions. Here we consider the entire posterior effects distribution by estimating full counterfactual outcome distributions. We propose a methodology for inference on counterfactual distributions which builds upon the martingale...
This paper examines the tension between the benefits of generative artificial intelligence (AI) for scientific research and the unresolved governance questions that accompany its rapid adoption. Drawing on an academic roundtable held at the AI for Science and Innovation Workshop (Scuola IMT Alti Studi Lucca, April 2026) and on a...
It is obvious to say that an adequate estimation of the autocorrelation function is central in time series analysis. In this paper, we propose three new robust estimators based on ratios of observations, which offer strong resistance against outliers. While the first estimator, which is based on the median, is not efficient, the...
Firms struggle to choose AI projects that pay off: two projects can look equally promising to smart, motivated stakeholders and yet deserve opposite decisions. At the residential real-estate brokerage Compass, one AI product (Likely-to-Sell recommendations) flagged sales outreach opportunities and went on to account for nine figures...
I critique a set of entrenched methodological conventions that collectively create systemic dysfunction in statistical research for clinical decisions. These include: (1) the prevalent use of hypothesis tests to compare treatments, (2) remoteness from patient care of the methods used to evaluate the accuracy of predictions of patient...
Let $V$ and $U$ be independent standard normal random variables. For any Borel map $φ\colon\mathbb{R}\to\mathbb{R}$, set $Y_φ=φ(V)+U$, and define $P_φ(y)=\mathbb{E}[V\mid Y_φ=y]$ and $F_φ(x)=\mathbb{E}[P_φ(x+U)]$. We prove that, if for every $v\in\mathbb{R}$, the quantity $φ(v)$ maximises $x(v-F_φ(x))$ over $x\in\mathbb{R}$, then $φ$...
Firms covered by emissions trading systems need forecasts not only to value allowances, but also to decide when to buy them. This paper asks whether European Union Allowance (EUA) prices contain short-horizon predictability that survives a forecast-origin information design and improves simulated compliance procurement. Using daily...
A red herring, an irrelevant passage added to a problem, makes a language model reason incorrectly and answer incorrectly far more often. Yet the model still writes out a full explanation, and the answer it gives remains consistent with the steps it shows. The red herring corrupts the reasoning, while leaving the explanation intact...
Bitcoin price prediction on sub-daily timescales is a hard open problem in computational finance. Bitcoin exhibits fat-tailed returns, non-stationary dynamics, and a price discovery process influenced by social discourse on Reddit and Twitter. Conventional approaches fuse OHLCV technical features with sentiment via static...
We study whether strictly positive marginal values restore the compatibility of envy-freeness up to one good (EF1) and Pareto optimality (PO) for indivisible goods. For two agents, we identify the exact threshold in the number of goods. Every instance with at most seven goods and strictly increasing valuations admits an allocation...
When does the global game information structure select a unique equilibrium? Limit uniqueness in two-player supermodular games fails exactly when a risk-dominant better response cycle exists (Veiel, 2025). We show that rank-one factor structure on payoffs eliminates such cycles entirely, so every rank-one supermodular game admits a...