Highest Rated Papers
Unravelling the Probabilistic Forest: Arbitrage in Prediction Markets
Oriol Saguillo, Vahid Ghafouri, Lucianna Kiffer, Guillermo Suarez-Tangil
arXiv·2025
Polymarket is a prediction market platform where users can speculate on future events by trading shares tied to specific outcomes, known as conditions. Each market is associated with a set of one or more such conditions. To ensure proper market resolution, the condition set must be exhaustive -- collectively accounting for all possible outcomes -- and mutually exclusive -- only one condition may resolve as true. Thus, the collective prices of all related outcomes should be \$1, representing a combined probability of 1 of any outcome. Despite this design, Polymarket exhibits cases where dependent assets are mispriced, allowing for purchasing (or selling) a certain outcome for less than (or more than) \$1, guaranteeing profit. This phenomenon, known as arbitrage, could enable sophisticated participants to exploit such inconsistencies.
In this paper, we conduct an empirical arbitrage analysis on Polymarket data to answer three key questions: (Q1) What conditions give rise to arbitrage (Q2) Does arbitrage actually occur on Polymarket and (Q3) Has anyone exploited these opportunities. A major challenge in analyzing arbitrage between related markets lies in the scalability of comparisons across a large number of markets and conditions, with a naive analysis requiring $O(2^{n+m})$ comparisons. To overcome this, we employ a heuristic-driven reduction strategy based on timeliness, topical similarity, and combinatorial relationships, further validated by expert input.
Our study reveals two distinct forms of arbitrage on Polymarket: Market Rebalancing Arbitrage, which occurs within a single market or condition, and Combinatorial Arbitrage, which spans across multiple markets. We use on-chain historical order book data to analyze when these types of arbitrage opportunities have existed, and when they have been executed by users. We find a realized estimate of 40 million USD of profit extracted.
★ 4.0 (1)
View paper →Escape Artists - The Drift
The Drift 2026; Daniel Yadin
The Drift·2025
Romantasy at the End of the World
★ 4.0 (1)
View paper →The Wisdom of Deliberating AI Crowds: Does Deliberation Improve LLM-Based Forecasting?
Paul Schneider, Amalie Schramm
arXiv·2025
Structured deliberation has been found to improve the performance of human forecasters. This study investigates whether a similar intervention, i.e. allowing LLMs to review each other's forecasts before updating, can improve accuracy in large language models (GPT-5, Claude Sonnet 4.5, Gemini Pro 2.5). Using 202 resolved binary questions from the Metaculus Q2 2025 AI Forecasting Tournament, accuracy was assessed across four scenarios: (1) diverse models with distributed information, (2) diverse models with shared information, (3) homogeneous models with distributed information, and (4) homogeneous models with shared information. Results show that the intervention significantly improves accuracy in scenario (2), reducing Log Loss by 0.020 or about 4 percent in relative terms (p = 0.017). However, when homogeneous groups (three instances of the same model) engaged in the same process, no benefit was observed. Unexpectedly, providing LLMs with additional contextual information did not improve forecast accuracy, limiting our ability to study information pooling as a mechanism. Our findings suggest that deliberation may be a viable strategy for improving LLM forecasting.
★ 4.0 (1)
View paper →Capitalism’s Court Jester: Slavoj Žižek - CounterPunch.org
Gabriel Rockhill
CounterPunch.org·2023
No abstract available
★ 4.0 (1)
View paper →Feasibility and preliminary findings of the digital self-management program for people with schizophrenia in Indonesia
Sri Padma Sari, Faith Martin, Deborah Lycett, Andy Turner
ScienceDirect·2025
Background
Individuals with schizophrenia often experience self-management challenges due to the symptoms and mental health problems that impact the recovery process. Currently, digital interventions have shown potential effectiveness for people with schizophrenia in low- and middle-income countries. However, no such studies have been undertaken in Indonesia. We developed HOPE4Schizophrenia, a 6-week co-created digital self-management program. This study aimed to examine the feasibility of HOPE4Schizophrenia for people with schizophrenia.
Methods
A total of 35 participants enrolled in the intervention. The primary outcomes were to investigate recruitment rates, adherence rates, engagement rates, progression criteria, and participants’ satisfaction with the intervention. The secondary outcomes measured hope, recovery, and mental well-being at pre-, post-, and 3-month follow-up.
Results
The results showed that the recruitment, adherence, and engagement rates were high (50.7 %, 79 %, and 85 %, respectively). All the predetermined progression criteria were met. Most participants (90 %) reported that they found the course useful. There was a significant difference in recovery between pre-course and post-course and follow-up (F(2, 48) = 4.997, p = 0.011). There were no significant differences in hope and mental well-being at the three time points.
Conclusions
All progression criteria for a definitive trial were met, as supported by high recruitment, adherence, and engagement rates. While this study was not powered to detect effectiveness, preliminary findings indicated that HOPE4schizophrenia has the potential to support recovery in individuals with schizophrenia. This study presents a novel and promising finding for HOPE4schizophrenia. A future trial is needed to test the clinical effectiveness of this intervention.
★ 4.0 (1)
View paper →Trampantojos. Una crítica a Poder inquilino - Contracultura
Colaboraciones
Contracultura·2026
La RAE define “trampantojo” como “trampa o ilusión con la que se engaña a alguien haciéndole ver lo que no es”. En ese sentido, Poder Inquilino[1] es un trampantojo, donde el uso de cierta retórica y ciertos términos trata de generar una ilusión de radicalidad que oculte el reformismo de sus propuestas y horizontes. “Reformismo” es uno de esos términos manoseados que, a fuerza de usarse más como insulto que como concepto descriptivo con un significado preciso, en ocasiones genera un rechazo inmediato. Si no hubiese razones de peso para ello, quizá sería más prudente no usarlo. Por desgracia, las hay. El objetivo de este artículo es precisamente exponerlas, tratando de demostrar una afirmación tan contundente con el rigor adecuado. Pero antes de entrar de lleno en ello, como quizá no todo el mundo que lea este artículo ha leído el libro, un poco de contexto.
★ 4.0 (1)
View paper →Current challenges to the concept of sustainability
Markus Vogt, Christoph Weber
Global Sustainability·2019·64 citations
Non-technical summaryIn this paper we discuss current challenges to the sustainability concept. This article focuses on seven dimensions of the concept. These dimensions are crucial for understanding sustainability. Even today, the literature contains basic misunderstandings about these seven dimensions. This article sketches such fallacies in the context of global and planetary sustainability. The sustainability concept has been criticized as a content-empty ‘fuzzy notion’ or non-committal ‘all-purpose glue’. This article thus has a critical intention of reflecting the sustainability concept accurately. The aim is to contribute a better understanding of the concept.
★ 4.0 (1)
View paper →How Gen Z is fighting back against digital brain rot | National Geographic
Dana Binfet
National Geographic·2025
From analog hobbies to tech curfews, these Gen Zers are experimenting with science-backed ways to help their brains feel a little less foggy.
★ 3.8 (4)
View paper →How to make the best of the most important century?
Holden Karnofsky
Cold Takes·2021
We, the people living in this century, have the chance to have a huge impact on huge numbers of people to come - if we can make sense of the situation enough to find helpful actions.
★ 3.5 (2)
View paper →A proposal to classify happiness as a psychiatric disorder - PMC
R P Bentall
pmc.ncbi.nlm.nih.gov
It is proposed that happiness be classified as a psychiatric disorder and be included in future editions of the major diagnostic manuals under the new name: major affective disorder, pleasant type. In a review of the relevant literature it is shown ...
★ 3.5 (2)
View paper →5 Practices to Deepen Your Journaling in the New Year
Jillian Hess
Substack·2025
"a man loves to review his own mind"
★ 3.5 (6)
View paper →AI-Augmented Predictions: LLM Assistants Improve Human Forecasting Accuracy
Philipp Schoenegger, Peter S. Park, Ezra Karger, Sean Trott, Philip E. Tetlock
arXiv·2024
Large language models (LLMs) match and sometimes exceeding human performance in many domains. This study explores the potential of LLMs to augment human judgement in a forecasting task. We evaluate the effect on human forecasters of two LLM assistants: one designed to provide high-quality ("superforecasting") advice, and the other designed to be overconfident and base-rate neglecting, thus providing noisy forecasting advice. We compare participants using these assistants to a control group that received a less advanced model that did not provide numerical predictions or engaged in explicit discussion of predictions. Participants (N = 991) answered a set of six forecasting questions and had the option to consult their assigned LLM assistant throughout. Our preregistered analyses show that interacting with each of our frontier LLM assistants significantly enhances prediction accuracy by between 24 percent and 28 percent compared to the control group. Exploratory analyses showed a pronounced outlier effect in one forecasting item, without which we find that the superforecasting assistant increased accuracy by 41 percent, compared with 29 percent for the noisy assistant. We further examine whether LLM forecasting augmentation disproportionately benefits less skilled forecasters, degrades the wisdom-of-the-crowd by reducing prediction diversity, or varies in effectiveness with question difficulty. Our data do not consistently support these hypotheses. Our results suggest that access to a frontier LLM assistant, even a noisy one, can be a helpful decision aid in cognitively demanding tasks compared to a less powerful model that does not provide specific forecasting advice. However, the effects of outliers suggest that further research into the robustness of this pattern is needed.
★ 3.0 (1)
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