Tootfinder

🌽 To get that perfect ear of corn, weather has to cooperate. But climate change is making it dicier
#corn

To get that perfect ear of corn, weather has to cooperate. But climate change is making it dicier
Robb Rynd and his brother grew up farming and wanted to do more of it outside their day jobs, so they went in together on what's now a little over 200 acres of corn, soybeans, wheat and sorghum. Last year was a good year, and Rynd said he enjoyed walking the fields with his kids to see how the corn was doing.

PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints
Yuanchun Guo, Bingyan Liu, Yulong Sha, Zhensheng Xian
https://arxiv.org/abs/2509.08750

PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints
Federating heterogeneous models on edge devices with diverse resource constraints has been a notable trend in recent years. Compared to traditional federated learning (FL) that assumes an identical model architecture to cooperate, model-heterogeneous FL is more practical and flexible since the model can be customized to satisfy the deployment requirement. Unfortunately, no prior work ever dives into the existing model-heterogeneous FL algorithms under the practical edge device constraints and p…

The biggest misnomer in cooperate speech is probably saying 'letting people go' like it's a bloody favour, when you just fire them
#cooperate #work

Tokyo-based Sakana AI details a new Monte Carlo tree search-based technique that lets multiple LLMs cooperate on a single task, outperforming individual models (Ben Dickson/VentureBeat)
https://venturebeat.com/ai/sakana-ais-

Sakana AI’s TreeQuest: Deploy multi-model teams that outperform individual LLMs by 30%
Sakana AI's new inference-time scaling technique uses Monte-Carlo Tree Search to orchestrate multiple LLMs to collaborate on complex tasks.

Interesting, letting AI models cooperate.
#ai #sakana

Sakana AI
Inference-Time Scaling and Collective Intelligence for Frontier AI

On vacation in Australia and out on a road trip to the Blue Mountains. Sadly the weather gods did not cooperate and it's been raining and foggy the whole day. So just hibernating in our Airbnb and hoping that tomorrow's weather forecast of cloudy but dry does hold.

X refuses to cooperate with French probe into algorithm bias
https://www.lemonde.fr/en/pixels/article/2025/07/21/x-refuses-to-cooperate-with-french-probe-into-algorithm-bias_6743577_13.html

Trump threatens to arrest Mamdani if he doesn't cooperate with ICE (Sareen Habeshian/Axios)
https://www.axios.com/2025/07/01/trump-mamdani-arrest-ice-immigration
http://www.memeorandum.com/250701/p86#a250701p86

Dilution, Diffusion and Symbiosis in Spatial Prisoner's Dilemma with Reinforcement Learning
Gustavo C. Mangold, Heitor C. M. Fernandes, Mendeli H. Vainstein
https://arxiv.org/abs/2507.02211

Dilution, Diffusion and Symbiosis in Spatial Prisoner's Dilemma with Reinforcement Learning
Recent studies in the spatial prisoner's dilemma games with reinforcement learning have shown that static agents can learn to cooperate through a diverse sort of mechanisms, including noise injection, different types of learning algorithms and neighbours' payoff knowledge.In this work, using an independent multi-agent Q-learning algorithm, we study the effects of dilution and mobility in the spatial version of the prisoner's dilemma. Within this setting, different possible actions for the algor…

Ice used Marriott chain to detain immigrants, despite hotel’s 2019 pledge not to cooperate | US immigration | The Guardian https://www.theguardian.com/us-news/2025/aug/19/ice-marriott-hotel-detentions

Interactions across multiple games: cooperation, corruption, and organizational design
Jonathan Bendor, Lukas Bolte, Nicole Immorlica, Matthew O. Jackson
https://arxiv.org/abs/2507.03030

Interactions across multiple games: cooperation, corruption, and organizational design
It is socially beneficial for teams to cooperate in some situations (``good games'') and not in others (``bad games;'' e.g., those that allow for corruption). A team's cooperation in any given game depends on expectations of cooperation in future iterations of both good and bad games. We identify when sustaining cooperation on good games necessitates cooperation on bad games. We then characterize how a designer should optimally assign workers to teams and teams to tasks that involve varying arr…

minPIC: Towards Optimal Power Allocation in Multi-User Interference Channels
Sagnik Bhattacharya, Abhiram Rao Gorle, John M. Cioffi
https://arxiv.org/abs/2509.02797 https://

minPIC: Towards Optimal Power Allocation in Multi-User Interference Channels
6G envisions massive cell-free networks with spatially nested multiple access (MAC) and broadcast (BC) channels without centralized coordination. This makes optimal resource allocation across power, subcarriers, and decoding orders crucial for interference channels (ICs), where neither transmitters nor receivers can cooperate. Current orthogonal multiple access (OMA) methods, as well as non-orthogonal (NOMA) and rate-splitting (RSMA) schemes, rely on fixed heuristics for interference management…

FastSet: Parallel Claim Settlement
Xiaohong Chen, Grigore Rosu
https://arxiv.org/abs/2506.23395 https://arxiv.org/pdf/2506.23395

FastSet: Parallel Claim Settlement
FastSet is an actor-based distributed protocol for decentralized finance and settlement, which is inspired from blockchains. Account holders cooperate by making claims, which can include payments, holding and transferring assets, accessing and updating shared data, medical records, digital identity, and mathematical theorems, among many others. The claims are signed by their owners and are broadcast to a decentralized network of validators, which validate and settle them. Validators replicate t…

Friend or Foe
Oleksandr Cherendichenko, Josephine Solowiej-Wedderburn, Laura M. Carroll, Eric Libby
https://arxiv.org/abs/2509.00123 https://arxiv.org/pdf/…

Friend or Foe
A fundamental challenge in microbial ecology is determining whether bacteria compete or cooperate in different environmental conditions. With recent advances in genome-scale metabolic models, we are now capable of simulating interactions between thousands of pairs of bacteria in thousands of different environmental settings at a scale infeasible experimentally. These approaches can generate tremendous amounts of data that can be exploited by state-of-the-art machine learning algorithms to uncov…

Intergroup cooperation and reputation for honesty in an OLG framework
Georgy Lukyanov, David Li
https://arxiv.org/abs/2509.04748 https://arxiv.org/pdf/2509…

Intergroup cooperation and reputation for honesty in an OLG framework
This paper studies an infinite-horizon framework in which two large populations of players are randomly matched to play a Prisoner's Dilemma. Each player lives for two consecutive periods: as a young player from one group, and then as an old player in the other group. Each population has a known fraction of honest types - individuals who always cooperate unless paired with a player who has been observed to defect against a cooperating partner in the past. Because such defections (i.e., breakdow…

Piezomagnetism-driven magnetoelectric coupling in altermagnetic multiferroic K3Cr2F7
Ying Zhou, Hui-Min Zhang, Cheng-Ao Ji, Hongjun Xiang, Shuai Dong, James M. Rondinelli, Xue-Zeng Lu
https://arxiv.org/abs/2508.13952

Piezomagnetism-driven magnetoelectric coupling in altermagnetic multiferroic K3Cr2F7
Ferroelectric control of altermagnetism in momentum space has been studied widely, while the control of magnetism in real space of altermagnets are still rare. We present a design rule to identify multiferroicity in n=2 Ruddlesden-Popper halides. Our results show that a Jahn-Teller distortion can cooperate with oxygen octahedral rotations to break inversion symmetry, which we demonstrate in K3Cr2F7 and cation-ordered KAg2Cu2Cl7, and leads to a ferrielectric-to-ferroelectric phase transition in …

Evolution of boundedly rational learning in games
Marta C. Couto, Fernando P. Santos, Christian Hilbe
https://arxiv.org/abs/2506.21498 https://

Evolution of boundedly rational learning in games
People make strategic decisions multiple times a day. We act strategically in negotiations, when we coordinate our actions with others, or when we choose with whom to cooperate. The resulting dynamics can be studied with evolutionary game theory. This framework explores how people adapt their decisions over time, in light of how effective their strategies have proven to be. A crucial quantity in respective models is the strength of selection. This quantity regulates how likely individuals switc…

Integrating Movable Antennas and Intelligent Reflecting Surfaces for Coverage Enhancement
Ying Gao, Qingqing Wu, Weidong Mei, Guangji Chen, Wen Chen, Ziyuan Zheng
https://arxiv.org/abs/2506.21375

Integrating Movable Antennas and Intelligent Reflecting Surfaces for Coverage Enhancement
This paper investigates an intelligent reflecting surface (IRS)-aided movable antenna (MA) system, where multiple IRSs cooperate with a multi-MA base station to extend wireless coverage to multiple designated target areas. The objective is to maximize the worst-case signal-to-noise ratio (SNR) across all locations within these areas through joint optimization of MA positions, IRS reflection coefficients, and transmit beamforming. To achieve this while balancing the performance-cost trade-off, w…

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
Senyao Li, Haozhao Wang, Wenchao Xu, Rui Zhang, Song Guo, Jingling Yuan, Xian Zhong, Tianwei Zhang, Ruixuan Li
https://arxiv.org/abs/2507.16731

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges
As large language models (LLMs) evolve, deploying them solely in the cloud or compressing them for edge devices has become inadequate due to concerns about latency, privacy, cost, and personalization. This survey explores a collaborative paradigm in which cloud-based LLMs and edge-deployed small language models (SLMs) cooperate across both inference and training. We present a unified taxonomy of edge-cloud collaboration strategies. For inference, we categorize approaches into task assignment, t…

Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement
Soheyb Ribouh, Osama Saleem, Mohamed Ababsa
https://arxiv.org/abs/2506.20597

Differential Transformer-driven 6G Physical Layer for Collaborative Perception Enhancement
The emergence of 6G wireless networks promises to revolutionize vehicular communications by enabling ultra-reliable, low-latency, and high-capacity data exchange. In this context, collaborative perception techniques, where multiple vehicles or infrastructure nodes cooperate to jointly receive and decode transmitted signals, aim to enhance reliability and spectral efficiency for Connected Autonomous Vehicle (CAV) applications. In this paper, we propose an end-to-end wireless neural receiver base…