Tootfinder

White House says TikTok's new US entity would lease a copy of the algorithm from ByteDance, which Oracle would retrain; users won't need to re-download the app (Axios)
https://www.axios.com/2025/09/22/tiktok-bytedance-trump-algorithm-lease

Inside Trump's deal to save TikTok
TikTok's new U.S. entity would lease its algorithm from Chinese owner ByteDance.

KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems
Stjepan Po\v{z}gaj, Dobrik Georgiev, Marin \v{S}ili\'c, Petar Veli\v{c}kovi\'c
https://arxiv.org/abs/2509.15239

KNARsack: Teaching Neural Algorithmic Reasoners to Solve Pseudo-Polynomial Problems
Neural algorithmic reasoning (NAR) is a growing field that aims to embed algorithmic logic into neural networks by imitating classical algorithms. In this extended abstract, we detail our attempt to build a neural algorithmic reasoner that can solve Knapsack, a pseudo-polynomial problem bridging classical algorithms and combinatorial optimisation, but omitted in standard NAR benchmarks. Our neural algorithmic reasoner is designed to closely follow the two-phase pipeline for the Knapsack problem…

White House says TikTok's new US entity would lease a copy of ByteDance's algorithm, which Oracle would retrain; US users wouldn't need to re-download the app (Axios)
https://www.axios.com/2025/09/22/tiktok-bytedance-trump-algorithm-lease

Inside Trump's deal to save TikTok
TikTok's new U.S. entity would lease its algorithm from Chinese owner ByteDance.

Tiktok USA soll separaten Algorithmus und andere Eigentümer bekommen
Mögliche chinesische Einflussnahme soll bei Tiktok USA durch mögliche US-Einflussnahme ersetzt werden. Das Weiße Haus wird konkreter.

Good article, regardless your opinion about GenAI , it will change society.
#ai

The Third Algorithm
ChatGPT and other generative AI isn't about to create superintelligence, but even if what we see now is it, the impact is on the scale of Google search and algorithmic social media, except maybe worse

Bridging Research Gaps Between Academic Research and Legal Investigations of Algorithmic Discrimination
Colleen V. Chien, Anna Zink, Irene Y. Chen
https://arxiv.org/abs/2508.14954

Bridging Research Gaps Between Academic Research and Legal Investigations of Algorithmic Discrimination
As algorithms increasingly take on critical roles in high-stakes areas such as credit scoring, housing, and employment, civil enforcement actions have emerged as a powerful tool for countering potential discrimination. These legal actions increasingly draw on algorithmic fairness research to inform questions such as how to define and detect algorithmic discrimination. However, current algorithmic fairness research, while theoretically rigorous, often fails to address the practical needs of lega…

Neural Architecture Search Algorithms for Quantum Autoencoders
Ankit Kulshrestha, Xiaoyuan Liu, Hayato Ushijima-Mwesigwa, Ilya Safro
https://arxiv.org/abs/2509.15451 https://

Neural Architecture Search Algorithms for Quantum Autoencoders
The design of quantum circuits is currently driven by the specific objectives of the quantum algorithm in question. This approach thus relies on a significant manual effort by the quantum algorithm designer to design an appropriate circuit for the task. However this approach cannot scale to more complex quantum algorithms in the future without exponentially increasing the circuit design effort and introducing unwanted inductive biases. Motivated by this observation, we propose to automate the p…

Distributed Nash Equilibrium Seeking Algorithm in Aggregative Games for Heterogeneous Multi-Robot Systems
Yi Dong, Zhongguo Li, Sarvapali D. Ramchurn, Xiaowei Huang
https://arxiv.org/abs/2509.15597

Distributed Nash Equilibrium Seeking Algorithm in Aggregative Games for Heterogeneous Multi-Robot Systems
This paper develops a distributed Nash Equilibrium seeking algorithm for heterogeneous multi-robot systems. The algorithm utilises distributed optimisation and output control to achieve the Nash equilibrium by leveraging information shared among neighbouring robots. Specifically, we propose a distributed optimisation algorithm that calculates the Nash equilibrium as a tailored reference for each robot and designs output control laws for heterogeneous multi-robot systems to track it in an aggreg…

"Whoever needs to see it, will see it": Motivations and Labor of Creating Algorithmic Conspirituality Content on TikTok
Ankolika De, Kelley Cotter, Shaheen Kanthawala, Haley McAtee, Amy Ritchart, Gahana Kadur
https://arxiv.org/abs/2506.16851

"Whoever needs to see it, will see it": Motivations and Labor of Creating Algorithmic Conspirituality Content on TikTok
Recent studies show that users often interpret social media algorithms as mystical or spiritual because of their unpredictability. This invites new questions about how such perceptions affect the content that creators create and the communities they form online. In this study, 14 creators of algorithmic conspirituality content on TikTok were interviewed to explore their interpretations and creation processes influenced by the platform's For You Page algorithm. We illustrate how creators' belief…

Strategy Improvement, the Simplex Algorithm and Lopsidedness
Matthew Maat
https://arxiv.org/abs/2509.16075 https://arxiv.org/pdf/2509.16075

Strategy Improvement, the Simplex Algorithm and Lopsidedness
The strategy improvement algorithm for mean payoff games and parity games is a local improvement algorithm, just like the simplex algorithm for linear programs. Their similarity has turned out very useful: many lower bounds on running time for the simplex method have been created from lower bounds for strategy improvement. However, earlier connections between these algorithms required constructing an intermediate Markov decision process, which is not always possible. We prove a formal, direct c…