Tootfinder

Filing: OpenAI seeks to block a May 13 court order requiring it to preserve all ChatGPT logs, including deleted chats, arguing it poses a risk to users' privacy (Ashley Belanger/Ars Technica)
https://arstechnica.com/tech-policy/20

OpenAI slams court order to save all ChatGPT logs, including deleted chats
OpenAI defends privacy of hundreds of millions of ChatGPT users.

How urban scaling and resource distribution shape social welfare and migration dynamics
Bryce Morsky
https://arxiv.org/abs/2506.03384 https://

How urban scaling and resource distribution shape social welfare and migration dynamics
Many outputs of cities scale in universal ways, including infrastructure, crime, and economic activity. Through a mathematical model, this study investigates the interplay between such scaling laws in human organization and governmental allocations of resources, focusing on impacts to migration patterns and social welfare. We find that if superlinear scaling resources of cities -- such as economic and social activity -- are the primary drivers of city dwellers' utility, then cities tend to conv…

Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters
Elvis Rodrigues, Jacob Goldverg, Tevfik Kosar
https://arxiv.org/abs/2506.04117 http…

Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters
Inter-datacenter communication is a significant part of cloud operations and produces a substantial amount of carbon emissions for cloud data centers, where the environmental impact has already been a pressing issue. In this paper, we present a novel carbon-aware temporal data transfer scheduling framework, called LinTS, which promises to significantly reduce the carbon emission of data transfers between cloud data centers. LinTS produces a competitive transfer schedule and makes scaling decisi…

This https://arxiv.org/abs/2505.17155 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling
Large Reasoning Models (LRMs) demonstrate exceptional capability in tackling complex mathematical, logical, and coding tasks by leveraging extended Chain-of-Thought (CoT) reasoning. Test-time scaling methods, such as prolonging CoT with explicit token-level exploration, can push LRMs' accuracy boundaries, but they incur significant decoding overhead. A key inefficiency source is LRMs often generate redundant thinking CoTs, which demonstrate clear structured overthinking and underthinking patter…

This https://arxiv.org/abs/2505.16133 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation
Retrieval-Augmented Generation (RAG) encounters efficiency challenges when scaling to massive knowledge bases while preserving contextual relevance. We propose Hash-RAG, a framework that integrates deep hashing techniques with systematic optimizations to address these limitations. Our queries directly learn binary hash codes from knowledgebase code, eliminating intermediate feature extraction steps, and significantly reducing storage and computational overhead. Building upon this hash-based eff…

»Cyber-Vorhängeschlösser knacken – Warum Quantencomputer ein Problem für die #Verschlüsselung bedeuten:
#Kryptografen wünschen sich Verschlüsselungssysteme, die auch für die #Quantencomputer

Cyber-Vorhängeschlösser knacken: Warum Quantencomputer ein Problem für die Verschlüsselung bedeuten -
Kryptografen wünschen sich Verschlüsselungssysteme, die auch für die Quantencomputer von morgen unmöglich zu knacken sind. Doch der Erfolg eines chinesischen Forscherteams zeigt, wo der Haken liegt. Unser Vertrauen in die Online-Sicherheit gründet fest in der Mathematik. Doch angesichts von Meldungen wie dieser, scheint das jetzt zu bröckeln: Einem Team aus Shanghai um Wang Chao, wie […]

"Leben. Fritz ist 85 Jahre alt und ist aus Leipzig gekommen, wo er zu einem Leder-Fetisch-Club gehört. Dass es mehr und mehr kleine CSDs in Ostdeutschland gibt, hält er für ein gutes Zeichen, „dann ist man nur nicht alleine ein bunter Hund“. Viele seiner queeren Freunde seien weggestorben, seit der DDR-Zeit war Fritz nicht mehr in Wittenberg. „Solange ich noch laufen kann, werd’ ich auf CSDs fahren‘, sagt er.
Drei Schüler:innen sind elektrisiert von dem Umzug, sie wohnen nur weni…

"Leben. Fritz ist 85 Jahre alt und ist aus Leipzig gekommen, wo er zu einem Leder-Fetisch-Club gehört. Dass es mehr und mehr kleine CSDs in Ostdeutschland gibt, hält er für ein gutes Zeichen, „dann ist man nur nicht alleine ein bunter Hund“. Viele seiner queeren Freunde seien weggestorben, seit der DDR-Zeit war Fritz nicht mehr in Wittenberg. „Solange ich noch laufen kann, werd’ ich auf CSDs fahren‘, sagt er.
Drei Schüler:innen sind elektrisiert von dem Umzug, sie wohnen nur weni…

Scaling Laws of Quantum Information Lifetime in Monitored Quantum Dynamics
Bingzhi Zhang, Fangjun Hu, Runzhe Mo, Tianyang Chen, Hakan E. T\"ureci, Quntao Zhuang
https://arxiv.org/abs/2506.22755

Scaling Laws of Quantum Information Lifetime in Monitored Quantum Dynamics
Quantum information is typically fragile under measurement and environmental coupling. Remarkably, we find that its lifetime can scale exponentially with system size when the environment is continuously monitored via mid-circuit measurements -- regardless of bath size. Starting from a maximally entangled state with a reference, we analytically prove this exponential scaling for typical Haar random unitaries and confirm it through numerical simulations in both Haar-random and chaotic Hamiltonian…

Collaborative Multi-Agent Reinforcement Learning Approach for Elastic Cloud Resource Scaling
Bruce Fang, Danyi Gao
https://arxiv.org/abs/2507.00550 https:/…

Collaborative Multi-Agent Reinforcement Learning Approach for Elastic Cloud Resource Scaling
This paper addresses the challenges of rapid resource variation and highly uncertain task loads in cloud computing environments. It proposes an optimization method for elastic cloud resource scaling based on a multi-agent system. The method deploys multiple autonomous agents to perceive resource states in parallel and make local decisions. While maintaining the distributed nature of the system, it introduces a collaborative value function to achieve global coordination. This improves the respon…