Tootfinder

FCPO: Federated Continual Policy Optimization for Real-Time High-Throughput Edge Video Analytics
Lucas Liebe, Thanh-Tung Nguyen, Dongman Lee
https://arxiv.org/abs/2507.18047 htt…

FCPO: Federated Continual Policy Optimization for Real-Time High-Throughput Edge Video Analytics
The growing complexity of Edge Video Analytics (EVA) facilitates new kind of intelligent applications, but creates challenges in real-time inference serving systems. State-of-the-art (SOTA) scheduling systems optimize global workload distributions for heterogeneous devices but often suffer from extended scheduling cycles, leading to sub-optimal processing in rapidly changing Edge environments. Local Reinforcement Learning (RL) enables quick adjustments between cycles but faces scalability, know…

Just six months after he regained power, in part by promising to rapidly reduce prices, Trump has presided over the chaotic rollout of tariffs on an array of overseas products that many have argued risk having the exact opposite effect.
After a lull, the consumer price index (CPI) is back on the rise. In June, everything from fruit and washing machines to dresses and toys became more expensive.
Businesses in the US and around the world have struggled to keep up with the Trump adm…

Great! No need to worry about tech companies manipulating us with AI — they can just hook us up to neurotech and manipulate us directly. W00t! *
Why EU Policy Must Catch Up to the Neurotechnology Boom https://techpolicy.press/why-eu-policy-must-cat…

Why EU Policy Must Catch Up to the Neurotechnology Boom | TechPolicy.Press
Neurotechnology that can read and interpret brain activity is rapidly entering the mainstream market with no regulatory oversight, writes Virginia Mahieu.

AI is changing the world rapidly, and we are still only at the beginning.
So the fact that #ElonMusk is trying to teach his #AI to parrot conspiracy theories is a scandal.
The fact that he doesn't seem to be able to is wonderful news.

This https://arxiv.org/abs/2501.14380 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Verifying Fault-Tolerance of Quantum Error Correction Codes
Quantum computers have advanced rapidly in qubit count and gate fidelity. However, large-scale fault-tolerant quantum computing still relies on quantum error correction code (QECC) to suppress noise. Manually or experimentally verifying the fault-tolerance property of complex QECC implementation is impractical due to the vast error combinations. This paper formalizes the fault-tolerance of QECC implementations within the language of quantum programs. By incorporating the techniques of quantum s…

Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Mohammad Ali Alomrani, Yingxue Zhang, Derek Li, Qianyi Sun, Soumyasundar Pal, Zhanguang Zhang, Yaochen Hu, Rohan Deepak Ajwani, Antonios Valkanas, Raika Karimi, Peng Cheng, Yunzhou Wang, Pengyi Liao, Hanrui Huang, Bin Wang, Jianye Hao, Mark Coates
https://

Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoning: they apply fixed inference-time compute regardless of task complexity, often overthinking simple problems while underthinking hard ones. This survey presents a comprehensive review of efficient test-time compute (TTC) strategies, which aim to improve the computational efficiency of LLM reasoning. We introduce a tw…

Computer Science Education in the Age of Generative AI
Russell Beale
https://arxiv.org/abs/2507.02183 https://arxiv.org/pdf/2507.0218…

Computer Science Education in the Age of Generative AI
Generative AI tools - most notably large language models (LLMs) like ChatGPT and Codex - are rapidly revolutionizing computer science education. These tools can generate, debug, and explain code, thereby transforming the landscape of programming instruction. This paper examines the profound opportunities that AI offers for enhancing computer science education in general, from coding assistance to fostering innovative pedagogical practices and streamlining assessments. At the same time, it highl…

Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
Roopkatha Banerjee, Prince Modi, Jinal Vyas, Chunduru Sri Abhijit, Tejus Chandrashekar, Harsha Varun Marisetty, Manik Gupta, Yogesh Simmhan
https://arxiv.org/abs/2507.02295

Flotilla: A scalable, modular and resilient federated learning framework for heterogeneous resources
With the recent improvements in mobile and edge computing and rising concerns of data privacy, Federated Learning(FL) has rapidly gained popularity as a privacy-preserving, distributed machine learning methodology. Several FL frameworks have been built for testing novel FL strategies. However, most focus on validating the learning aspects of FL through pseudo-distributed simulation but not for deploying on real edge hardware in a distributed manner to meaningfully evaluate the federated aspects…

Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing
Yanran Wu, Inez Hua, Yi Ding
https://arxiv.org/abs/2506.22773 …

Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing
Water consumption is an increasingly critical dimension of computing sustainability, especially as AI workloads rapidly scale. However, current water impact assessment often overlooks where and when water stress is more severe. To fill in this gap, we present SCARF, the first general framework that evaluates water impact of computing by factoring in both spatial and temporal variations in water stress. SCARF calculates an Adjusted Water Impact (AWI) metric that considers both consumption volume…