Tootfinder

Towards Microgrid Resilience Enhancement via Mobile Power Sources and Repair Crews: A Multi-Agent Reinforcement Learning Approach
Yi Wang, Dawei Qiu, Fei Teng, Goran Strbac
https://arxiv.org/abs/2507.18095

Towards Microgrid Resilience Enhancement via Mobile Power Sources and Repair Crews: A Multi-Agent Reinforcement Learning Approach
Mobile power sources (MPSs) have been gradually deployed in microgrids as critical resources to coordinate with repair crews (RCs) towards resilience enhancement owing to their flexibility and mobility in handling the complex coupled power-transport systems. However, previous work solves the coordinated dispatch problem of MPSs and RCs in a centralized manner with the assumption that the communication network is still fully functioning after the event. However, there is growing evidence that ce…

Real-time deep learning phase imaging flow cytometer reveals blood cell aggregate biomarkers for haematology diagnostics
Kerem Delikoyun, Qianyu Chen, Liu Wei, Si Ko Myo, Johannes Krell, Martin Schlegel, Win Sen Kuan, John Tshon Yit Soong, Gerhard Schneider, Clarissa Prazeres da Costa, Percy A. Knolle, Laurent Renia, Matthew Edward Cove, Hwee Kuan Lee, Klaus Diepold, Oliver Hayden

Real-time deep learning phase imaging flow cytometer reveals blood cell aggregate biomarkers for haematology diagnostics
While analysing rare blood cell aggregates remains challenging in automated haematology, they could markedly advance label-free functional diagnostics. Conventional flow cytometers efficiently perform cell counting with leukocyte differentials but fail to identify aggregates with flagged results, requiring manual reviews. Quantitative phase imaging flow cytometry captures detailed aggregate morphologies, but clinical use is hampered by massive data storage and offline processing. Incorporating …

Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models
Xushuo Tang, Yi Ding, Zhengyi Yang, Yin Chen, Yongrui Gu, Wenke Yang, Mingchen Ju, Xin Cao, Yongfei Liu, Wenjie Zhang
https://arxiv.org/abs/2508.00788

Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models
Large language models (LLMs) are increasingly deployed in sensitive contexts where fairness and inclusivity are critical. Pronoun usage, especially concerning gender-neutral and neopronouns, remains a key challenge for responsible AI. Prior work, such as the MISGENDERED benchmark, revealed significant limitations in earlier LLMs' handling of inclusive pronouns, but was constrained to outdated models and limited evaluations. In this study, we introduce MISGENDERED+, an extended and updated bench…

deepSURF: Detecting Memory Safety Vulnerabilities in Rust Through Fuzzing LLM-Augmented Harnesses
Georgios Androutsopoulos, Antonio Bianchi
https://arxiv.org/abs/2506.15648

deepSURF: Detecting Memory Safety Vulnerabilities in Rust Through Fuzzing LLM-Augmented Harnesses
Although Rust ensures memory safety by default, it also permits the use of unsafe code, which can introduce memory safety vulnerabilities if misused. Unfortunately, existing tools for detecting memory bugs in Rust typically exhibit limited detection capabilities, inadequately handle Rust-specific types, or rely heavily on manual intervention. To address these limitations, we present deepSURF, a tool that integrates static analysis with Large Language Model (LLM)-guided fuzzing harness generat…

"Es ist höchste Zeit, dass sich deutsche Wissenschaftsinstitutionen nicht nur mit Solidaritätsbekundungen an die USA wenden, sondern sich auch gegen die wachsende Bedrohung für Wissenschaft und Demokratie in Deutschland positionieren."
"Überpolitisierung im Namen der Depolitisierung ist das Programm, mit dem die Wissenschaft nach rechtsextremer Façon umgeformt wird."
Andreas #FischerLescano

Wer die Wissenschaft schützen will, muss die AfD verbieten
Die Angriffe auf Universitäten in den USA sind ein Warnsignal. Während deutsche Forschungsorganisationen noch Solidaritätsbekundungen formulieren, bläst die AfD zu ihrem eigenen Feldzug gegen die freie Wissenschaft. Zeit zum Handeln. Ein Gastbeitrag von Andreas Fischer-Lescano.

Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices
Jiaqi Sun, Dingyu Yang, Shiyou Qian, Jian Cao, Guangtao Xue
https://arxiv.org/abs/2506.15523

Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices
To handle the high volume of requests, large-scale services are comprised of thousands of instances deployed in clouds. These services utilize diverse programming languages and are distributed across various nodes as encapsulated containers. Given their vast scale, even minor performance enhancements can lead to significant cost reductions. In this paper, we introduce Atys1, an efficient profiling framework specifically designed to identify hotspot functions within large-scale distributed servi…

IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
Shiwei Feng, Xiangzhe Xu, Xuan Chen, Kaiyuan Zhang, Syed Yusuf Ahmed, Zian Su, Mingwei Zheng, Xiangyu Zhang
https://arxiv.org/abs/2506.07524

IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
LLM agents are increasingly deployed to automate real-world tasks by invoking APIs through natural language instructions. While powerful, they often suffer from misinterpretation of user intent, leading to the agent's actions that diverge from the user's intended goal, especially as external toolkits evolve. Traditional software testing assumes structured inputs and thus falls short in handling the ambiguity of natural language. We introduce IntenTest, an API-centric stress testing framework th…

A Type System for Data Privacy Compliance in Active Object Languages
Chinmayi Prabhu Baramashetru (University of Oslo, Norway), Paola Giannini (Universita' del Piemonte Orientale, Italy), Silvia Lizeth Tapia Tarifa (University of Oslo, Norway), Olaf Owe (University of Oslo, Norway)
https://arxiv.org/abs/2508.03831

A Type System for Data Privacy Compliance in Active Object Languages
Data protection laws such as GDPR aim to give users unprecedented control over their personal data. Compliance with these regulations requires systematically considering information flow and interactions among entities handling sensitive data. Privacy-by-design principles advocate embedding data protection into system architectures as a default. However, translating these abstract principles into concrete, explicit methods remains a significant challenge. This paper addresses this gap by propos…

Nexus: Taming Throughput-Latency Tradeoff in LLM Serving via Efficient GPU Sharing
Xiaoxiang Shi, Colin Cai, Junjia Du, Zhanda Zhu, Xingda Wei, Zhihao Jia
https://arxiv.org/abs/2507.06608

Nexus: Taming Throughput-Latency Tradeoff in LLM Serving via Efficient GPU Sharing
Current prefill-decode (PD) disaggregation is typically deployed at the level of entire serving engines, assigning separate GPUs to handle prefill and decode phases. While effective at reducing latency, this approach demands more hardware. To improve GPU utilization, Chunked Prefill mixes prefill and decode requests within the same batch, but introduces phase interference between prefill and decode. While existing PD disaggregation solutions separate the phases across GPUs, we ask: can the sa…

In other news, I've sent a few fun patches to improve epytest in #Gentoo.
This includes forcing short summaries, creating junit .xml for machine processing, and most importantly, EPYTEST_PLUGINS to handle specifying the plugins to load. The goal is to eventually move away from plugin autoloading by default.
#PyTest #Python