Tootfinder

Glad to see this...
LibreQoS Bufferbloat Test
Some of my company (IWL) products can create bufferbloat situations, but testing how the end-point protocols react is a separate concern.
I've written in the past about the inadequacy of "speed test" tool and how things like "iperf" can easily be (and often are) mis-interpreted. (I'll add some links).

« Des coups de couteau » mortels : une touriste française soupçonnée d’avoir tué son époux et leur fille en Islande - Le Parisien
https://www.leparisien.fr/faits-divers/de…

« Des coups de couteau » mortels : une touriste française soupçonnée d’avoir tué son époux et leur fille en Islande
L’homme et sa fille ont été retrouvés morts dans un hôtel de luxe de la capitale Reykjavik ce samedi matin.

🇺🇦 #NowPlaying on BBCRadio3's #JazzRecordRequests
Leo Parker:
🎵 TCTB
#LeoParker
https://open.spotify.com/track/5LXldK8NPugehfksVoda0y

A retrospective on DISPEED -- Leveraging heterogeneity in a drone swarm for IDS execution
Vincent Lannurien, Cam\'elia Slimani, Louis Morge-Rollet, Laurent Lemarchand, David Espes, Fr\'ed\'eric Le Roy, Jalil Boukhobza
https://arxiv.org/abs/2506.11800

A retrospective on DISPEED -- Leveraging heterogeneity in a drone swarm for IDS execution
Swarms of drones are gaining more and more autonomy and efficiency during their missions. However, security threats can disrupt their missions' progression. To overcome this problem, Network Intrusion Detection Systems ((N)IDS) are promising solutions to detect malicious behavior on network traffic. However, modern NIDS rely on resource-hungry machine learning techniques, that can be difficult to deploy on a swarm of drones. The goal of the DISPEED project is to leverage the heterogeneity (exec…

Confidence-Based Self-Training for EMG-to-Speech: Leveraging Synthetic EMG for Robust Modeling
Xiaodan Chen, Xiaoxue Gao, Mathias Quoy, Alexandre Pitti, Nancy F. Chen
https://arxiv.org/abs/2506.11862

Confidence-Based Self-Training for EMG-to-Speech: Leveraging Synthetic EMG for Robust Modeling
Voiced Electromyography (EMG)-to-Speech (V-ETS) models reconstruct speech from muscle activity signals, facilitating applications such as neurolaryngologic diagnostics. Despite its potential, the advancement of V-ETS is hindered by a scarcity of paired EMG-speech data. To address this, we propose a novel Confidence-based Multi-Speaker Self-training (CoM2S) approach, along with a newly curated Libri-EMG dataset. This approach leverages synthetic EMG data generated by a pre-trained model, followe…

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Boris Ivanovic, Cristiano Saltori, Yurong You, Yan Wang, Wenjie Luo, Marco Pavone
https://arxiv.org/abs/2506.12251

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
Autoregressive Transformers are increasingly being deployed as end-to-end robot and autonomous vehicle (AV) policy architectures, owing to their scalability and potential to leverage internet-scale pretraining for generalization. Accordingly, tokenizing sensor data efficiently is paramount to ensuring the real-time feasibility of such architectures on embedded hardware. To this end, we present an efficient triplane-based multi-camera tokenization strategy that leverages recent advances in 3D ne…

Leveraging GPT-4 for Vulnerability-Witnessing Unit Test Generation
G\'abor Antal, D\'enes B\'an, Martin Isztin, Rudolf Ferenc, P\'eter Heged\H{u}s
https://arxiv.org/abs/2506.11559

Leveraging GPT-4 for Vulnerability-Witnessing Unit Test Generation
In the life-cycle of software development, testing plays a crucial role in quality assurance. Proper testing not only increases code coverage and prevents regressions but it can also ensure that any potential vulnerabilities in the software are identified and effectively fixed. However, creating such tests is a complex, resource-consuming manual process. To help developers and security experts, this paper explores the automatic unit test generation capability of one of the most widely used larg…

Krugman continues:
❝While there is a cadre of Trumpist true believers who will obey the Leader under any circumstances, most of those doing the dirty work of undermining democracy and the rule of law are cowards and opportunists. They’re willing to participate in the destruction of America as we know it because they believe that many others will do the same. As a result, they believe that they are unlikely to face any personal consequences for their actions and may even be rewarded for their lawbreaking.
And what of those who oppose Trumpism? While there are heroes willing to take a stand against tyranny whatever the personal cost, most anti-Trumpists are reluctant to stick their necks out unless they believe that they are part of a widespread resistance that will grant them some measure of safety in numbers.
In other words, the victory or defeat of competitive authoritarianism will depend to a large extent on which side ordinary people believe will win. If Trump looks unstoppable, resistance will wither away and democracy will be lost. On the other hand, if he appears weak and stymied, resistance will grow and — just maybe — American democracy will survive.❞
2/

on my way to the optional friday meeting of early arrivers to RetroNetConf, our small German-language meeting of various #retronetworking enthusiasts https://osmocom.org/projects/retronetw…

Leveraging Reference Documents for Zero-Shot Ranking via Large Language Models
Jieran Li, Xiuyuan Hu, Yang Zhao, Shengyao Zhuang, Hao Zhang
https://arxiv.org/abs/2506.11452

Leveraging Reference Documents for Zero-Shot Ranking via Large Language Models
Large Language Models (LLMs) have demonstrated exceptional performance in the task of text ranking for information retrieval. While Pointwise ranking approaches offer computational efficiency by scoring documents independently, they often yield biased relevance estimates due to the lack of inter-document comparisons. In contrast, Pairwise methods improve ranking accuracy by explicitly comparing document pairs, but suffer from substantial computational overhead with quadratic complexity ($O(n^2)…