Tootfinder

Ich finde die deutsche Feiertagsdiskussion irre, solange man nicht Tage, sondern Wochen mit irrsinniger Bürokratie aus dem Hause Schilda verbringt. Das deutsche Steuerrecht ist komplett krank, die Planfeststellungverfahren führen zum Totalstillstand. Im Ahrtal bauen sie wieder in die Flutgebiete weil der Flächentausch nicht gelingt. Aber einen Feiertag abschaffen für den journalistischen Clickbait. #Fail …

NDR (@NDR@ard.social)
Angehängt: 1 Bild Einen Tag weniger Pause – dafür aber mehr Einnahmen für den Staat? In Deutschland wird über die Abschaffung eines Feiertags diskutiert, in Dänemark ist das bereits passiert. Der Ökonom Marcel Fratzscher warnte davor, diesem Beispiel zu folgen: https://www.ndr.de/feiertag316.html

Jetzt ist auch noch die LIVE Zustellung bei DHL ausgefallen. Shit. Ich kriege eine Sendung, wo ich gegenzeichnen muss und sitze jetzt fest hier. Frisches Roggenbrot vom Bäcker adé.
#DHL #DHL_fail

Now that SCOTUS has crippled the ability of Federal judges to issue blanket injunctions against unconstitutional acts by the government we can anticipate that there have to be many, many, many more individual lawsuits, pretty much one suit per victim of a government policy.
I do hope that lawyers have begun to create a shared repository of text and research that can be updated and evolved as cases succeed or fail.
(Of course there will have to be limited access rights in order to…

Owning two Pixel phones running GrapheneOS made me both chuckle and tear up a little. It’s such an amazing operating system that I’m planning to start making monthly donations to support the project.
I had my Pixel 6a since early May 2023, but yesterday I upgraded to a Pixel 9a because the speakers and earpiece microphone on my 6a had started to fail badly, and the battery was showing its age.
I’m glad I made the upgrade, and now people can hear me clearly on the phone again.

Impeached Beached Fail
bot by @…
This is a joke, not a threat: let's not make entertainment lead to internment.
#satire #potus45

Tony Blair is (a) clearly a lich and (b) recently worked/works for a Saudi oil company. Weird that the guardian didn’t mention either in this article.

European Commission says Meta has proposed limited changes to its pay-or-consent ad model, and Meta faces daily fines if it determines they are not sufficient (Reuters)
https://economictimes.indiatimes.com/t

Meta will only make limited changes to pay-or-consent model, EU says
Meta Platforms made only limited changes to its pay-or-consent model, and EU regulators cannot confirm compliance with an antitrust order. The European Commission may impose periodic penalties starting June 27, if Meta continues to fail meeting the required standards.

Hahaha.
#fail
https://mastodon.social/@gwynnion/114740122636886432

Out of the Past: An AI-Enabled Pipeline for Traffic Simulation from Noisy, Multimodal Detector Data and Stakeholder Feedback
Rex Chen, Karen Wu, John McCartney, Norman Sadeh, Fei Fang
https://arxiv.org/abs/2505.21349

Out of the Past: An AI-Enabled Pipeline for Traffic Simulation from Noisy, Multimodal Detector Data and Stakeholder Feedback
How can a traffic simulation be designed to faithfully reflect real-world traffic conditions? Past data-driven approaches to traffic simulation in the literature have relied on unrealistic or suboptimal heuristics. They also fail to adequately account for the effects of uncertainty and multimodality in the data on simulation outcomes. In this work, we integrate advances in AI to construct a three-step, end-to-end pipeline for generating a traffic simulation from detector data: computer vision f…

"the operations at the two new Laguna Street sites will be contracted out which means they will no longer be eligible to work with their clients."
Somehow, I get the feeling that the great minds behind this project fail to understand the importance of community and trust.

S.F. plans to move mentally ill adults draws protest
If the city has its way, all 83 residents will be moved to two facilities on Laguna Street in Hayes Valley.

"the operations at the two new Laguna Street sites will be contracted out which means they will no longer be eligible to work with their clients."
Somehow, I get the feeling that the great minds behind this project fail to understand the importance of community and trust.

S.F. plans to move mentally ill adults draws protest
If the city has its way, all 83 residents will be moved to two facilities on Laguna Street in Hayes Valley.

Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning
Le Xu, Chenxing Li, Yong Ren, Yujie Chen, Yu Gu, Ruibo Fu, Shan Yang, Dong Yu
https://arxiv.org/abs/2505.22045

Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning
Current vision-guided audio captioning systems frequently fail to address audiovisual misalignment in real-world scenarios, such as dubbed content or off-screen sounds. To bridge this critical gap, we present an entropy-aware gated fusion framework that dynamically modulates visual information flow through cross-modal uncertainty quantification. Our novel approach employs attention entropy analysis in cross-attention layers to automatically identify and suppress misleading visual cues during mo…

Why does the #CBC consistently #fail to include hyperlinks or original documents in their #news #reporting?

Neural Face Skinning for Mesh-agnostic Facial Expression Cloning
Sihun Cha, Serin Yoon, Kwanggyoon Seo, Junyong Noh
https://arxiv.org/abs/2505.22416 https:…

Neural Face Skinning for Mesh-agnostic Facial Expression Cloning
Accurately retargeting facial expressions to a face mesh while enabling manipulation is a key challenge in facial animation retargeting. Recent deep-learning methods address this by encoding facial expressions into a global latent code, but they often fail to capture fine-grained details in local regions. While some methods improve local accuracy by transferring deformations locally, this often complicates overall control of the facial expression. To address this, we propose a method that combi…

This https://arxiv.org/abs/2403.06767 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Continuity and equivariant dimension
We study the local-triviality dimensions of actions on $C^*$-algebras, which are invariants developed for noncommutative Borsuk-Ulam theory. While finiteness of the local-triviality dimensions is known to guarantee freeness of an action, we show that free actions need not have finite weak local-triviality dimension. Moreover, the local-triviality dimensions of a continuous field may be greater than those of its individual fibers, and the dimensions may fail to vary continuously across the fiber…

DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View Diffusion
Yansong Qu, Shaohui Dai, Xinyang Li, Yuze Wang, You Shen, Liujuan Cao, Rongrong Ji
https://arxiv.org/abs/2506.21544

DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View Diffusion
Reconstructing 3D objects from a single image is a long-standing challenge, especially under real-world occlusions. While recent diffusion-based view synthesis models can generate consistent novel views from a single RGB image, they generally assume fully visible inputs and fail when parts of the object are occluded. This leads to inconsistent views and degraded 3D reconstruction quality. To overcome this limitation, we propose an end-to-end framework for occlusion-aware multi-view generation. …

Boosting Vulnerability Detection with Inter-function Multilateral Association Insights
Shaojian Qiu, Mengyang Huang, Jiahao Cheng
https://arxiv.org/abs/2506.21014

Boosting Vulnerability Detection with Inter-function Multilateral Association Insights
Vulnerability detection is a crucial yet challenging technique for ensuring the security of software systems. Currently, most deep learning-based vulnerability detection methods focus on stand-alone functions, neglecting the complex inter-function interrelations, particularly the multilateral associations. This oversight can fail to detect vulnerabilities in these interrelations. To address this gap, we present an Inter-Function Multilateral Association analysis framework for Vulnerability Dete…

Dave Solomon, CEO Good Machine (@ Sun Valley Forum)
"Venture funding isn't set up for most businesses to succeed. It's the wrong tool for climate, because we need the businesses in this space to work. We need financing tools that help 90% of companies succeed and 10% fail rather than the reverse."

Resilience Through Escalation: A Graph-Based PACE Architecture for Satellite Threat Response
Anouar Boumeftah, Sarah McKenzie-Picot, Peter Klimas, Gunes Karabulut Kurt
https://arxiv.org/abs/2506.20882

Resilience Through Escalation: A Graph-Based PACE Architecture for Satellite Threat Response
Satellite systems increasingly face operational risks from jamming, cyberattacks, and electromagnetic disruptions. Traditional redundancy strategies often fail against dynamic, multi-vector threats. This paper introduces a resilience-by-design framework grounded in the PACE (Primary, Alternate, Contingency, Emergency) methodology, originally developed for tactical communications in military operations, adapting it to satellite systems through a layered state-transition model informed by threat …

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Travis Thompson, Seung-Hwan Lim, Paul Liu, Ruoying He, Dongkuan Xu
https://arxiv.org/abs/2506.19967

Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs
Large Language Models (LLMs) have achieved impressive capabilities in language understanding and generation, yet they continue to underperform on knowledge-intensive reasoning tasks due to limited access to structured context and multi-hop information. Retrieval-Augmented Generation (RAG) partially mitigates this by grounding generation in retrieved context, but conventional RAG and GraphRAG methods often fail to capture relational structure across nodes in knowledge graphs. We introduce Infere…

Multicontinuum Homogenization for Poroelasticity Model
Dmitry Ammosov, Mohammed Al-Kobaisi, Yalchin Efendiev
https://arxiv.org/abs/2506.20890 https://

Multicontinuum Homogenization for Poroelasticity Model
In this paper, we derive multicontinuum poroelasticity models using the multicontinuum homogenization method. Poroelasticity models are widely used in many areas of science and engineering to describe coupled flow and mechanics processes in porous media. However, in many applications, the properties of poroelastic media possess high contrast, presenting serious computational challenges. It is well known that standard homogenization approaches often fail to give an accurate solution due to the l…

Autonomous Cyber Resilience via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox
Malikussaid, Sutiyo
https://arxiv.org/abs/2506.20102 h…

Autonomous Cyber Resilience via a Co-Evolutionary Arms Race within a Fortified Digital Twin Sandbox
The convergence of IT and OT has created hyper-connected ICS, exposing critical infrastructure to a new class of adaptive, intelligent adversaries that render static defenses obsolete. Existing security paradigms often fail to address a foundational "Trinity of Trust," comprising the fidelity of the system model, the integrity of synchronizing data, and the resilience of the analytical engine against sophisticated evasion. This paper introduces the ARC framework, a method for achieving analytic…

Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives
Brian Liu, Rahul Mazumder, Peter Radchenko
https://arxiv.org/abs/2506.20114

Extracting Interpretable Models from Tree Ensembles: Computational and Statistical Perspectives
Tree ensembles are non-parametric methods widely recognized for their accuracy and ability to capture complex interactions. While these models excel at prediction, they are difficult to interpret and may fail to uncover useful relationships in the data. We propose an estimator to extract compact sets of decision rules from tree ensembles. The extracted models are accurate and can be manually examined to reveal relationships between the predictors and the response. A key novelty of our estimator…

The Blind Spot of BGP Anomaly Detection: Why LSTM Autoencoders Fail on Real-World Outages
Samuel Oluwafemi Adebayo
https://arxiv.org/abs/2506.17821 https:/…

The Blind Spot of BGP Anomaly Detection: Why LSTM Autoencoders Fail on Real-World Outages
Deep learning has significant potential to make the Internet's Border Gateway Protocol (BGP) secure by detecting anomalous routing activity. However, all but a few of these approaches rely on the implicit assumption that anomalies manifest as noisy, high-complexity outliers from some normal baseline. This work challenges this assumption by investigating if a best-in-class detection model built on this assumption can effectively deal with real-world security events' diverse signatures. We employ…

I went downstairs, filled the kettle, waited for it boil, and poured the water into my mug.
I then popped back upstairs for 5 minutes to let it brew. Went back down to the kitchen, gave it a stir. "Hmm this looks a bit weak".
I'd only forgotten to put a bloody tea bag in the mug at the start of the exercise, hadn't I.
Obviously I have now contacted the government and arranged to hand in my British passport.
#Tea #FAIL

Proof of The TAP Free Energy for High-Dimensional Linear Regression with Spherical Priors at All Temperatures
Zhiyuan Yu, Jingbo Liu
https://arxiv.org/abs/2506.20768

Proof of The TAP Free Energy for High-Dimensional Linear Regression with Spherical Priors at All Temperatures
Variational inference (VI) has emerged as an efficient framework for approximating intractable posteriors. Traditional mean-field VI methods fail to capture the complex dependencies and can be inconsistent in high-dimensional settings. In contrast, it has been conjectured, based on statistical physics heuristics and conditions for the stationary points, that the more refined Thouless-Anderson-Palmer (TAP) approximation is consistent in the high-dimensional regimes. Existing results, however, ha…

Virginia Candidates Show You Can Try to Kill DEI, But You'll Fail (Jill Lawrence/The Bulwark)
https://www.thebulwark.com/p/virginia-candidates-dei-diversity-maga-racism
http://www.memeorandum.com/250623/p20#a250623p20

Current Galactic Chemical Evolution models fail to explain rising Na-abundances of young thick disc stars
E. K. Owusu (School of Science, University of New South Wales Canberra, Australia Defence Force Academy, Australia, ARC Centre of Excellence for All-Sky Astrophysics in 3 Dimensions, Max-Planck-Institut f\"ur Astronomie, Heidelberg, Germany, Heidelberger Institut f\"ur Theoretische Studien, Heidelberg, Germany), A. J. Ruiter (School of Science, University of New South Wal…

Current Galactic Chemical Evolution models fail to explain rising Na-abundances of young thick disc stars
We recently identified an upturn in [Na/Fe] for the population of Solar-type stars in the Galactic thick disc ($-0.3 < [\mathrm{Fe/H}] < +0.3$ dex) at super-Solar metallicity in GALactic Archaeology with HERMES (GALAH) data. Here, we investigate the cause of this unexplained Na enrichment between ([Fe/H] $\sim 0 - 0.6$ dex) using the OMEGA$+$ galactic chemical evolution code. We investigate the increase of [Na/Fe] with four combinations of nucleosynthetic yields from the literature, with source…

#NixOS driving me nuts right now. Keeps rebuilding coreutils for aarch64-linux when building for my RPi (but it's definitely in the cache, so it has to be some obscure special version deep down), it takes ONE.FRICKING.HOUR just for it to fail on ONE 'test-free' (qemu: uncught target signal 11 (Segmentation fault) - core dumped). 😠
Also, I can't override what I don't find, w…

'"[…] Suppose you compile an #eBPF program on #kernel version 5.3, but it fails to run on 5.4.
Why? Because each kernel version ships with its own kernel headers, which define structs and memory layouts. […]
So if a certain struct field […] sits at a different offset in another OS or ke…

DiT-SGCR: Directed Temporal Structural Representation with Global-Cluster Awareness for Ethereum Malicious Account Detection
Ye Tian, Liangliang Song, Peng Qian, Yanbin Wang, Jianguo Sun, Yifan Jia
https://arxiv.org/abs/2506.20123

DiT-SGCR: Directed Temporal Structural Representation with Global-Cluster Awareness for Ethereum Malicious Account Detection
The detection of malicious accounts on Ethereum - the preeminent DeFi platform - is critical for protecting digital assets and maintaining trust in decentralized finance. Recent advances highlight that temporal transaction evolution reveals more attack signatures than static graphs. However, current methods either fail to model continuous transaction dynamics or incur high computational costs that limit scalability to large-scale transaction networks. Furthermore, current methods fail to consid…

Cowboys appear to have a plan should Tyler Guyton fail to develop https://insidethestar.com/cowboys-appear-to-have-a-plan-should-tyler-guyton-fail-to-develop

Efficient Strategy Synthesis for MDPs via Hierarchical Block Decomposition
Alexandros Evangelidis, Gricel V\'azquez, Simos Gerasimou
https://arxiv.org/abs/2506.17792

Efficient Strategy Synthesis for MDPs via Hierarchical Block Decomposition
Software-intensive systems, such as software product lines and robotics, utilise Markov decision processes (MDPs) to capture uncertainty and analyse sequential decision-making problems. Despite the usefulness of conventional policy synthesis methods, they fail to scale to large state spaces. Our approach addresses this issue and accelerates policy synthesis in large MDPs by dynamically refining the MDP and iteratively selecting the most fragile MDP regions for refinement. This iterative procedu…

Higher co-dimension de Sitter branes
Florian Niedermann, Antonio Padilla
https://arxiv.org/abs/2506.19515 https://arxiv.org/pdf/2506.…

Higher co-dimension de Sitter branes
We extend the arguments of Maldacena and Núñez to include higher co-dimension brane setups and derive a new no-go theorem. Specifically, we show that under reasonable assumptions on the energy-momentum conservation and the bulk curvature, co-dimension-two branes fail to support stable de Sitter solutions. For co-dimensions higher than two embedded in a compact internal space, we show that negative tension sources would be required. This result places strong constraints on the viability of hig…

ReCoGNet: Recurrent Context-Guided Network for 3D MRI Prostate Segmentation
Ahmad Mustafa, Reza Rastegar, Ghassan AlRegib
https://arxiv.org/abs/2506.19687 …

ReCoGNet: Recurrent Context-Guided Network for 3D MRI Prostate Segmentation
Prostate gland segmentation from T2-weighted MRI is a critical yet challenging task in clinical prostate cancer assessment. While deep learning-based methods have significantly advanced automated segmentation, most conventional approaches-particularly 2D convolutional neural networks (CNNs)-fail to leverage inter-slice anatomical continuity, limiting their accuracy and robustness. Fully 3D models offer improved spatial coherence but require large amounts of annotated data, which is often imprac…

Higher-Order Graph Databases
Maciej Besta, Shriram Chandran, Jakub Cudak, Patrick Iff, Marcin Copik, Robert Gerstenberger, Tomasz Szydlo, J\"urgen M\"uller, Torsten Hoefler
https://arxiv.org/abs/2506.19661

Higher-Order Graph Databases
Recent advances in graph databases (GDBs) have been driving interest in large-scale analytics, yet current systems fail to support higher-order (HO) interactions beyond first-order (one-hop) relations, which are crucial for tasks such as subgraph counting, polyadic modeling, and HO graph learning. We address this by introducing a new class of systems, higher-order graph databases (HO-GDBs) that use lifting and lowering paradigms to seamlessly extend traditional GDBs with HO. We provide a theore…

Radar and Event Camera Fusion for Agile Robot Ego-Motion Estimation
Yang Lyu, Zhenghao Zou, Yanfeng Li, Chunhui Zhao, Quan Pan
https://arxiv.org/abs/2506.18443

Radar and Event Camera Fusion for Agile Robot Ego-Motion Estimation
Achieving reliable ego motion estimation for agile robots, e.g., aerobatic aircraft, remains challenging because most robot sensors fail to respond timely and clearly to highly dynamic robot motions, often resulting in measurement blurring, distortion, and delays. In this paper, we propose an IMU-free and feature-association-free framework to achieve aggressive ego-motion velocity estimation of a robot platform in highly dynamic scenarios by combining two types of exteroceptive sensors, an even…

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park, Jini Kim, Jodi Forlizzi, Kenneth Holstein, John Zimmerman
https://arxiv.org/abs/2506.17494

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with ind…

Technical recommendation on multiplex MR elastography for tomographic mapping of abdominal stiffness with a focus on the pancreas and pancreatic ductal adenocarcinoma
Jakob Schattenfroh, Salma Almutawakel, Jan Bieling, Johannes Castelein, Melanie Estrella, Philippe Garteiser, Viktor Hartung, Karl H. Hillebrandt, Adrian T. Huber, Laura K\"orner, Thomas Kr\"oncke, Thomas Malinka, Hans-Jonas Meyer, Tom Meyer, Uwe Pelzer, Felix Pfister, Igor M. Sauer, Anna Speth, Bernard E. Van B…

Technical recommendation on multiplex MR elastography for tomographic mapping of abdominal stiffness with a focus on the pancreas and pancreatic ductal adenocarcinoma
Objectives: MR elastography (MRE) offers valuable mechanical tissue characterization, however, in deep abdominal organs like the pancreas conventional single-driver, single-frequency approaches often fail. This study evaluates whether multiplex MRE using multiple drivers and vibration frequencies can overcome these limitations. Methods: This study used single-shot spin-echo MRE in 18 healthy volunteers targeting the liver, pancreas, kidneys, and spleen. Each healthy volunteer underwent 16 MRE…

I Tried Pre-Ordering the Trump Phone. The Page Failed and It Charged My Credit Card the Wrong Amount https://www.404media.co/trump-mobile-phone-preorder-fail/

Finished Hollow Fires by Samira Ahmed last night. It's gripping, sad, and fierce all at the same time. Explores themes of racism, Islamophobia, white supremacist terrorism, and police malcompetence in an extremely timely manner. It's a good book, which I'm extra happy about since I also liked Ahmed's This Book Won't Burn, so now I have another author whose work I'll be reading through.
Including Sabaa Tahir, Sabina Khan, and Adiba Jaigirdar, I've been reading a ton of great YA books by south Asian muslim authors recently, all discovered via the "grab something off the YA shelf by a probably-not-white author" method that has yet to fail me. Turns out the racism in publishing that puts a higher bar in front of authors of color at least makes it easy to find good books in one way >:(
#AmReading

Foreign students will be required to unlock their social media profiles
to allow US diplomats to review their online activity
before receiving educational and exchange visas, the state department has announced.
Those who fail to do so will be suspected of hiding that activity from US officials.
The new guidance, unveiled by the state department on Wednesday, directs US diplomats to conduct an online presence review to look for
“any indications of hostility towa…

Fault Tolerance by Construction
Benjamin Rodatz, Boldizs\'ar Po\'or, Aleks Kissinger
https://arxiv.org/abs/2506.17181 https://

Fault Tolerance by Construction
A key challenge in fault-tolerant quantum computing is synthesising and optimising circuits in a noisy environment, as traditional techniques often fail to account for the effect of noise on circuits. In this work, we propose a framework for designing fault-tolerant quantum circuits that are correct by construction. The framework starts with idealised specifications of fault-tolerant gadgets and refines them using provably sound basic transformations. To reason about manipulating circuits whi…

Ach stimmt. #Klimatransformationsfonds kann auch gelesen werden als Fonds der das Klima transformiert. 🧐
@… das ist ja nicht zu glauben!

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant
Akash Awasthi, Brandon V. Chang, Anh M. Vu, Ngan Le, Rishi Agrawal, Zhigang Deng, Carol Wu, Hien Van Nguyen
https://arxiv.org/abs/2506.17320

MAARTA:Multi-Agentic Adaptive Radiology Teaching Assistant
Radiology students often struggle to develop perceptual expertise due to limited expert mentorship time, leading to errors in visual search and diagnostic interpretation. These perceptual errors, such as missed fixations, short dwell times, or misinterpretations, are not adequately addressed by current AI systems, which focus on diagnostic accuracy but fail to explain how and why errors occur. To address this gap, we introduce MAARTA (Multi-Agentic Adaptive Radiology Teaching Assistant), a mult…

I do fail to notice the challenges that other are facing.
And I am sure acknowledging them is not moving the needle even a bit.
What can we do? https://c.im/@bercut2000/114709553384266626

Not what it seems ...
#blogging

Automating Financial Statement Audits with Large Language Models
Rushi Wang, Jiateng Liu, Weijie Zhao, Shenglan Li, Denghui Zhang
https://arxiv.org/abs/2506.17282

Automating Financial Statement Audits with Large Language Models
Financial statement auditing is essential for stakeholders to understand a company's financial health, yet current manual processes are inefficient and error-prone. Even with extensive verification procedures, auditors frequently miss errors, leading to inaccurate financial statements that fail to meet stakeholder expectations for transparency and reliability. To this end, we harness large language models (LLMs) to automate financial statement auditing and rigorously assess their capabilities, …

🇺🇦 Auf #radioeins läuft...
When Saints Go Machine:
🎵 Fail Forever
#NowPlaying #WhenSaintsGoMachine
https://when-saints-go-machine.bandcamp.com/album/fail-forever
https://open.spotify.com/track/6zIpXfRuASVRcRF2YFyTnE

Frequency-Weighted Training Losses for Phoneme-Level DNN-based Speech Enhancement
Nasser-Eddine Monir, Paul Magron, Romain Serizel
https://arxiv.org/abs/2506.18714

Frequency-Weighted Training Losses for Phoneme-Level DNN-based Speech Enhancement
Recent advances in deep learning have significantly improved multichannel speech enhancement algorithms, yet conventional training loss functions such as the scale-invariant signal-to-distortion ratio (SDR) may fail to preserve fine-grained spectral cues essential for phoneme intelligibility. In this work, we propose perceptually-informed variants of the SDR loss, formulated in the time-frequency domain and modulated by frequency-dependent weighting schemes. These weights are designed to emphas…

Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS
Sabrine Ennaji, Elhadj Benkhelifa, Luigi V. Mancini
https://arxiv.org/abs/2506.20576

Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS
Adversarial attacks, wherein slight inputs are carefully crafted to mislead intelligent models, have attracted increasing attention. However, a critical gap persists between theoretical advancements and practical application, particularly in structured data like network traffic, where interdependent features complicate effective adversarial manipulations. Moreover, ambiguity in current approaches restricts reproducibility and limits progress in this field. Hence, existing defenses often fail to…

https://kolektiva.social/@susurros/114701605671238735
""A couple of unmarked vehicles were here trying to take day laborers," described Teodoro, adding that some day laborers, who are U.S. citizens, distracted the ICE agents, giving undocumented fri…

Scott Campbell (@susurros@kolektiva.social)
Attached: 1 image Well done, Inland Empire! "A group of immigrant [sic] agents Monday tried to detain undocumented day laborers at a Home Depot store parking lot in the Inland Empire until community members intervened, according to witnesses and a nonprofit." https://www.nbclosangeles.com/news/local/ice-agents-fail-to-detain-day-laborers-at-upland-home-depot-after-bystanders-intervene/ #California #Upland #InlandEmpire #immigration #ICE

Triadic Novelty: A Typology and Measurement Framework for Recognizing Novel Contributions in Science
Jin Ai, Richard S. Steinberg, Chao Guo, Filipi Nascimento Silva
https://arxiv.org/abs/2506.17851

Triadic Novelty: A Typology and Measurement Framework for Recognizing Novel Contributions in Science
Scientific progress depends on novel ideas, but current reward systems often fail to recognize them. Many existing metrics conflate novelty with popularity, privileging ideas that fit existing paradigms over those that challenge them. This study develops a theory-driven framework to better understand how different types of novelty emerge, take hold, and receive recognition. Drawing on network science and theories of discovery, we introduce a triadic typology: Pioneers, who introduce entirely ne…

On Designing Modulation for Over-the-Air Computation -- Part I: Noise-Aware Design
Saeed Razavikia, Carlo Fischione
https://arxiv.org/abs/2506.15950 https:…

On Designing Modulation for Over-the-Air Computation -- Part I: Noise-Aware Design
Over-the-air computation (OAC) leverages the physical superposition property of wireless multiple access channels (MACs) to compute functions while communication occurs, enabling scalable and low-latency processing in distributed networks. While analog OAC methods suffer from noise sensitivity and hardware constraints, existing digital approaches are often limited in design complexity, which may hinder scalability and fail to exploit spectral efficiency fully. This two-part paper revisits and e…

"Despite good-faith efforts by DSI [dense street imagery] providers to protect individual privacy through blurring faces and license plates, these measures fail to address broader privacy concerns. In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from supposedly anonymized data."
via @…

Privacy of Groups in Dense Street Imagery
Spatially and temporally dense street imagery (DSI) datasets have grown unbounded. In 2024, individual companies possessed around 3 trillion unique images of public streets. DSI data streams are only set to grow as companies like Lyft and Waymo use DSI to train autonomous vehicle algorithms and analyze collisions. Academic researchers leverage DSI to explore novel approaches to urban analysis. Despite good-faith efforts by DSI providers to protect individual privacy through blurring faces and l…

Weak null singularity for the Einstein-Euler system
Yuefeng Song
https://arxiv.org/abs/2506.16635 https://arxiv.org/pdf/2506.16635

Weak null singularity for the Einstein-Euler system
We study the behavior of a self-gravitating perfect relativistic fluid satisfying the Einstein-Euler system in the presence of a weak null terminal spacetime singularity. This type of singularities is expected in the interior of generic dynamical black holes. In the vacuum case, weak null singularities have been constructed locally by Luk, where the metrics extend continuously to the singularities while the Christoffel symbols fail to be square integrable in any neighborhood of any point on the…

Replaced article(s) found for physics.geo-ph. https://arxiv.org/list/physics.geo-ph/new
[1/1]:
- When Cubic Law and Darcy Fail: Bayesian Correction of Model Misspecification in Fracture Conducti...
Sarah Perez, Florian Doster, Julien Maes, Hannah Menke, Ahmed ElS…

Some thoughts on bluesky, gift article on WaPo. #Fediverse happily sails under the radar here. Slow and steady wins the race, is what I'm thinking. Seems Megan McArdle thinks staying on X is a viable strategy.
https://wapo.st/4mXOdBb

Loss functions incorporating auditory spatial perception in deep learning -- a review
Boaz Rafaely, Stefan Weinzierl, Or Berebi, Fabian Brinkmann
https://arxiv.org/abs/2506.19404 …

Loss functions incorporating auditory spatial perception in deep learning -- a review
Binaural reproduction aims to deliver immersive spatial audio with high perceptual realism over headphones. Loss functions play a central role in optimizing and evaluating algorithms that generate binaural signals. However, traditional signal-related difference measures often fail to capture the perceptual properties that are essential to spatial audio quality. This review paper surveys recent loss functions that incorporate spatial perception cues relevant to binaural reproduction. It focuses …

The EU says Apple and Meta will not face sanctions immediately after their 60 day DMA grace period ends on June 26, following €500M and €200M fines in April (Peggy Corlin/Euronews)
https://www.euronews.com/my-europe/2025/06…

Apple and Meta to escape sanctions for failing to meet digital rules
The European Commission will opt not to impose immediate financial penalties on Apple and Meta—even if they fail to comply with the legislation by next week's deadline. #EuropeNews

A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction
Chengjie Liu, Weiyu Chen, Huiyao Xu, Yuan Du, Jun Yang, Li Du
https://arxiv.org/abs/2506.18424

A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction
In the design process of the analog circuit pre-layout phase, device sizing is an important step in determining whether an analog circuit can meet the required performance metrics. Many existing techniques extract the circuit sizing task as a mathematical optimization problem to solve and continuously improve the optimization efficiency from a mathematical perspective. But they ignore the automatic introduction of prior knowledge, fail to achieve effective pruning of the search space, which the…

Vulnerability of electrical systems to total blackouts is not just a result of high penetration of renewables. The opposite applies in La Palma, Canarias, as in Cuba, when old thermal power plants fail. In La Palma, renewables have the lowest share (11%) of all Spain's islands.
Por qué los apagones se ceban con La Palma: un sistema aislado y una central térmica de hace medio siglo

Por qué los apagones se ceban con La Palma: un sistema aislado y una central térmica de hace medio siglo
La isla cuenta con una red eléctrica que depende en gran parte de una sola estación con varios grupos muy antiguos. Cuando esta sufre un problema, las posibilidades de un corte total del suministro se multiplican

4/4 📊 Visible failure tracking in #Horizon, #Telescope, or your #APM for better debugging and monitoring of failed jobs.

LLMs fail at old video games because LLMs don't think, they just regurgitate pre-ingested information, and older video games (and some new ones) have so much chaos and unpredictability baked in that you can't navigate them simply by regurgitating things.
#OldGames #RetroGaming

Is Your Automated Software Engineer Trustworthy?
Noble Saji Mathews, Meiyappan Nagappan
https://arxiv.org/abs/2506.17812 https://arxi…

Is Your Automated Software Engineer Trustworthy?
Large Language Models (LLMs) are being increasingly used in software engineering tasks, with an increased focus on bug report resolution over the past year. However, most proposed systems fail to properly handle uncertain or incorrect inputs and outputs. Existing LLM-based tools and coding agents respond to every issue and generate a patch for every case, even when the input is vague or their own output is incorrect. There are no mechanisms in place to abstain when confidence is low. This leads…

IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Siyu Mu, Wei Xuan Chan, Choon Hwai Yap
https://arxiv.org/abs/2506.20696

IMC-PINN-FE: A Physics-Informed Neural Network for Patient-Specific Left Ventricular Finite Element Modeling with Image Motion Consistency and Biomechanical Parameter Estimation
Elucidating the biomechanical behavior of the myocardium is crucial for understanding cardiac physiology, but cannot be directly inferred from clinical imaging and typically requires finite element (FE) simulations. However, conventional FE methods are computationally expensive and often fail to reproduce observed cardiac motions. We propose IMC-PINN-FE, a physics-informed neural network (PINN) framework that integrates imaged motion consistency (IMC) with FE modeling for patient-specific left …

PG-LIO: Photometric-Geometric fusion for Robust LiDAR-Inertial Odometry
Nikhil Khedekar, Kostas Alexis
https://arxiv.org/abs/2506.18583 https://

PG-LIO: Photometric-Geometric fusion for Robust LiDAR-Inertial Odometry
LiDAR-Inertial Odometry (LIO) is widely used for accurate state estimation and mapping which is an essential requirement for autonomous robots. Conventional LIO methods typically rely on formulating constraints from the geometric structure sampled by the LiDAR. Hence, in the lack of geometric structure, these tend to become ill-conditioned (degenerate) and fail. Robustness of LIO to such conditions is a necessity for its broader deployment. To address this, we propose PG-LIO, a real-time LIO me…

Now personally, I'm not invested in the law and I reject the logical underpinnings of the whole thing. The US is founded on land that already had people on it, that already had multiple systems of authority, so there can be no claim that it has any legal authority to exist at all.
But it's hard to ignore the inconsistency here. Accepting the logic from the Declaration of Independence and the Constitution, there is no way in which the current state can be legitimate and which Trump has the authority to do anything. The last legal president, again, following the logic that assumes such a thing even possible, was Barak Obama. Since the transfer of power, the country has failed to enforce the law.
If the executive cannot complete their oath, then they are considered vacant under the 25th amendment. If the cabinet fails to invoke article 4, then they too are involved in the insurrection (again, simply following the logic outlined pretty clearly here) as are any who would fail to support the invocation.
Since a full takeover of the federal government by insurrectionists wasn't really planned for, I'm guessing that it would necessarily go to the states, being the only remaining legal authority.

Writing a unit test for a newer, faster version of a libscopehal primitive and it wasn't lining up with the original results.
Turns out there was a bug in the original (FindZeroCrossings would fail to correctly detect a crossing between samples 0 and 1).

Capturing Misalignment
Pierfrancesco Guarino, Gabriel Ziegler
https://arxiv.org/abs/2506.17176 https://arxiv.org/pdf/2506.17176

Capturing Misalignment
We introduce and formalize misalignment, a phenomenon of interactive environments perceived from an analyst's perspective where an agent holds beliefs about another agent's beliefs that do not correspond to the actual beliefs of the latter. We demonstrate that standard frameworks, such as type structures, fail to capture misalignment, necessitating new tools to analyze this phenomenon. To this end, we characterize misalignment through non-belief-closed state spaces and introduce agent-dependent…

"That is the real reason why Starship was doomed to fail from the beginning. It’s not trying to revolutionise the space industry; if it were, its concept, design, and testing plan would be totally different. Instead, the entire project is optimised to fleece as much money from the US taxpayer as possible, and as such, that is all it will ever do."
Wow, this is an interesting piece..
https://www.planetearthandbeyond.co/p/starship-was-doomed-from-the-beginning

Nice blog by Gary Marcus, for me personally this is not a blow, I don't see current AI as reasoning or thinking, it still will have enormous impact without these capabilities.
Also it's fascinating that models are able to solve some difficult math problems (that are not in their trainingset ) while they fail with seemingly simple other problems.

A knockout blow for LLMs?
LLM “reasoning” is so cooked they turned my name into a verb

@… Luckily, I can use pass/fail grading for most of my courses. However, I have no interest in being a jester whose job is to entertain disinterested students. This will be the challenge…

@… Luckily, I can use pass/fail grading for most of my courses. However, I have no interest in being a jester whose job is to entertain disinterested students. This will be the challenge…

No one is as good at making their application worse over time as the YouTube mobile app team. They never fail to impress me with how they can make the experience worse so consistently over time.
#rant

Uncovering Conceptual Blindspots in Generative Image Models Using Sparse Autoencoders
Matyas Bohacek, Thomas Fel, Maneesh Agrawala, Ekdeep Singh Lubana
https://arxiv.org/abs/2506.19708

Uncovering Conceptual Blindspots in Generative Image Models Using Sparse Autoencoders
Despite their impressive performance, generative image models trained on large-scale datasets frequently fail to produce images with seemingly simple concepts -- e.g., human hands or objects appearing in groups of four -- that are reasonably expected to appear in the training data. These failure modes have largely been documented anecdotally, leaving open the question of whether they reflect idiosyncratic anomalies or more structural limitations of these models. To address this, we introduce a …

Impeached Beached Fail
bot by @…
This is satire, not sedition: I hope you'll lol, not take legal action.
#satire #potus45

Democrats fail to subpoena Musk for Trump-era role
https://thehill.com/policy/technology/5334582-republicans-block-musk-testimony-over-trump/

A late addition to stroke awareness month (May).
From my article: #health #stroke

Accelerating Large-Scale Regularized High-Order Tensor Recovery
Wenjin Qin, Hailin Wang, Jingyao Hou, Jianjun Wang
https://arxiv.org/abs/2506.09594 https:/…

Accelerating Large-Scale Regularized High-Order Tensor Recovery
Currently, existing tensor recovery methods fail to recognize the impact of tensor scale variations on their structural characteristics. Furthermore, existing studies face prohibitive computational costs when dealing with large-scale high-order tensor data. To alleviate these issue, assisted by the Krylov subspace iteration, block Lanczos bidiagonalization process, and random projection strategies, this article first devises two fast and accurate randomized algorithms for low-rank tensor approx…

Floating-Point Data Transformation for Lossless Compression
Samirasadat Jamalidinan, Kazem Cheshmi
https://arxiv.org/abs/2506.18062 https://

Floating-Point Data Transformation for Lossless Compression
Floating-point data is widely used across various domains. Depending on the required precision, each floating-point value can occupy several bytes. Lossless storage of this information is crucial due to its critical accuracy, as seen in applications such as medical imaging and language model weights. In these cases, data size is often significant, making lossless compression essential. Previous approaches either treat this data as raw byte streams for compression or fail to leverage all pattern…

Madleen Gaza flotilla live tracker: Greta Thunberg, crew near Gaza | Gaza News | Al Jazeera
https://aje.io/p6b8m7?update=3762371
UN rights expert says Israeli speedboats surrounding Madleen
(Via @…

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
Hongzhou Rao, Yanjie Zhao, Wenjie Zhu, Ling Xiao, Meizhen Wang, Haoyu Wang
https://arxiv.org/abs/2506.17627

CodeMorph: Mitigating Data Leakage in Large Language Model Assessment
Concerns about benchmark leakage in large language models for code (Code LLMs) have raised issues of data contamination and inflated evaluation metrics. The diversity and inaccessibility of many training datasets make it difficult to prevent data leakage entirely, even with time lag strategies. Consequently, generating new datasets through code perturbation has become essential. However, existing methods often fail to produce complex and diverse variations, struggle with complex cross-file depe…

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Kai He, Ruofan Liang, Jacob Munkberg, Jon Hasselgren, Nandita Vijaykumar, Alexander Keller, Sanja Fidler, Igor Gilitschenski, Zan Gojcic, Zian Wang
https://arxiv.org/abs/2506.15673

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-to-end relighting models are often limited by the scarcity of paired multi-illumination data, restricting their ability to generalize across diverse scenes. Conversely, two-stage pipelines that combine inverse and forward rendering can mitigate data requirements but are susceptible to error accumulation and often fail …

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Teng Guo, Baichuan Huang, Jingjin Yu
https://arxiv.org/abs/2506.17110 https://

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Accurate 6D object pose estimation is a prerequisite for successfully completing robotic prehensile and non-prehensile manipulation tasks. At present, 6D pose estimation for robotic manipulation generally relies on depth sensors based on, e.g., structured light, time-of-flight, and stereo-vision, which can be expensive, produce noisy output (as compared with RGB cameras), and fail to handle transparent objects. On the other hand, state-of-the-art monocular depth estimation models (MDEMs) provid…

Fuckface McFuckington First Earl of Fail
bot by @…
This is for tee hee, not treason: no waterboarding please and thank you.
#satire #potus45

A Study of Dynamic Stock Relationship Modeling and S&P500 Price Forecasting Based on Differential Graph Transformer
Linyue Hu, Qi Wang
https://arxiv.org/abs/2506.18717

A Study of Dynamic Stock Relationship Modeling and S&P500 Price Forecasting Based on Differential Graph Transformer
Stock price prediction is vital for investment decisions and risk management, yet remains challenging due to markets' nonlinear dynamics and time-varying inter-stock correlations. Traditional static-correlation models fail to capture evolving stock relationships. To address this, we propose a Differential Graph Transformer (DGT) framework for dynamic relationship modeling and price prediction. Our DGT integrates sequential graph structure changes into multi-head self-attention via a differentia…

AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri, Samuel J. Bell
https://arxiv.org/abs/2506.09038

AbstentionBench: Reasoning LLMs Fail on Unanswerable Questions
For Large Language Models (LLMs) to be reliably deployed in both everyday and high-stakes domains, knowing when not to answer is equally critical as answering correctly. Real-world user queries, which can be underspecified, ill-posed, or fundamentally unanswerable, require LLMs to reason about uncertainty and selectively abstain -- i.e., refuse to answer definitively. However, abstention remains understudied, without a systematic evaluation framework for modern LLMs. In this work, we introduce …

PBench: Workload Synthesizer with Real Statistics for Cloud Analytics Benchmarking
Yan Zhou, Chunwei Liu, Bhuvan Urgaonkar, Zhengle Wang, Magnus Mueller, Chao Zhang, Songyue Zhang, Pascal Pfeil, Dominik Horn, Zhengchun Liu, Davide Pagano, Tim Kraska, Samuel Madden, Ju Fan
https://arxiv.org/abs/2506.16379

PBench: Workload Synthesizer with Real Statistics for Cloud Analytics Benchmarking
Cloud service providers commonly use standard benchmarks like TPC-H and TPC-DS to evaluate and optimize cloud data analytics systems. However, these benchmarks rely on fixed query patterns and fail to capture the real execution statistics of production cloud workloads. Although some cloud database vendors have recently released real workload traces, these traces alone do not qualify as benchmarks, as they typically lack essential components like the original SQL queries and their underlying dat…

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety
Christina Q. Knight, Kaustubh Deshpande, Ved Sirdeshmukh, Meher Mankikar, Scale Red Team, SEAL Research Team, Julian Michael
https://arxiv.org/abs/2506.14922

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety
The rapid advancement of large language models (LLMs) introduces dual-use capabilities that could both threaten and bolster national security and public safety (NSPS). Models implement safeguards to protect against potential misuse relevant to NSPS and allow for benign users to receive helpful information. However, current benchmarks often fail to test safeguard robustness to potential NSPS risks in an objective, robust way. We introduce FORTRESS: 500 expert-crafted adversarial prompts with ins…

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi
https://arxiv.org/abs/2506.14914

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Anatomical trees play an important role in clinical diagnosis and treatment planning. Yet, accurately representing these structures poses significant challenges owing to their intricate and varied topology and geometry. Most existing methods to synthesize vasculature are rule based, and despite providing some degree of control and variation in the structures produced, they fail to capture the diversity and complexity of actual anatomical data. We developed a Recursive variational Neural Network…

Adversarial Disentanglement by Backpropagation with Physics-Informed Variational Autoencoder
Ioannis Christoforos Koune, Alice Cicirello
https://arxiv.org/abs/2506.13658

Adversarial Disentanglement by Backpropagation with Physics-Informed Variational Autoencoder
Inference and prediction under partial knowledge of a physical system is challenging, particularly when multiple confounding sources influence the measured response. Explicitly accounting for these influences in physics-based models is often infeasible due to epistemic uncertainty, cost, or time constraints, resulting in models that fail to accurately describe the behavior of the system. On the other hand, data-driven machine learning models such as variational autoencoders are not guaranteed t…

AcademicBrowse: Benchmarking Academic Browse Ability of LLMs
Junting Zhou, Wang Li, Yiyan Liao, Nengyuan Zhang, Tingjia Miaoand Zhihui Qi, Yuhan Wu, Tong Yang
https://arxiv.org/abs/2506.13784

AcademicBrowse: Benchmarking Academic Browse Ability of LLMs
Large Language Models (LLMs)' search capabilities have garnered significant attention. Existing benchmarks, such as OpenAI's BrowseComp, primarily focus on general search scenarios and fail to adequately address the specific demands of academic search. These demands include deeper literature tracing and organization, professional support for academic databases, the ability to navigate long-tail academic knowledge, and ensuring academic rigor. Here, we proposed AcademicBrowse, the first dataset …

OH (not mine):
One thing a lot of people fail to understand is that a if a social group are oppressors in one place and oppressed in another, the score isn't oppressors:1, humanity:1.
It's oppression:2, humanity:0.

From Tea Leaves to System Maps: Context-awareness in Monitoring Operational Machine Learning Models
Joran Leest, Claudia Raibulet, Patricia Lago, Ilias Gerostathopoulos
https://arxiv.org/abs/2506.10770

From Tea Leaves to System Maps: Context-awareness in Monitoring Operational Machine Learning Models
Machine learning (ML) models in production do not fail due to statistical anomalies in their input data; they fail due to contextual misalignment -- when their environment deviates from training assumptions, leading to unreliable predictions. Effective ML monitoring requires rich contextual information to move beyond detecting statistical shifts toward meaningful alerts and systematic root-cause analysis. Yet, surprisingly, despite extensive research in ML monitoring and related disciplines (dr…

Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities
Jiancheng Ruan, Tingyang Chen, Renchi Yang, Xiangyu Ke, Yunjun Gao
https://arxiv.org/abs/2506.15986

Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities
Approximate Nearest Neighbor Search (ANNS) in high-dimensional spaces finds extensive applications in databases, information retrieval, recommender systems, etc. While graph-based methods have emerged as the leading solution for ANNS due to their superior query performance, they still face several challenges, such as struggling with local optima and redundant computations. These issues arise because existing methods (i) fail to fully exploit the topological information underlying the proximity …

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Hyeonseo Lee, Juhyun Park, Jihyong Oh, Chanho Eom
https://arxiv.org/abs/2506.12413

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Person Re-identification (ReID) aims to retrieve images of the same individual captured across non-overlapping camera views, making it a critical component of intelligent surveillance systems. Traditional ReID methods assume that the training and test domains share similar characteristics and primarily focus on learning discriminative features within a given domain. However, they often fail to generalize to unseen domains due to domain shifts caused by variations in viewpoint, background, and l…

Fuckface McFuckington First Earl of Fail
bot by @…
This is satire, not sedition: tell the black helicopters to return to base.
#satire #potus45…

A Hierarchical Test Platform for Vision Language Model (VLM)-Integrated Real-World Autonomous Driving
Yupeng Zhou, Can Cui, Juntong Peng, Zichong Yang, Juanwu Lu, Jitesh H Panchal, Bin Yao, Ziran Wang
https://arxiv.org/abs/2506.14100

A Hierarchical Test Platform for Vision Language Model (VLM)-Integrated Real-World Autonomous Driving
Vision-Language Models (VLMs) have demonstrated notable promise in autonomous driving by offering the potential for multimodal reasoning through pretraining on extensive image-text pairs. However, adapting these models from broad web-scale data to the safety-critical context of driving presents a significant challenge, commonly referred to as domain shift. Existing simulation-based and dataset-driven evaluation methods, although valuable, often fail to capture the full complexity of real-world …