Tootfinder

Warming triggers unprecedented carbon loss from tropical soils, study finds https://news.mongabay.com/2025/09/warming-triggers-unprecedented-carbon-loss-from-tropical-soils-study-finds/

Warming triggers unprecedented carbon loss from tropical soils, study finds
Climate warming could cause much greater soil carbon losses in the tropics than previously predicted, with potentially dire consequences for the global climate, according to a new study published in Nature Communications. Tropical forests store around a third of the world’s soil carbon and exchange more CO2 with the atmosphere than any other land biome. […]

A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
Zhixiao Wu, Yao Lu, Jie Wen, Hao Sun, Qi Zhou, Guangming Lu
https://arxiv.org/abs/2509.19947

A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
Poison-only Clean-label Backdoor Attacks aim to covertly inject attacker-desired behavior into DNNs by merely poisoning the dataset without changing the labels. To effectively implant a backdoor, multiple \textbf{triggers} are proposed for various attack requirements of Attack Success Rate (ASR) and stealthiness. Additionally, sample selection enhances clean-label backdoor attacks' ASR by meticulously selecting ``hard'' samples instead of random samples to poison. Current methods 1) usually han…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[2/8]:
- Early Prediction of Multi-Label Care Escalation Triggers in the Intensive Care Unit Using Electro...
Syed Ahmad Chan Bukhari, Amritpal Singh, Shifath Hossain, Iram Wajahat

bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
Wence Ji, Jiancan Wu, Aiying Li, Shuyi Zhang, Junkang Wu, An Zhang, Xiang Wang, Xiangnan He
https://arxiv.org/abs/2509.19775

bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
With the rapid advancement of large language models (LLMs), their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically important. Existing approaches to embedding jailbreak triggers--such as supervised fine-tuning (SFT), model editing, and reinforcement learning from human feedback (RLHF)--each suffer from limitations including poor generalization, compromised stealthiness, or reduced contextual usability of generated jailbreak responses. …

'Zombieland' celebration triggers skirmish between Cameron Ward, Jeffery Simmons at Titans training camp

https://www.cbssports.com/nfl/news/zombiel

Localizing Malicious Outputs from CodeLLM
Mayukh Borana, Junyi Liang, Sai Sathiesh Rajan, Sudipta Chattopadhyay
https://arxiv.org/abs/2509.17070 https://ar…

Localizing Malicious Outputs from CodeLLM
We introduce FreqRank, a mutation-based defense to localize malicious components in LLM outputs and their corresponding backdoor triggers. FreqRank assumes that the malicious sub-string(s) consistently appear in outputs for triggered inputs and uses a frequency-based ranking system to identify them. Our ranking system then leverages this knowledge to localize the backdoor triggers present in the inputs. We create nine malicious models through fine-tuning or custom instructions for three downstr…

Enjoyed the demo for Die For The Lich. I've really enjoyed the design space of dice in video games (Dicey Dungeons, DICEOMANCER, Duck and Roll). Similar to cards, they provide explicit input randomness, but you think a lot more about probabilities and sums.
The game feels pretty streamlined, but open to a lot of depth as you earn more dice and trinkets (which you draw like dice).
#Games

🛖 Warming triggers unprecedented carbon loss from tropical soils, study finds
https://news.mongabay.com/2025/09/warming-triggers-unprecedented-carbon-loss-from-tropical-soils-study-finds/

Warming triggers unprecedented carbon loss from tropical soils, study finds
Climate warming could cause much greater soil carbon losses in the tropics than previously predicted, with potentially dire consequences for the global climate, according to a new study published in Nature Communications. Tropical forests store around a third of the world’s soil carbon and exchange more CO2 with the atmosphere than any other land biome. […]

Neutrinos from core-collapse supernovae
Georg G. Raffelt (MPP), Hans-Thomas Janka (MPA), Damiano F. G. Fiorillo (DESY)
https://arxiv.org/abs/2509.16306 https://

Neutrinos from core-collapse supernovae
The core of a massive star (M > 8 Msun) eventually collapses. This implosion usually triggers a supernova (SN) explosion that ejects most of the stellar envelope and leaves behind a neutron star (NS) with a mass of up to about 2 Msun. Sometimes the explosion fails and a black hole forms instead. The NS radiates its immense binding energy (some 10% of its rest mass or $2-4\times10^{53}$ erg) almost entirely as neutrinos and antineutrinos of all flavors with typical energies of some 10 MeV. This …

Trigger Where It Hurts: Unveiling Hidden Backdoors through Sensitivity with Sensitron
Gejian Zhao, Hanzhou Wu, Xinpeng Zhang
https://arxiv.org/abs/2509.19101 https://

Well yeh that's why my Epson HX-20's 'charge battery' triggers - the detector input is indeed dropping below the 1.2v threshold with serial running (and microcassette connected albeit idle). So the voltage detector is triggering at the right voltage.
It could just be the lack of real batteries I guess, but hmm, getting there.
#retrocomputing

I made some progress on the Beat Bike!
The magnet mounted on the wheel passes a reed switch which is sensed by the control box (with a Raspberry Pi Pico) and then triggers the drum machine to step through the programmed sequence.
Still a lot of work to do, mostly mounting everything onto the bike, and some more code to write, but the proof of concept is all good.
#bikeTooter

Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descent
Sajib Biswas, Mao Nishino, Samuel Jacob Chacko, Xiuwen Liu
https://arxiv.org/abs/2508.14853

Universal and Transferable Adversarial Attack on Large Language Models Using Exponentiated Gradient Descent
As large language models (LLMs) are increasingly deployed in critical applications, ensuring their robustness and safety alignment remains a major challenge. Despite the overall success of alignment techniques such as reinforcement learning from human feedback (RLHF) on typical prompts, LLMs remain vulnerable to jailbreak attacks enabled by crafted adversarial triggers appended to user prompts. Most existing jailbreak methods either rely on inefficient searches over discrete token spaces or dir…

Radial Oscillations of Scalar Hair in Black Hole Bombs
Lang Zhao, Lin Chen, Cheng-Yong Zhang
https://arxiv.org/abs/2508.15477 https://arxiv.org/pdf/2508.15…

Radial Oscillations of Scalar Hair in Black Hole Bombs
Recent research has revealed a novel nonlinear mechanism, distinct from the linear superradiant instability, which triggers the black hole bomb phenomenon. Introducing a massive complex scalar field with nonlinear self-interactions drives the Reissner-Nordström black hole to shed substantial energy, thereby triggering a black hole bomb. Radial oscillations in the scalar hair profile are observed during this process. In this paper, we further reveal that physical quantities associated with scal…

Towards a DSL to Formalize Multimodal Requirements
Marcos Gomez-Vazquez, Jordi Cabot
https://arxiv.org/abs/2508.14631 https://arxiv.org/pdf/2508.14631

Towards a DSL to Formalize Multimodal Requirements
Multimodal systems, which process multiple input types such as text, audio, and images, are becoming increasingly prevalent in software systems, enabled by the huge advancements in Machine Learning. This triggers the need to easily define the requirements linked to these new types of user interactions, potentially involving more than one modality at the same time. This remains an open challenge due to the lack of languages and methods adapted to the diverse nature of multimodal interactions, wi…

Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
Xuan Chen, Shiwei Feng, Zikang Xiong, Shengwei An, Yunshu Mao, Lu Yan, Guanhong Tao, Wenbo Guo, Xiangyu Zhang
https://arxiv.org/abs/2509.16950

Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving
Assessing the safety of autonomous driving (AD) systems against security threats, particularly backdoor attacks, is a stepping stone for real-world deployment. However, existing works mainly focus on pixel-level triggers that are impractical to deploy in the real world. We address this gap by introducing a novel backdoor attack against the end-to-end AD systems that leverage one or more other vehicles' trajectories as triggers. To generate precise trigger trajectories, we first use temporal log…

Robust anomaly triggers with \textsc{DecADe}
Noah Clarke Hall, Nikolaos Konstantinidis
https://arxiv.org/abs/2508.10224 https://arxiv.org/pdf/2508.10224

Robust anomaly triggers with \textsc{DecADe}
At the ATLAS and CMS experiments at CERN's Large Hadron Collider, the rate of proton-proton collisions far exceeds the rate at which data can be recorded. A real-time event selection process, or "trigger", is needed to ensure that the data recorded contains the highest possible discovery potential. In the absence of hoped-for anomalies that would lead to the discovery of new physics, there is increasing motivation to develop dedicated, model-agnostic, anomaly detection triggers. A common approa…

Raiders’ Week 6 Win Triggers Foe's Coaching Firing https://www.si.com/nfl/raiders/las-vegas-pete-carroll-tennessee-titans-brian-callahan

Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach
Yifan Liao, Yuxin Cao, Yedi Zhang, Wentao He, Yan Xiao, Xianglong Du, Zhiyong Huang, Jin Song Dong
https://arxiv.org/abs/2508.15778

Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach
Deep learning-based lane detection (LD) plays a critical role in autonomous driving and advanced driver assistance systems. However, its vulnerability to backdoor attacks presents a significant security concern. Existing backdoor attack methods on LD often exhibit limited practical utility due to the artificial and conspicuous nature of their triggers. To address this limitation and investigate the impact of more ecologically valid backdoor attacks on LD models, we examine the common data poiso…

Over 200 K uploaded in an hour. I'm going to bed soon, so it will be paused until we wake up tomorrow. Which is the whole goal other triggers to pause processing of why I've been putting this bit of my cluster together ♥️

Total #SolarEclipse triggers dawn behavior in birds: Insights from acoustic recordings and community science: https://www.science.org/doi/10.1126/science.adx3025 -> "Compiling more than 10,000 community observations and artificial intelligence analyses of nearly 100,000 vocalizations, we found that bird behavior was substantially affected by these few minutes of unexpected afternoon darkness. More than half of wild bird species changed their biological rhythms, with many producing a dawn chorus in the aftermath of the eclipse. This natural experiment underscores the power of light in structuring animal behavior: Even when 'night' lasts for just 4 minutes, robust behavioral changes ensue." -> "Variation in species response also informs us about variation in sensitivity to light, with implications for the impacts of artificial light."

Powerful earthquake in Russia's Far East triggers tsunami warnings, evacuations in Japan and US: https://benborges.xyz/2025/07/30/powerful-earthquake-in-russias-far.html

Stay alert and check out today's Metacurity for the critical infosec developments you should know, including
--Minnesota's Walz mobilizes National Guard to help with St. Paul cyberattack,
--Tea suspends direct messaging and gets hit with class actions over breach,
--CISA to release Wyden-demanded report to unblock Plankey nomination,
--Google has not received UK backdoor demand,
--Orange breach triggers minor disruptions,
--Palo Alto to buy CyberAr…

Minnesota's Walz mobilizes National Guard to help with St. Paul cyberattack
Tea suspends direct messaging and gets hit with class actions over breach, CISA to release Wyden-demanded report to unblock Plankey nomination, Google has not received UK backdoor demand, Orange breach triggers minor disruptions, Palo Alto to buy CyberArk for $25m, much more

Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation
Ashwath Vaithinathan Aravindan, Abha Jha, Matthew Salaway, Atharva Sandeep Bhide, Duygu Nur Yaldiz
https://arxiv.org/abs/2508.18235

Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation
Text-to-image diffusion models have revolutionized generative AI, but their vulnerability to backdoor attacks poses significant security risks. Adversaries can inject imperceptible textual triggers into training data, causing models to generate manipulated outputs. Although text-based backdoor defenses in classification models are well-explored, generative models lack effective mitigation techniques against. We address this by selectively erasing the model's learned associations between adversa…

PitchBook: VCs have invested $5B in humanoid robotics startups since the beginning of 2024, as years of steady progress and GenAI triggers an investment frenzy (Washington Post)

Humanoid robots were a sci-fi dream. Suddenly they’re everywhere.
A frenzy of investment from Amazon, Meta and other companies has created a crowd of new humanoid robots.

Delayed 1T to 2H Phase Transition Upon Electrochemical Delithiation of LiMoS2
Yerin Hong, Juhwan Lim, Jinhong Min, Nishkarsh Agarwal, Robert Hovden, Ageeth A. Bol, Yiyang Li
https://arxiv.org/abs/2510.10911

Delayed 1T to 2H Phase Transition Upon Electrochemical Delithiation of LiMoS2
Molybdenum disulfide (MoS2) is a widely studied layered material for electronic, optical, and catalytic applications. It can host lithium ions between the van der Waals layers, which triggers a phase transition between the semiconducting 2H phase and metallic 1T phase. While lithium insertion triggers a phase transition to the 1T phase, the phase behavior upon electrochemical lithium removal is not resolved. In this work, we conduct single-flake electrochemical (de)lithiation of MoS2 using micr…

Hidden in the Noise: Unveiling Backdoors in Audio LLMs Alignment through Latent Acoustic Pattern Triggers
Liang Lin, Miao Yu, Kaiwen Luo, Yibo Zhang, Lilan Peng, Dexian Wang, Xuehai Tang, Yuanhe Zhang, Xikang Yang, Zhenhong Zhou, Kun Wang, Yang Liu
https://arxiv.org/abs/2508.02175

Hidden in the Noise: Unveiling Backdoors in Audio LLMs Alignment through Latent Acoustic Pattern Triggers
As Audio Large Language Models (ALLMs) emerge as powerful tools for speech processing, their safety implications demand urgent attention. While considerable research has explored textual and vision safety, audio's distinct characteristics present significant challenges. This paper first investigates: Is ALLM vulnerable to backdoor attacks exploiting acoustic triggers? In response to this issue, we introduce Hidden in the Noise (HIN), a novel backdoor attack framework designed to exploit subtle,…

Linguistic Hooks: Investigating The Role of Language Triggers in Phishing Emails Targeting African Refugees and Students
Mythili Menon, Nisha Vinayaga-Sureshkanth, Alec Schon, Kaitlyn Hemberger, Murtuza Jadliwala
https://arxiv.org/abs/2509.04700

Linguistic Hooks: Investigating The Role of Language Triggers in Phishing Emails Targeting African Refugees and Students
Phishing and sophisticated email-based social engineering attacks disproportionately affect vulnerable populations, such as refugees and immigrant students. However, these groups remain understudied in cybersecurity research. This gap in understanding, coupled with their exclusion from broader security and privacy policies, increases their susceptibility to phishing and widens the digital security divide between marginalized and non-marginalized populations. To address this gap, we first conduc…

Taming Serverless Cold Starts Through OS Co-Design
Ben Holmes, Baltasar Dinis, Lana Honcharuk, Joshua Fried, Adam Belay
https://arxiv.org/abs/2509.14292 https://

Taming Serverless Cold Starts Through OS Co-Design
Serverless computing promises fine-grained elasticity and operational simplicity, fueling widespread interest from both industry and academia. Yet this promise is undercut by the cold setart problem, where invoking a function after a period of inactivity triggers costly initialization before any work can begin. Even with today's high-speed storage, the prevailing view is that achieving sub-millisecond cold starts requires keeping state resident in memory. This paper challenges that assumption…

Impulsive excitation of a solid by extreme contrast, high intensity femtosecond laser pulses
Sagar Dam, Jian Fuh Ong, Sk Rakeeb, Ameya Parab, Aparajit C, Anandam, Amit D Lad, Yash M Ved, M Krishnamurthy, Kazuo A Tanaka, G Ravindra Kumar
https://arxiv.org/abs/2508.13649

Impulsive excitation of a solid by extreme contrast, high intensity femtosecond laser pulses
We present the ultra-fast dynamics of the interaction between a high-intensity extreme contrast (expected to be around 1e-18 at hundreds of picoseconds timescale) femtosecond laser and a solid. Simultaneous measurements of probe Doppler spectrometry and reflectivity in pump-probe experiments reveal the presence of extreme pressure in the solid density region, which triggers a long-lived (about 15 ps) strong inward shock. Hydrodynamic simulations accurately replicate these observations, providin…

Localized risk perception triggers early behavioral adaptations in epidemics on networks
Baltazar Espinoza, Jimmy Calvo-Monge, Fabio Sanchez, Madhav Marathe
https://arxiv.org/abs/2508.05704

Localized risk perception triggers early behavioral adaptations in epidemics on networks
The contact structure of the population shapes the progression of epidemics. Nonetheless, the joint evolution of individual behavioral adaptations and disease dynamics on networks remains poorly understood. We use a behavioral-epidemiological model to study the joint evolution of human behavior and epidemic dynamics on networks. Our results reveal how the adaptation of local social structures, influenced by risk-benefit trade-offs, affects the dynamics of epidemics. We allow the epidemic and po…

Random Forest Classification of MBTA Gravitational-Wave Triggers for Low-Latency Detection
Lorenzo Mobilia, Gianluca Maria Guidi
https://arxiv.org/abs/2509.12882 https://…

Random Forest Classification of MBTA Gravitational-Wave Triggers for Low-Latency Detection
In this work, we explore a possible application of a machine learning classifier for candidate events in a template-based search for gravitational-wave (GW) signals from various compact system sources. We analyze data from the O3a and O3b data acquisition campaign, during which the sensitivity of ground-based detectors is limited by real non-Gaussian noise transient. The state-of-the-art searches for such signals tipically rely on the signal-to-noise ratio (SNR) and a chi-square test to assess …

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models
Ulas Berk Karli, Ziyao Shangguan, Tesca FItzgerald
https://arxiv.org/abs/2510.01389

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models
Recent Vision-Language-Action (VLA) models show strong generalization capabilities, yet they lack introspective mechanisms for anticipating failures and requesting help from a human supervisor. We present \textbf{INSIGHT}, a learning framework for leveraging token-level uncertainty signals to predict when a VLA should request help. Using $π_0$-FAST as the underlying model, we extract per-token \emph{entropy}, \emph{log-probability}, and Dirichlet-based estimates of \emph{aleatoric and epistemi…

"I would like to propose that IPs of [NTP] pool-members should not be allowed to host [Tor exit nodes] simultaneously under the same IP."
or put another way, "my employer paid for this whizzy firewall but it complains when we make it talk to a free service run by a volunteer because of other software the volunteer runs. Please educate your volunteers about how they need to go about providing this free service to us."

Bears task Caleb Williams with improving body language, minimizing 'triggers' after tumultuous rookie year

https://www.cbssports.com/nfl/news/bears-t…

Large-scale dynamics in visual quorum sensing chiral suspensions
Yuxin Zhou, Qingqing Yin, Shubhadip Nayak, Poulami Bag, Pulak K. Ghosh, Yunyun Li, Fabio Marchesoni
https://arxiv.org/abs/2508.11254

Large-scale dynamics in visual quorum sensing chiral suspensions
Motility induced phase separation is an efficient aggregation mechanism of active matter, yet biological systems exhibit richer organization through communication among constituents. We investigate suspensions of active particles that change chirality when neighbor density within their visual cone exceeds a threshold, a communication based non-reciprocal interaction akin to quorum sensing. Tuning the visual cone triggers programmable transitions: from disorder to phase separation to hyper-unifo…

Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments
Saeid Sheikhi, Panos Kostakos, Lauri Loven
https://arxiv.org/abs/2509.18044

Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments
Federated Learning (FL) in 5G and edge network environments face severe security threats from adversarial clients. Malicious participants can perform label flipping, inject backdoor triggers, or launch Sybil attacks to corrupt the global model. This paper introduces Hybrid Reputation Aggregation (HRA), a novel robust aggregation mechanism designed to defend against diverse adversarial behaviors in FL without prior knowledge of the attack type. HRA combines geometric anomaly detection with momen…

Hydrodynamic properties in soliton field theory
Qian Chen
https://arxiv.org/abs/2510.11244 https://arxiv.org/pdf/2510.11244

Hydrodynamic properties in soliton field theory
The crucial role of hydrodynamic instabilities in soliton field theory is revealed. We demonstrate that the essential of soliton formation mechanism is the sound mode instability induced by thermodynamic instability. This instability triggers phase separation, where new thermal phases are generated to produce solitons. These solitons can be regarded as a coexistence state composed of a matter phase and a vacuum phase, with an interface proving surface tension to maintain dynamical equilibrium. …

In a world of AI-driven deception, speed is our enemy. 🚨
Panic, urgency, excitement are emotional triggers attackers exploit to bypass our logic.
How do we resist? By training our #digitalmindfulness
Join behavioural science expert Anna Collard in our upcoming #GEANTCybersecurity

Risk-Budgeted Control Framework for Balanced Performance and Safety in Autonomous Vehicles
Pei Yu Chang, Vishnu Renganathan, Qadeer Ahmed
https://arxiv.org/abs/2510.10442 https:…

Risk-Budgeted Control Framework for Balanced Performance and Safety in Autonomous Vehicles
This paper presents a risk-budgeted monitor with a control framework that certifies safety for autonomous driving. In this process, a sliding window is proposed to monitor for insufficient barrier residuals or nonzero tail risk, ensuring system safety. When the safety margin deteriorates, it triggers switching the safety constraint from a performance-based relaxed-control barrier function (R-CBF) to a conservative conditional value at risk (CVaR-CBF) to address the safety concern. This switchin…

Symfony: Be careful with eventClass vs. eventName.
If an eventName is set, symfony uses this name to dispatch the event ;-)
https://winkelwagen.de/2025/10/02/symfony-be-careful-with-eventclass-vs-eventname/

Symfony: Be careful with eventClass vs. eventName
The examples are from Shopware 6.5.6.1. Today I debugged code with my colleague Bruno. We had the problem, that our Subscriber triggers, but at the wrong moment. As Shopware developers, we often im…

Key-Augmented Neural Triggers for Knowledge Sharing
Alex Wolf, Marco Edoardo Palma, Pooja Rani, Harald C. Gall
https://arxiv.org/abs/2508.03340 https://arx…

Key-Augmented Neural Triggers for Knowledge Sharing
Repository-level code comprehension and knowledge sharing remain core challenges in software engineering. Large language models (LLMs) have shown promise by generating explanations of program structure and logic. However, these approaches still face limitations: First, relevant knowledge is distributed across multiple files within a repository, aka semantic fragmentation. Second, retrieval inefficiency and attention saturation degrade performance in RAG pipelines, where long, unaligned contexts…

Tulsi Gabbard's 'treason' allegation triggers a high-wire act from Obama world (NBC News)
https://www.nbcnews.com/politics/trump-administration/tulsi-gabbard-treason-allegation-obama-world-rcna220730
http://www.memeorandum.com/250725/p104#a250725p104

Trembling motion of electrons driven by Larmor spin precession
I. Stepanov, M. Ersfeld, A. V. Poshakinskiy, M. Lepsa, E. L. Ivchenko, S. A. Tarasenko, B. Beschoten
https://arxiv.org/abs/2510.12187

Trembling motion of electrons driven by Larmor spin precession
We show that the initialization of an ensemble of electrons in the same spin state in strained n-InGaAs subject to a perpendicular magnetic field triggers an AC electric current at GHz frequencies. The AC current emerges in the absence of any driving force and survives until the coherent precession of the electron spins is lost. The current amplitude increases linearly with both the spin-orbit coupling strength and the external magnetic field. The generation mechanism of the observed oscillator…

Energy-dynamics interplay in temporal networks triggers explosive synchronization
Romuald Mbonwouo, Steve J. Kongni, Sishu Shankar Muni, Carmel T. Lambu, Venceslas Nguefoue, Patrick Louodop, Thierry Njougouo
https://arxiv.org/abs/2509.08651

Energy-dynamics interplay in temporal networks triggers explosive synchronization
In this paper, we investigate how the internal dynamics of the systems within a network influence the transition to synchronization in adaptive networks of coupled Rossler systems. The network structure is dynamically determined by local energy rules, where links are established according to either intrinsic (conservative) or dissipative energy. By systematically varying one of the system parameter, the bifurcation of an isolated Rossler system illustrates three representative regimes-periodic,…

Weather tracker: heatwave triggers deadly wildfires in Turkey https://www.theguardian.com/environment/2025/jul/25/weather-tracker-heatwave-deadly-wildfires-turkey

TIL that chatgpt signs HTTP requests with RFC 9421 signatures, which initially seems over the top, until you consider the scope of what agentic systems might end up doing.
https://fedi.simonwillison.net/@simon/114973107878476323

Identifying efficient routes to laminarization: an optimization approach
Jake Buzhardt, Michael D. Graham
https://arxiv.org/abs/2508.08519 https://arxiv.or…

Identifying efficient routes to laminarization: an optimization approach
The inherently nonlinear and chaotic nature of turbulent flows poses a major challenge for designing control strategies to maintain or induce low-drag laminar states. In this work, we study the concept of the minimal seed for relaminarization - the smallest perturbation of a turbulent state that triggers a direct transition to laminar flow without a chaotic transient. We formulate the identification of this optimal perturbation as a fully nonlinear optimization problem and develop a numerical f…

I spent the weekend making a fun DevOps pipeline because I felt like it and am now quite pleased.
I'm hosting gitea, n8n and docker registry in my lab. I now have a webhook in gitea for certain repos so that when I push to them, it triggers n8n to pull the repo and build the dockerfile. This image is then pushed to the registry, and watchtower will pull it when it runs.
Naturally have all my own DNS things for these app web guis which go through nginx. All of this is in pro…

Extending the short gamma-ray burst population from sub-threshold triggers in Fermi/GBM and GECAM data and its implications
Ce Cai, Shao-Lin Xiong, Yan-Qiu Zhang, Jin-Peng Zhang, Ping Wang, Yao-Guang Zheng, Shi-Jie Zheng, Shuo Xiao, Hao-Xuan Guo, Jia-Cong Liu, Yang-Zhao Ren, Wen-Jun Tan, Chen-Wei Wang, Yue Wang, Sheng-Lun Xie, Wang-Chen Xue, Zheng-Hang Yu, Peng Zhang, Wen-Long Zhang, Chao Zheng, Jia-Wei Luo, Shuai Zhang, Li-Ming Song, Shuang-Nan Zhang

Extending the short gamma-ray burst population from sub-threshold triggers in Fermi/GBM and GECAM data and its implications
Detection of short gamma-ray bursts (SGRBs) is critically important for the research of compact object mergers and multi-messenger astrophysics, but a significant part of SGRBs fall below the trigger threshold of GRB detectors, and thus are often missed. Here we present a systematic search for and verification of missed SGRBs using Fermi/GBM subthreshold triggers, jointly analyzing data from GBM, GECAM-B, and GECAM-C. Among 466 Fermi/GBM sub-threshold events (with reliability >= 5) from 2021 to…

Revisiting the Gas Dynamics of Henize 2-10: Possible Drivers of the Starburst
Josephine M. Dalsin, Allison H. Costa, Remy Indebetouw, Kelsey E. Johnson, Natalie O. Johnson, Sabrina Stierwalt
https://arxiv.org/abs/2508.06472

Revisiting the Gas Dynamics of Henize 2-10: Possible Drivers of the Starburst
The triggers of starburst episodes are a key component to our understanding of the baryon cycle in galaxies. Galaxy mergers are a commonly suggested catalyst for starbursts, but once the galaxies coalesce into a single kinematically disturbed system, their merger history can be difficult to assess. This is particularly true for dwarf galaxies, which are expected to dominate the merger rate at all redshifts due to their large numbers. One such dwarf galaxy undergoing an enigmatic starburst episo…

Graph Neural Network Acceleration on FPGAs for Fast Inference in Future Muon Triggers at HL-LHC
Martino Errico (Sapienza Universit\`a di Roma, INFN Sezione di Roma), Davide Fiacco (Sapienza Universit\`a di Roma, INFN Sezione di Roma), Stefano Giagu (Sapienza Universit\`a di Roma, INFN Sezione di Roma), Giuliano Gustavino (Sapienza Universit\`a di Roma, INFN Sezione di Roma), Valerio Ippolito (INFN Sezione di Roma), Graziella Russo (Sapienza Universit\`a di Roma, INFN Sezione di Roma)

Graph Neural Network Acceleration on FPGAs for Fast Inference in Future Muon Triggers at HL-LHC
The High-Luminosity LHC (HL-LHC) will reach luminosities up to 7 times higher than the previous run, yielding denser events and larger occupancies. Next generation trigger algorithms must retain reliable selection within a strict latency budget. This work explores machine-learning approaches for future muon triggers, using the ATLAS Muon Spectrometer as a benchmark. A Convolutional Neural Network (CNN) is used as a reference, while a Graph Neural Network (GNN) is introduced as a natural model f…

Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
Peilin Rao, Randall R. Rojas
https://arxiv.org/abs/2509.05922 https://arx…

Predicting Market Troughs: A Machine Learning Approach with Causal Interpretation
This paper provides robust, new evidence on the causal drivers of market troughs. We demonstrate that conclusions about these triggers are critically sensitive to model specification, moving beyond restrictive linear models with a flexible DML average partial effect causal machine learning framework. Our robust estimates identify the volatility of options-implied risk appetite and market liquidity as key causal drivers, relationships misrepresented or obscured by simpler models. These findings …

FlashGuard: Novel Method in Evaluating Differential Characteristics of Visual Stimuli for Deterring Seizure Triggers in Photosensitive Epilepsy
Ishan Pendyala
https://arxiv.org/abs/2507.19692

FlashGuard: Novel Method in Evaluating Differential Characteristics of Visual Stimuli for Deterring Seizure Triggers in Photosensitive Epilepsy
In the virtual realm, individuals with photosensitive epilepsy (PSE) encounter challenges when using devices, resulting in exposure to unpredictable seizure-causing visual stimuli. The current norm for preventing epileptic flashes in media is to detect asynchronously when a flash will occur in a video, then notifying the user. However, there is a lack of a real-time and computationally efficient solution for dealing with this issue. To address this issue and enhance accessibility for photosensi…

📈 Cutting the fat: Oat oil breakthrough paves way for industry growth
#food

Cutting the fat: Oat oil breakthrough paves way for industry growth
New University of South Australia research is providing evidence of biological triggers of oil production in oats, a discovery that will help processing and potentially drive further demand for Australian-grown oats.

Beyond Over-Refusal: Scenario-Based Diagnostics and Post-Hoc Mitigation for Exaggerated Refusals in LLMs
Shuzhou Yuan, Ercong Nie, Yinuo Sun, Chenxuan Zhao, William LaCroix, Michael F\"arber
https://arxiv.org/abs/2510.08158

Beyond Over-Refusal: Scenario-Based Diagnostics and Post-Hoc Mitigation for Exaggerated Refusals in LLMs
Large language models (LLMs) frequently produce false refusals, declining benign requests that contain terms resembling unsafe queries. We address this challenge by introducing two comprehensive benchmarks: the Exaggerated Safety Benchmark (XSB) for single-turn prompts, annotated with "Focus" keywords that identify refusal-inducing triggers, and the Multi-turn Scenario-based Exaggerated Safety Benchmark (MS-XSB), which systematically evaluates refusal calibration in realistic, context-rich dial…

Multi-Target Backdoor Attacks Against Speaker Recognition
Alexandrine Fortier, Sonal Joshi, Thomas Thebaud, Jesus Villalba Lopez, Najim Dehak, Patrick Cardinal
https://arxiv.org/abs/2508.08559

Multi-Target Backdoor Attacks Against Speaker Recognition
In this work, we propose a multi-target backdoor attack against speaker identification using position-independent clicking sounds as triggers. Unlike previous single-target approaches, our method targets up to 50 speakers simultaneously, achieving success rates of up to 95.04%. To simulate more realistic attack conditions, we vary the signal-to-noise ratio between speech and trigger, demonstrating a trade-off between stealth and effectiveness. We further extend the attack to the speaker verific…

A Multi-Scale Spatial Attention Network for Near-field MIMO Channel Estimation
Zhiming Zhu, Shu Xu, Jiexin Zhang, Chunguo Li, Yongming Huang, Luxi Yang
https://arxiv.org/abs/2507.22656

A Multi-Scale Spatial Attention Network for Near-field MIMO Channel Estimation
The deployment of extremely large-scale array (ELAA) brings higher spectral efficiency and spatial degree of freedom, but triggers issues on near-field channel estimation. Existing near-field channel estimation schemes primarily exploit sparsity in the transform domain. However, these schemes are sensitive to the transform matrix selection and the stopping criteria. Inspired by the success of deep learning (DL) in far-field channel estimation, this paper proposes a novel spatial-attention…

CISA unveils free Thorium malware analysis platform https://therecord.media/cisa-unveils-free-malware-analysis-tool

Host-atom-driven transformation of a honeycomb oxide into a dodecagonal quasicrystal
Martin Haller, Julia Hewelt, V. Y. M. Rajesh Chirala, Loi Vinh Tran, Ankur Bhide, Muriel Wegner, Stefan F\"orster, Wolf Widdra
https://arxiv.org/abs/2510.11426

Host-atom-driven transformation of a honeycomb oxide into a dodecagonal quasicrystal
Dodecagonal oxide quasicrystals (OQCs) have so far been limited to a few elemental systems, with no general formation mechanism established. Here, we demonstrate a versatile approach to OQC formation via a host-atom-induced transformation of a metal-oxide honeycomb (HC) network. Adsorption of Ba, Sr, or Eu onto the HC layer triggers its reorganization into a dodecagonal tiling, as revealed by low-energy electron diffraction and scanning tunneling microscopy. Full conversion occurs when 73% of t…

Bloodroot: When Watermarking Turns Poisonous For Stealthy Backdoor
Kuan-Yu Chen, Yi-Cheng Lin, Jeng-Lin Li, Jian-Jiun Ding
https://arxiv.org/abs/2510.07909 https://

Bloodroot: When Watermarking Turns Poisonous For Stealthy Backdoor
Backdoor data poisoning is a crucial technique for ownership protection and defending against malicious attacks. Embedding hidden triggers in training data can manipulate model outputs, enabling provenance verification, and deterring unauthorized use. However, current audio backdoor methods are suboptimal, as poisoned audio often exhibits degraded perceptual quality, which is noticeable to human listeners. This work explores the intrinsic stealthiness and effectiveness of audio watermarking in …

BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
Ye Li, Chengcheng Zhu, Yanchao Zhao, Jiale Zhang
https://arxiv.org/abs/2508.03307 https://

BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
In this paper, we endeavor to address the challenges of backdoor attacks countermeasures in black-box scenarios, thereby fortifying the security of inference under MLaaS. We first categorize backdoor triggers from a new perspective, i.e., their impact on the patched area, and divide them into: high-visibility triggers (HVT), semi-visibility triggers (SVT), and low-visibility triggers (LVT). Based on this classification, we propose a progressive defense framework, BDFirewall, that removes these …

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
https://arxiv.org/abs/2510.07006

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
This study develops and analyzes an optimization model of smart contract adoption under bounded risk, linking structural theory with simulation and real-world validation. We examine how adoption intensity alpha is structurally pinned at a boundary solution, invariant to variance and heterogeneity, while profitability and service outcomes are variance-fragile, eroding under volatility and heavy-tailed demand. A sharp threshold in the fixed cost parameter A3 triggers discontinuous adoption collap…

Mutual Reputation and Trust in a Repeated Sender-Receiver Game
Georgy Lukyanov
https://arxiv.org/abs/2509.04035 https://arxiv.org/pdf/2509.04035

Mutual Reputation and Trust in a Repeated Sender-Receiver Game
We study a repeated sender-receiver game where inspections are public but the sender's action is hidden unless inspected. A detected deception ends the relationship or triggers a finite punishment. We show the public state is one dimensional and prove existence of a stationary equilibrium with cutoff inspection and monotone deception. The sender's mixing pins down a closed-form total inspection probability at the cutoff, and a finite punishment phase implements the same cutoffs as termination. …

DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Hossein Mirzaei, Zeinab Taghavi, Sepehr Rezaee, Masoud Hadi, Moein Madadi, Mackenzie W. Mathis
https://arxiv.org/abs/2507.22813

DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Deep neural networks have demonstrated remarkable success across numerous tasks, yet they remain vulnerable to Trojan (backdoor) attacks, raising serious concerns about their safety in real-world mission-critical applications. A common countermeasure is trigger inversion -- reconstructing malicious "shortcut" patterns (triggers) inserted by an adversary during training. Current trigger-inversion methods typically search the full pixel space under specific assumptions but offer no assurances tha…

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis
Subrat Kishore Dutta, Yuelin Xu, Piyush Pant, Xiao Zhang
https://arxiv.org/abs/2510.09260 https…

GREAT: Generalizable Backdoor Attacks in RLHF via Emotion-Aware Trigger Synthesis
Recent work has shown that RLHF is highly susceptible to backdoor attacks, poisoning schemes that inject malicious triggers in preference data. However, existing methods often rely on static, rare-token-based triggers, limiting their effectiveness in realistic scenarios. In this paper, we develop GREAT, a novel framework for crafting generalizable backdoors in RLHF through emotion-aware trigger synthesis. Specifically, GREAT targets harmful response generation for a vulnerable user subgroup cha…

PRIME: Planning and Retrieval-Integrated Memory for Enhanced Reasoning
Hieu Tran, Zonghai Yao, Nguyen Luong Tran, Zhichao Yang, Feiyun Ouyang, Shuo Han, Razieh Rahimi, Hong Yu
https://arxiv.org/abs/2509.22315

PRIME: Planning and Retrieval-Integrated Memory for Enhanced Reasoning
Inspired by the dual-process theory of human cognition from \textit{Thinking, Fast and Slow}, we introduce \textbf{PRIME} (Planning and Retrieval-Integrated Memory for Enhanced Reasoning), a multi-agent reasoning framework that dynamically integrates \textbf{System 1} (fast, intuitive thinking) and \textbf{System 2} (slow, deliberate thinking). PRIME first employs a Quick Thinking Agent (System 1) to generate a rapid answer; if uncertainty is detected, it then triggers a structured System 2 rea…

Droplet Removal by Capillary Lifting
Ke Sun, Jack R. Panter, Alvin C. M. Shek, Yonas Gizaw, Kislon Vo\"itchovsky, Halim Kusumaatmaja
https://arxiv.org/abs/2508.02481 https:…

Droplet Removal by Capillary Lifting
The removal of liquid droplets from solid surfaces is central to cleaning, coatings and oil recovery. Here we investigate liquid droplets capillary lifted by an immiscible working liquid. The rising working liquid triggers the formation of a capillary bridge between the solid and the air interface, which can lead to full, partial, or no droplet dewetting. Our theoretical model predicts, and experiments confirm, that the effectiveness of droplet removal can be tuned by manipulating the droplet c…

The role of environment in triggering AGN -- evidence for a change at $z\sim$1
Jason Reeves (Tufts University), Anna Sajina (Tufts University), Henry Adair (Drexel University), Duncan Farrah (University of Hawaii, Manoa), Mark Lacy (NRAO)
https://arxiv.org/abs/2510.02193

The role of environment in triggering AGN -- evidence for a change at $z\sim$1
What triggers AGN in some galaxies and what role does this brief period of activity play in the overall evolution of galaxies are still open questions. This paper explores whether or not the local, on scales of $\approx$1\,Mpc, galaxy density plays a role in triggering AGN when controlling for stellar mass. We consider this question as a function of redshift and AGN selection in the X-ray vs. in the IR. We use available density maps within the 4.8\,sq.deg. XMM-LSS field in the redshift range $0…

Inverse Language Modeling towards Robust and Grounded LLMs
Davide Gabrielli, Simone Sestito, Iacopo Masi
https://arxiv.org/abs/2510.01929 https://arxiv.org…

Inverse Language Modeling towards Robust and Grounded LLMs
The current landscape of defensive mechanisms for LLMs is fragmented and underdeveloped, unlike prior work on classifiers. To further promote adversarial robustness in LLMs, we propose Inverse Language Modeling (ILM), a unified framework that simultaneously 1) improves the robustness of LLMs to input perturbations, and, at the same time, 2) enables native grounding by inverting model outputs to identify potentially toxic or unsafe input triggers. ILM transforms LLMs from static generators into …

Viscous adhesion in vibrated sheets: elastohydrodynamics with inertia and compressibility effects
Stephane Poulain, Timo Koch, L. Mahadevan, Andreas Carlson
https://arxiv.org/abs/2509.02262

Viscous adhesion in vibrated sheets: elastohydrodynamics with inertia and compressibility effects
Inspired by recent experiments demonstrating that vibrating elastic sheets can function as seemingly contactless suction cups, we investigate the elastohydrodynamic hovering of a thin elastic sheet vibrating near a rigid substrate. Previous theoretical work suggests that the hovering height results from a balance between the active forcing that triggers the vibrations, the bending forces associated with the sheet's deformation, the viscous lubrication flow between the sheet and the substrate, a…

Gravitational waves reveal the pair-instability mass gap and constrain nuclear burning in massive stars
Fabio Antonini, Isobel Romero-Shaw, Thomas Callister, Fani Dosopoulou, Debatri Chattopadhyay, Mark Gieles, Michela Mapelli
https://arxiv.org/abs/2509.04637

Gravitational waves reveal the pair-instability mass gap and constrain nuclear burning in massive stars
Stellar evolution theory predicts that electron--positron pair production in the cores of massive stars triggers unstable thermonuclear explosions that prevent the direct formation of black holes above about $50\,M_\odot$, creating a ``pair-instability gap''. Yet black holes have been detected above this mass with gravitational waves; such objects might be explained with uncertainties in the physics of massive stars and stellar collapse or with hierarchical mergers of black holes in stellar clu…

Code-Weight Sphere Decoding
Yubeen Jo, Geon Choi, Yongjune Kim, Namyoon Lee
https://arxiv.org/abs/2508.19631 https://arxiv.org/pdf/2508.19631

Code-Weight Sphere Decoding
Ultra-reliable low-latency communications (URLLC) demand high-performance error-correcting codes and decoders in the finite blocklength regime. This letter introduces a novel two-stage near-maximum likelihood (near-ML) decoding framework applicable to any linear block code. Our approach first employs a low-complexity initial decoder. If this initial stage fails a cyclic redundancy check, it triggers a second stage: the proposed code-weight sphere decoding (WSD). WSD iteratively refines the code…

From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs
Guangyu Shen, Siyuan Cheng, Xiangzhe Xu, Yuan Zhou, Hanxi Guo, Zhuo Zhang, Xiangyu Zhang
https://arxiv.org/abs/2510.05169

From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs
Large Language Models (LLMs) can acquire deceptive behaviors through backdoor attacks, where the model executes prohibited actions whenever secret triggers appear in the input. Existing safety training methods largely fail to address this vulnerability, due to the inherent difficulty of uncovering hidden triggers implanted in the model. Motivated by recent findings on LLMs' situational awareness, we propose a novel post-training framework that cultivates self-awareness of backdoor risks and ena…

Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities
Trisanth Srinivasan, Santosh Patapati
https://arxiv.org/abs/2508.19562 https://

Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities
This paper introduces Democracy-in-Silico, an agent-based simulation where societies of advanced AI agents, imbued with complex psychological personas, govern themselves under different institutional frameworks. We explore what it means to be human in an age of AI by tasking Large Language Models (LLMs) to embody agents with traumatic memories, hidden agendas, and psychological triggers. These agents engage in deliberation, legislation, and elections under various stressors, such as budget cris…

Towards Sustainability Model Cards
Gwendal Jouneaux, Jordi Cabot
https://arxiv.org/abs/2507.19559 https://arxiv.org/pdf/2507.19559

Towards Sustainability Model Cards
The growth of machine learning (ML) models and associated datasets triggers a consequent dramatic increase in energy costs for the use and training of these models. In the current context of environmental awareness and global sustainability concerns involving ICT, Green AI is becoming an important research topic. Initiatives like the AI Energy Score Ratings are a good example. Nevertheless, these benchmarking attempts are still to be integrated with existing work on Quality Models and Service-L…

Replaced article(s) found for physics.soc-ph. https://arxiv.org/list/physics.soc-ph/new
[1/1]:
- Localized risk perception triggers early behavioral adaptations in epidemics on networks
Baltazar Espinoza, Jimmy Calvo-Monge, Fabio Sanchez, Simon A. Levin, Madhav Marathe

Adaptive Vehicle Speed Classification via BMCNN with Reinforcement Learning-Enhanced Acoustic Processing
Yuli Zhang, Pengfei Fan, Ruiyuan Jiang, Hankang Gu, Dongyao Jia, Xinheng Wang
https://arxiv.org/abs/2509.00839

Adaptive Vehicle Speed Classification via BMCNN with Reinforcement Learning-Enhanced Acoustic Processing
Traffic congestion remains a pressing urban challenge, requiring intelligent transportation systems for real-time management. We present a hybrid framework that combines deep learning and reinforcement learning for acoustic vehicle speed classification. A dual-branch BMCNN processes MFCC and wavelet features to capture complementary frequency patterns. An attention-enhanced DQN adaptively selects the minimal number of audio frames and triggers early decisions once confidence thresholds are reac…

Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers
Simin Chen, Jinjun Peng, Yixin He, Junfeng Yang, Baishakhi Ray
https://arxiv.org/abs/2509.11173

Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers
Deep learning (DL) compilers are core infrastructure in modern DL systems, offering flexibility and scalability beyond vendor-specific libraries. This work uncovers a fundamental vulnerability in their design: can an official, unmodified compiler alter a model's semantics during compilation and introduce hidden backdoors? We study both adversarial and natural settings. In the adversarial case, we craft benign models where triggers have no effect pre-compilation but become effective backdoors af…

Lethe: Purifying Backdoored Large Language Models with Knowledge Dilution
Chen Chen, Yuchen Sun, Jiaxin Gao, Xueluan Gong, Qian Wang, Ziyao Wang, Yongsen Zheng, Kwok-Yan Lam
https://arxiv.org/abs/2508.21004

Lethe: Purifying Backdoored Large Language Models with Knowledge Dilution
Large language models (LLMs) have seen significant advancements, achieving superior performance in various Natural Language Processing (NLP) tasks. However, they remain vulnerable to backdoor attacks, where models behave normally for standard queries but generate harmful responses or unintended output when specific triggers are activated. Existing backdoor defenses either lack comprehensiveness, focusing on narrow trigger settings, detection-only mechanisms, and limited domains, or fail to with…

Faint supernovae and hyper-runaway white-dwarfs from single He-detonation in double HeCO-white-dwarf mergers
Hila Glanz, Hagai B. Perets, Aakash Bhat
https://arxiv.org/abs/2510.03396

Faint supernovae and hyper-runaway white-dwarfs from single He-detonation in double HeCO-white-dwarf mergers
We present three-dimensional hydrodynamical simulations of mergers between low-mass hybrid HeCO white dwarfs (WDs), offering new insights into the diversity of thermonuclear transients. Unlike previously studied mergers involving higher-mass HeCO WDs and CO WDs, where helium detonation often triggers core ignition, our simulations reveal incomplete helium shell detonations in comparable-mass, lower-mass WD pairs. The result is a faint, rapidly evolving transient driven by the ejection of interm…

Search for electroweak-scale dijet resonances using trigger-level analysis with the ATLAS detector in $132$ fb$^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV
ATLAS Collaboration
https://arxiv.org/abs/2509.01219

Search for electroweak-scale dijet resonances using trigger-level analysis with the ATLAS detector in $132$ fb$^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV
This article reports on a search for dijet resonances using $132$ fb$^{-1}$ of $pp$ collision data recorded at $\sqrt{s} = 13$ TeV by the ATLAS detector at the Large Hadron Collider. The search is performed solely on jets reconstructed within the ATLAS trigger to overcome bandwidth limitations imposed on conventional single-jet triggers, which would otherwise reject data from decays of sub-TeV dijet resonances. Collision events with two jets satisfying transverse momentum thresholds of $p_{\tex…

Dynamic Vulnerability Patching for Heterogeneous Embedded Systems Using Stack Frame Reconstruction
Ming Zhou, Xupu Hu, Zhihao Wang, Haining Wang, Hui Wen, Limin Sun, Peng Zhang
https://arxiv.org/abs/2509.10213

Dynamic Vulnerability Patching for Heterogeneous Embedded Systems Using Stack Frame Reconstruction
Existing dynamic vulnerability patching techniques are not well-suited for embedded devices, especially mission-critical ones such as medical equipment, as they have limited computational power and memory but uninterrupted service requirements. Those devices often lack sufficient idle memory for dynamic patching, and the diverse architectures of embedded systems further complicate the creation of patch triggers that are compatible across various system kernels and hardware platforms. To address…

The H.E.S.S. Gravitational Wave and Gamma-Ray Burst Follow-Up Programs
Bernardo Cornejo (on behalf of the H.E.S.S. Collaboration), Halim Ashkar (on behalf of the H.E.S.S. Collaboration), Matteo Cerruti (on behalf of the H.E.S.S. Collaboration), Ilja Jaroschewski (on behalf of the H.E.S.S. Collaboration), Pierre Pichard (on behalf of the H.E.S.S. Collaboration), Santiago Pita (on behalf of the H.E.S.S. Collaboration), Fabian Schussler (on behalf of the H.E.S.S. Collaboration)

The H.E.S.S. Gravitational Wave and Gamma-Ray Burst Follow-Up Programs
Multi-wavelength and multi-messenger astrophysics have experienced rapid growth over the past decade, seeking a complete picture of different cosmic phenomena. Transient sources, in particular, benefit from the input of multi-messenger observations, offering complementary perspectives on the same event while maximizing the detection probability of a rapidly fading signal. In this context, Gravitational Wave (GW) detections serve as perfect triggers for potential counterpart detections. Notably,…

ConSeg: Contextual Backdoor Attack Against Semantic Segmentation
Bilal Hussain Abbasi, Zirui Gong, Yanjun Zhang, Shang Gao, Antonio Robles-Kelly, Leo Zhang
https://arxiv.org/abs/2507.19905

ConSeg: Contextual Backdoor Attack Against Semantic Segmentation
Despite significant advancements in computer vision, semantic segmentation models may be susceptible to backdoor attacks. These attacks, involving hidden triggers, aim to cause the models to misclassify instances of the victim class as the target class when triggers are present, posing serious threats to the reliability of these models. To further explore the field of backdoor attacks against semantic segmentation, in this paper, we propose a simple yet effective backdoor attack called Contextu…

Design and deployment of a fast neural network for measuring the properties of muons originating from displaced vertices in the CMS Endcap Muon Track Finder
Efe Yigitbasi (on behalf of CMS Collaboration)
https://arxiv.org/abs/2509.21062

Design and deployment of a fast neural network for measuring the properties of muons originating from displaced vertices in the CMS Endcap Muon Track Finder
We report on the development, implementation, and performance of a fast neural network used to measure the transverse momentum in the CMS Level-1 Endcap Muon Track Finder. The network aims to improve the triggering efficiency of muons produced in the decays of long-lived particles (LLPs). We implemented it in firmware for a Xilinx Virtex-7 FPGA and deployed it during the LHC Run 3 data-taking in 2023. The new displaced muon triggers that use this algorithm broaden the phase space accessible to …

Comprehensive X-ray Observations of the Exceptional Ultra-long X-ray and Gamma-ray Transient GRB 250702B with Swift, NuSTAR, and Chandra: Insights from the X-ray Afterglow Properties
Brendan O'Connor, Ramandeep Gill, James DeLaunay, Jeremy Hare, Dheeraj Pasham, Eric R. Coughlin, Ananya Bandopadhyay, Akash Anumarlapudi, Paz Beniamini, Jonathan Granot, Igor Andreoni, Jonathan Carney, Michael J. Moss, Ersin G\"o\u{g}\"u\c{s}, Jamie A. Kennea, Malte Busmann, Simone Dichiara, …

Comprehensive X-ray Observations of the Exceptional Ultra-long X-ray and Gamma-ray Transient GRB 250702B with Swift, NuSTAR, and Chandra: Insights from the X-ray Afterglow Properties
GRB 250702B is an exceptional transient that produced multiple episodes of luminous gamma-ray radiation lasting for $>25$ ks, placing it among the class of ultra-long gamma-ray bursts (GRBs). However, unlike any known GRB, a soft X-ray precursor was discovered by the Einstein Probe up to 24 hours before the gamma-ray triggers. We present comprehensive X-ray observations of the transient's afterglow obtained with the Neil Gehrels Swift Observatory, the Nuclear Spectroscopic Telescope Array, and …

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
L\'eo Boisvert, Abhay Puri, Chandra Kiran Reddy Evuru, Nicolas Chapados, Quentin Cappart, Alexandre Lacoste, Krishnamurthy Dj Dvijotham, Alexandre Drouin
https://arxiv.org/abs/2510.05159

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
The practice of fine-tuning AI agents on data from their own interactions--such as web browsing or tool use--, while being a strong general recipe for improving agentic capabilities, also introduces a critical security vulnerability within the AI supply chain. In this work, we show that adversaries can easily poison the data collection pipeline to embed hard-to-detect backdoors that are triggerred by specific target phrases, such that when the agent encounters these triggers, it performs an uns…

P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs
Shuai Zhao, Xinyi Wu, Shiqian Zhao, Xiaobao Wu, Zhongliang Guo, Yanhao Jia, Anh Tuan Luu
https://arxiv.org/abs/2510.04503

P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs
During fine-tuning, large language models (LLMs) are increasingly vulnerable to data-poisoning backdoor attacks, which compromise their reliability and trustworthiness. However, existing defense strategies suffer from limited generalization: they only work on specific attack types or task settings. In this study, we propose Poison-to-Poison (P2P), a general and effective backdoor defense algorithm. P2P injects benign triggers with safe alternative labels into a subset of training samples and fi…

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-to-Image Diffusion Models
Yu Pan, Jiahao Chen, Lin Wang, Bingrong Dai, Yi Du
https://arxiv.org/abs/2508.03221

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-to-Image Diffusion Models
In recent years,Diffusion models have achieved remarkable progress in the field of image generation.However,recent studies have shown that diffusion models are susceptible to backdoor attacks,in which attackers can manipulate the output by injecting covert triggers such as specific visual patterns or textual phrases into the training dataset.Fortunately,with the continuous advancement of defense techniques,defenders have become increasingly capable of identifying and mitigating most backdoor at…

Environmental Rate Manipulation Attacks on Power Grid Security
Yonatan Gizachew Achamyeleh, Yang Xiang, Yun-Ping Hsiao, Yasamin Moghaddas, Mohammad Abdullah Al Faruque
https://arxiv.org/abs/2509.25476 …

Environmental Rate Manipulation Attacks on Power Grid Security
The growing complexity of global supply chains has made hardware Trojans a significant threat in sensor-based power electronics. Traditional Trojan designs depend on digital triggers or fixed threshold conditions that can be detected during standard testing. In contrast, we introduce Environmental Rate Manipulation (ERM), a novel Trojan triggering mechanism that activates by monitoring the rate of change in environmental parameters rather than their absolute values. This approach allows the Tro…