Tootfinder

Whil I'm editing photos from our vacation I quickly share this from last year for #WaterfallWednesday .
Enjoy!
#photography #nature

In line with my longtime pet issue of cascading #SystemicFailure in complex systems which we've created and come to depend upon, yet have seemingly forgotten how to maintain.
We saw a hint of what's possible in the early years of Covid when shortages rolled across the economy in unpredictable ways. I fear what might happen as the Fash keep dismantling all forms of systemic in…

Understanding AI Evaluation Patterns: How Different GPT Models Assess Vision-Language Descriptions
Sajjad Abdoli, Rudi Cilibrasi, Rima Al-Shikh
https://arxiv.org/abs/2509.10707 …

Understanding AI Evaluation Patterns: How Different GPT Models Assess Vision-Language Descriptions
As AI systems increasingly evaluate other AI outputs, understanding their assessment behavior becomes crucial for preventing cascading biases. This study analyzes vision-language descriptions generated by NVIDIA's Describe Anything Model and evaluated by three GPT variants (GPT-4o, GPT-4o-mini, GPT-5) to uncover distinct "evaluation personalities" the underlying assessment strategies and biases each model demonstrates. GPT-4o-mini exhibits systematic consistency with minimal variance, GPT-4o ex…

Research on fault diagnosis and root cause analysis based on full stack observability
Jian Hou
https://arxiv.org/abs/2509.12231 https://arxiv.org/pdf/2509.…

Research on fault diagnosis and root cause analysis based on full stack observability
With the rapid development of cloud computing and ultra-large-scale data centers, the scale and complexity of systems have increased significantly, leading to frequent faults that often show cascading propagation. How to achieve efficient, accurate, and interpretable Root Cause Analysis (RCA) based on observability data (metrics, logs, traces) has become a core issue in AIOps. This paper reviews two mainstream research threads in top conferences and journals over the past five years: FaultInsig…

Real-Time Defense Against Coordinated Cyber-Physical Attacks: A Robust Constrained Reinforcement Learning Approach
Saman Mazaheri Khamaneh, Tong Wu, Wei Sun, Cong Chen
https://arxiv.org/abs/2509.10999 …

Real-Time Defense Against Coordinated Cyber-Physical Attacks: A Robust Constrained Reinforcement Learning Approach
Modern power systems face increasing vulnerability to sophisticated cyber-physical attacks beyond traditional N-1 contingency frameworks. Existing security paradigms face a critical bottleneck: efficiently identifying worst-case scenarios and rapidly coordinating defensive responses are hindered by intensive computation and time delays, during which cascading failures can propagate. This paper presents a novel tri-level robust constrained reinforcement learning (RCRL) framework for robust power…

Resilient-native and Intelligent NextG Systems
Mehdi Bennis
https://arxiv.org/abs/2506.12795 https://arxiv.org/pdf/2506.12795

Resilient-native and Intelligent NextG Systems
Just like power, water and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless networks must be resilient to unforeseen events, able to withstand and recover from unexpected adverse conditions, shocks, unmodeled disturbances and cascading failures. Despite its critical importance, resilience remains an elusive concept, with its mathematical foundations still underdeveloped. Unlike robustness and rel…

Nice, #Python 3.9 is very soon EOL [1], so it is finally fine to use Structural Pattern Matching [2] (i.e. the `match` statement, a `switch` on steroids) everywhere! 🥳
[1] https://devguide.python.org/versions/

Estimating the size of a set using cascading exclusion
Sourav Chatterjee, Persi Diaconis, Susan Holmes
https://arxiv.org/abs/2508.05901 https://arxiv.org/p…

Estimating the size of a set using cascading exclusion
Let $S$ be a finite set, and $X_1,\ldots,X_n$ an i.i.d. uniform sample from $S$. To estimate the size $|S|$, without further structure, one can wait for repeats and use the birthday problem. This requires a sample size of the order $|S|^\frac{1}{2}$. On the other hand, if $S=\{1,2,\ldots,|S|\}$, the maximum of the sample blown up by $n/(n-1)$ gives an efficient estimator based on any growing sample size. This paper gives refinements that interpolate between these e…

LA-CaRe-CNN: Cascading Refinement CNN for Left Atrial Scar Segmentation
Franz Thaler, Darko Stern, Gernot Plank, Martin Urschler
https://arxiv.org/abs/2508.04553 https://…

LA-CaRe-CNN: Cascading Refinement CNN for Left Atrial Scar Segmentation
Atrial fibrillation (AF) represents the most prevalent type of cardiac arrhythmia for which treatment may require patients to undergo ablation therapy. In this surgery cardiac tissues are locally scarred on purpose to prevent electrical signals from causing arrhythmia. Patient-specific cardiac digital twin models show great potential for personalized ablation therapy, however, they demand accurate semantic segmentation of healthy and scarred tissue typically obtained from late gadolinium enhanc…

Semantic Causality-Aware Vision-Based 3D Occupancy Prediction
Dubing Chen, Huan Zheng, Yucheng Zhou, Xianfei Li, Wenlong Liao, Tao He, Pai Peng, Jianbing Shen
https://arxiv.org/abs/2509.08388

Semantic Causality-Aware Vision-Based 3D Occupancy Prediction
Vision-based 3D semantic occupancy prediction is a critical task in 3D vision that integrates volumetric 3D reconstruction with semantic understanding. Existing methods, however, often rely on modular pipelines. These modules are typically optimized independently or use pre-configured inputs, leading to cascading errors. In this paper, we address this limitation by designing a novel causal loss that enables holistic, end-to-end supervision of the modular 2D-to-3D transformation pipeline. Ground…

Multi-User Contextual Cascading Bandits for Personalized Recommendation
Jiho Park, Huiwen Jia
https://arxiv.org/abs/2508.13981 https://arxiv.org/pdf/2508.1…

Multi-User Contextual Cascading Bandits for Personalized Recommendation
We introduce a Multi-User Contextual Cascading Bandit model, a new combinatorial bandit framework that captures realistic online advertising scenarios where multiple users interact with sequentially displayed items simultaneously. Unlike classical contextual bandits, MCCB integrates three key structural elements: (i) cascading feedback based on sequential arm exposure, (ii) parallel context sessions enabling selective exploration, and (iii) heterogeneous arm-level rewards. We first propose Uppe…

A Spatiotemporal Adaptive Local Search Method for Tracking Congestion Propagation in Dynamic Networks
Weihua Huan, Kaizhen Tan, Xintao Liu, Shoujun Jia, Shijun Lu, Jing Zhang, Wei Huang
https://arxiv.org/abs/2509.06099

A Spatiotemporal Adaptive Local Search Method for Tracking Congestion Propagation in Dynamic Networks
Traffic congestion propagation poses significant challenges to urban sustainability, disrupting spatial accessibility. The cascading effect of traffic congestion propagation can cause large-scale disruptions to networks. Existing studies have laid a solid foundation for characterizing the cascading effects. However, they typically rely on predefined graph structures and lack adaptability to diverse data granularities. To address these limitations, we propose a spatiotemporal adaptive local sear…

🔧 #ccundo – Intelligent undo for Claude Code sessions
* Reads directly from Claude Code session files to track operations
* Provides granular undo/redo with cascading safety & detailed previews
* Supports file edits, creations, deletions & bash commands
* Zero configuration – works out of the box

Generative Bid Shading in Real-Time Bidding Advertising
Yinqiu Huang, Hao Ma, Wenshuai Chen, Shuli Wang, Yongqiang Zhang, Xue Wei, Yinhua Zhu, Haitao Wang, Xingxing Wang
https://arxiv.org/abs/2508.06550

Generative Bid Shading in Real-Time Bidding Advertising
Bid shading plays a crucial role in Real-Time Bidding~(RTB) by adaptively adjusting the bid to avoid advertisers overspending. Existing mainstream two-stage methods, which first model bid landscapes and then optimize surplus using operations research techniques, are constrained by unimodal assumptions that fail to adapt for non-convex surplus curves and are vulnerable to cascading errors in sequential workflows. Additionally, existing discretization models of continuous values ignore the depend…

Cascading and Proxy Membership Inference Attacks
Yuntao Du, Jiacheng Li, Yuetian Chen, Kaiyuan Zhang, Zhizhen Yuan, Hanshen Xiao, Bruno Ribeiro, Ninghui Li
https://arxiv.org/abs/2507.21412

Cascading and Proxy Membership Inference Attacks
A Membership Inference Attack (MIA) assesses how much a trained machine learning model reveals about its training data by determining whether specific query instances were included in the dataset. We classify existing MIAs into adaptive or non-adaptive, depending on whether the adversary is allowed to train shadow models on membership queries. In the adaptive setting, where the adversary can train shadow models after accessing query instances, we highlight the importance of exploiting membershi…

The Spontaneous Cascading Mechanism Behind Critical Phenomena in Self-Coupled Lasers
Jiaoqing Wang, Yael Kfir-Cohen, Chenni Xu, Bnaya Gross, Aswathy Sundaresan, Shlomo Havlin, Patrick Sebbah
https://arxiv.org/abs/2508.21786

The Spontaneous Cascading Mechanism Behind Critical Phenomena in Self-Coupled Lasers
The basic physics of lasers is characterized by a second-order continuous phase transition at the critical lasing threshold. Nevertheless, laser bistability with abrupt transitions has been reported in some laser systems, but its underlying mechanism has never been explored. Here we study experimentally and theoretically a novel nonlinearly self-coupled laser system. We show both experimentally and theoretically that this system experiences spontaneous cascading that yields an abrupt mixed-orde…

Cascading from the winds to the disk: the universality of supernovae-driven turbulence in different galactic interstellar mediums
Isabelle Connor, James R. Beattie, Anne Noer Kolborg, Enrico Ramirez-Ruiz
https://arxiv.org/abs/2509.01653

Cascading from the winds to the disk: the universality of supernovae-driven turbulence in different galactic interstellar mediums
Star-forming galaxies are in a state of turbulence, with one of the principle components of the turbulence sourced by the constant injection of momentum from supernovae (SNe) explosions. Utilizing high-resolution stratified, gravito-hydrodynamical models of SNe-driven turbulence with interstellar medium (ISM) cooling and heating, we explore how SNe-driven turbulence changes across different galactic conditions, parameterized by the galactic mass and potential, SNe-driving rate, and seeding func…

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations
Saurabhsingh Rajput, Mootez Saad, Tushar Sharma
https://arxiv.org/abs/2506.18289

Tu(r)ning AI Green: Exploring Energy Efficiency Cascading with Orthogonal Optimizations
AI's exponential growth intensifies computational demands and energy challenges. While practitioners employ various optimization techniques, that we refer as "knobs" in this paper, to tune model efficiency, these are typically afterthoughts and reactive ad-hoc changes applied in isolation without understanding their combinatorial effects on energy efficiency. This paper emphasizes on treating energy efficiency as the first-class citizen and as a fundamental design consideration for a compute-in…

A Self-Organized Criticality Model of Extreme Events and Cascading Disasters of Hub and Spoke Air Traffic Networks
Mary Lai O. Salva\~na, Harold Jay M. Bolingot, Gregory L. Tangonan
https://arxiv.org/abs/2506.16727

A Self-Organized Criticality Model of Extreme Events and Cascading Disasters of Hub and Spoke Air Traffic Networks
Critical infrastructure networks--including transportation, power grids, and communication systems--exhibit complex interdependencies that can lead to cascading failures with catastrophic consequences. These disasters often originate from failures at critical points in the network, where single-node disruptions can propagate rapidly due to structural dependencies and high-impact linkages. Such vulnerabilities are exacerbated in systems that have been highly optimized for efficiency or have self…

Distributionally Robust Cascading Risk Quantification in Multi-Agent Rendezvous: Effects of Time Delay and Network Connectivity
Vivek Pandey, Nader Motee
https://arxiv.org/abs/2507.23489

Distributionally Robust Cascading Risk Quantification in Multi-Agent Rendezvous: Effects of Time Delay and Network Connectivity
Achieving safety in autonomous multi-agent systems, particularly in time-critical tasks like rendezvous, is a critical challenge. In this paper, we propose a distributionally robust risk framework for analyzing cascading failures in multi-agent rendezvous. To capture the complex interactions between network connectivity, system dynamics, and communication delays, we use a time-delayed network model as a benchmark. We introduce a conditional distributionally robust functional to quantify cascadi…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[4/6]:
- A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Langu...
Miao Zhang, Zhenlong Fang, Tianyi Wang, Qian Zhang, Shuai Lu, Junfeng Jiao, Tianyu Shi

Energy Cascade and Damping in Fast-Mode Compressible Turbulence
Chuanpeng Hou, Huirong Yan, Siqi Zhao, Parth Pavaskar
https://arxiv.org/abs/2508.03443 https://

Energy Cascade and Damping in Fast-Mode Compressible Turbulence
This letter presents hybrid and fully kinetic particle-in-cell simulations of fast-mode compressible turbulence. Turbulence damping at magnetohydrodynamic (MHD) scales closely follows linear transit-time damping theory. Despite strong phase steepening, turbulence sustains robust cross-scale energy cascading. These findings resolve the long-standing question about the validity of classical wave theories in strongly nonlinear regimes and overturn the common presumption that wave steepening disrup…

OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Ben Chen, Xian Guo, Siyuan Wang, Zihan Liang, Yue Lv, Yufei Ma, Xinlong Xiao, Bowen Xue, Xuxin Zhang, Ying Yang, Huangyu Dai, Xing Xu, Tong Zhao, Mingcan Peng, XiaoYang Zheng, Cong Zhang, Qihang Zhao, Yuqing Ding, Chenyi Lei, Wenwu Ou, Han Li
https://

OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Traditional e-commerce search systems employ multi-stage cascading architectures (MCA) that progressively filter items through recall, pre-ranking, and ranking stages. While effective at balancing computational efficiency with business conversion, these systems suffer from fragmented computation and optimization objective collisions across stages, which ultimately limit their performance ceiling. To address these, we propose \textbf{OneSearch}, the first industrial-deployed end-to-end generativ…

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- Cascading CMA-ES Instances for Generating Input-diverse Solution Batches
Maria Laura Santoni, Christoph D\"urr, Carola Doerr, Mike Preuss, Elena Raponi

Thekla Reuten

Stationary Power-Law Solutions of Kinetic-Alfv\'{e}nic Turbulence
Kexun Shen, Zhiwen Cheng, Zhiyong Qiu
https://arxiv.org/abs/2508.03478 https://arxiv.…

Stationary Power-Law Solutions of Kinetic-Alfvénic Turbulence
The wave-kinetic description of weak kinetic-Alfvénic turbulence based on the gyrokinetic theoretical framework is proposed. The wave kinetic equation describing kinetic Alfvén wave spectral cascading via resonant three-wave interactions is derived, and the stationary spectra are analytically obtained using the Zakharov transformation in both the long-wavelength limit and the short-wavelength limit, for both counter-propagating and co-propagating cases. The cascade directions of stationary so…

Learning From the Past with Cascading Eligibility Traces
Tokiniaina Raharison Ralambomihanta, Ivan Anokhin, Roman Pogodin, Samira Ebrahimi Kahou, Jonathan Cornford, Blake Aaron Richards
https://arxiv.org/abs/2506.14598

Learning From the Past with Cascading Eligibility Traces
Animals often receive information about errors and rewards after a significant delay. For example, there is typically a delay of tens to hundreds of milliseconds between motor actions and visual feedback. The standard approach to handling delays in models of synaptic plasticity is to use eligibility traces. However, standard eligibility traces that decay exponentially mix together any events that happen during the delay, presenting a problem for any credit assignment signal that occurs with a s…

Quantification of the cascading tipping probability from the AMOC to the Amazon rainforest
Val\'erian Jacques-Dumas, Henk A. Dijkstra
https://arxiv.org/abs/2508.13383 https:…

Quantification of the cascading tipping probability from the AMOC to the Amazon rainforest
The Amazon rainforest and the AMOC are two key components of the Earth system and may both collapse under climate change. Due to its influence on precipitation patterns, a collapsed AMOC influences the dynamics of the Amazon rainforest. We investigate this effect using a coupled conceptual AMOC-Amazon model. The Amazon model is based on empirical hydrological data controlled by the AMOC strength. The AMOC model and its influence on the Amazon are tuned using a simulated AMOC collapse in the Com…

A Multi-Model Probabilistic Framework for Seismic Risk Assessment and Retrofit Planning of Electric Power Networks
Huangbin Liang, Beatriz Moya, Francisco Chinesta, Eleni Chatzi
https://arxiv.org/abs/2508.07376

A Multi-Model Probabilistic Framework for Seismic Risk Assessment and Retrofit Planning of Electric Power Networks
Electric power networks are critical lifelines, and their disruption during earthquakes can lead to severe cascading failures and significantly hinder post-disaster recovery. Enhancing their seismic resilience requires identifying and strengthening vulnerable components in a cost-effective and system-aware manner. However, existing studies often overlook the systemic behavior of power networks under seismic loading. Common limitations include isolated component analyses that neglect network-wid…

Oh #waterfallWednesday! I almost missed it again.
I hope you enjoy it. And it also reminds me that I wanted to visit that place again. Especially now as it rained so much.
#waterfall #photography

FlipWalker: Jacob's Ladder toy-inspired robot for locomotion across diverse, complex terrain
Diancheng Li, Nia Ralston, Bastiaan Hagen, Phoebe Tan, Matthew A. Robertson
https://arxiv.org/abs/2508.19380

FlipWalker: Jacob's Ladder toy-inspired robot for locomotion across diverse, complex terrain
This paper introduces FlipWalker, a novel underactuated robot locomotion system inspired by Jacob's Ladder illusion toy, designed to traverse challenging terrains where wheeled robots often struggle. Like the Jacob's Ladder toy, FlipWalker features two interconnected segments joined by flexible cables, enabling it to pivot and flip around singularities in a manner reminiscent of the toy's cascading motion. Actuation is provided by motor-driven legs within each segment that push off either the g…

Predicting any small-scale statistics of high-Reynolds-number turbulence using ensemble simulations
Lukas Bentkamp, Michael Wilczek
https://arxiv.org/abs/2506.23712

Predicting any small-scale statistics of high-Reynolds-number turbulence using ensemble simulations
The complex small-scale statistics of turbulence are a result of the combined cascading dynamics through all scales of the flow. Predicting these statistics using fully resolved simulations at the high Reynolds numbers that typically occur in engineering, geophysical, and astrophysical flows will exceed the capabilities of even the largest supercomputers for the foreseeable future. A common observation is that high-Reynolds-number flows are organized in clusters of intense turbulent activity se…

Gravity, finite duality cascades and confinement
Fabrizio Aramini, Riccardo Argurio, Matteo Bertolini, Eduardo Garc\'ia-Valdecasas, Pietro Moroni
https://arxiv.org/abs/2506.18988

Gravity, finite duality cascades and confinement
Cascading RG flows are characteristic of $\mathcal{N}=1$ gauge theories realized by D3-branes probing singularities in the presence of fractional branes. A celebrated example is the Klebanov-Strassler model, which exhibits an infinite cascade that ends with confinement. In this work, we explore a related setup where the addition of an orientifold plane modifies the cascade structure: the RG flow now consists of a finite number of steps, originating from a UV fixed point with a finite number of …

Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications
Mehdi Bennis, Sumudu Samarakoon, Tamara Alshammari, Chathuranga Weeraddana, Zhoujun Tian, Chaouki Ben Issaid
https://arxiv.org/abs/2506.22991

Resilient-Native and Intelligent Next-Generation Wireless Systems: Key Enablers, Foundations, and Applications
Just like power, water, and transportation systems, wireless networks are a crucial societal infrastructure. As natural and human-induced disruptions continue to grow, wireless networks must be resilient. This requires them to withstand and recover from unexpected adverse conditions, shocks, unmodeled disturbances and cascading failures. Unlike robustness and reliability, resilience is based on the understanding that disruptions will inevitably happen. Resilience, as elasticity, focuses on the …

Cascading nuclear excitation of \(^{235}\text{U}\) via inelastic electron scattering in laser-irradiated clusters
Qiong Xiao, Yangyang Xu, Junhao Cheng, Liangqi Zhang, Wenyu Zhang, Yongsheng Huang, Tongpu Yu
https://arxiv.org/abs/2508.18336

Cascading nuclear excitation of \(^{235}\text{U}\) via inelastic electron scattering in laser-irradiated clusters
Nuclear excitation induced by lasers holds broad application prospects in precision metrology and nuclear energy, such as nuclear batteries and nuclear clocks. In the present work, the nuclear excitation via inelastic electron scattering (NEIES) mechanism in \(^{235}\text{U}\) is investigated by combining the Dirac-Hartree-Fock-Slater method for theoretical calculations with 2D3V particle-in-cell (PIC) simulations for numerical modeling. The excitation cross-sections of \(^{235}\text{U}\) from …

Assessing the Macroeconomic Impacts of Disasters: an Updated Multi-Regional Impact Assessment (MRIA) model
Surender Raj Vanniya Perumal, Mark Thissen, Marleen de Ruiter, Elco E. Koks
https://arxiv.org/abs/2508.00510

Assessing the Macroeconomic Impacts of Disasters: an Updated Multi-Regional Impact Assessment (MRIA) model
Disasters often impact supply chains, leading to cascading effects across regions. While unaffected regions may attempt to compensate, their ability is constrained by their available production capacity and logistical constraints between regions. This study introduces a Multi-Regional Impact Assessment (MRIA) model to evaluate the regional and macroeconomic consequences of disasters, capturing regional post-disaster trade dynamics and logistical constraints. Our findings emphasize that enhancin…

AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction
Song Wang, Zhen Tan, Zihan Chen, Shuang Zhou, Tianlong Chen, Jundong Li
https://arxiv.org/abs/2506.17784

AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction
Recent progress in large language model (LLM)-based multi-agent collaboration highlights the power of structured communication in enabling collective intelligence. However, existing methods largely rely on static or graph-based inter-agent topologies, lacking the potential adaptability and flexibility in communication. In this work, we propose a new framework that rethinks multi-agent coordination through a sequential structure rather than a graph structure, offering a significantly larger topo…

The Aegis Protocol: A Foundational Security Framework for Autonomous AI Agents
Sai Teja Reddy Adapala, Yashwanth Reddy Alugubelly
https://arxiv.org/abs/2508.19267 https://

The Aegis Protocol: A Foundational Security Framework for Autonomous AI Agents
The proliferation of autonomous AI agents marks a paradigm shift toward complex, emergent multi-agent systems. This transition introduces systemic security risks, including control-flow hijacking and cascading failures, that traditional cybersecurity paradigms are ill-equipped to address. This paper introduces the Aegis Protocol, a layered security framework designed to provide strong security guarantees for open agentic ecosystems. The protocol integrates three technological pillars: (1) non-s…

Day 11
Well, technically it’s been a few days.
I just finished populating the entire partner-contracts layer in our system. That means hundreds of users, each linked to the correct unit, with the proper supervisor, job title, and contract type. All of it reflected in a single, consistent data model.
Every user has a contract pointing to their supervisor — with cascading relations:
- regional managers report directly to the admin,
- unit managers report to regional …

Crosslisted article(s) found for physics.comp-ph. https://arxiv.org/list/physics.comp-ph/new
[1/1]:
- Quantification of the cascading tipping probability from the AMOC to the Amazon rainforest
Val\'erian Jacques-Dumas, Henk A. Dijkstra

ANSC: Probabilistic Capacity Health Scoring for Datacenter-Scale Reliability
Madhava Gaikwad, Abhishek Gandhi
https://arxiv.org/abs/2508.16119 https://arxi…

ANSC: Probabilistic Capacity Health Scoring for Datacenter-Scale Reliability
We present ANSC, a probabilistic capacity health scoring framework for hyperscale datacenter fabrics. While existing alerting systems detect individual device or link failures, they do not capture the aggregate risk of cascading capacity shortfalls. ANSC provides a color-coded scoring system that indicates the urgency of issues \emph{not solely by current impact, but by the probability of imminent capacity violations}. Our system accounts for both current residual capacity and the probability o…

Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation
Hengyu Zhang, Chunxu Shen, Xiangguo Sun, Jie Tan, Yanchao Tan, Yu Rong, Hong Cheng, Lingling Yi
https://arxiv.org/abs/2507.15395

Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation
In real-world recommendation scenarios, users typically engage with platforms through multiple types of behavioral interactions. Multi-behavior recommendation algorithms aim to leverage various auxiliary user behaviors to enhance prediction for target behaviors of primary interest (e.g., buy), thereby overcoming performance limitations caused by data sparsity in target behavior records. Current state-of-the-art approaches typically employ hierarchical design following either cascading (e.g., vi…

Phase Matched Plasmonic Transmission Lines for Cascaded Second-Harmonic Generation as a Pathway to Nonlinear Logic Circuits
Komal Gupta, Anand Hegde, Xiaofei Wu, Jer-Shing Huang, Chen-Bin Huang
https://arxiv.org/abs/2508.15188

Phase Matched Plasmonic Transmission Lines for Cascaded Second-Harmonic Generation as a Pathway to Nonlinear Logic Circuits
In nonlinear nanophotonics, cascaded second-harmonic generation (SHG) in pure plasmonic waveguides for sequential signal transformation and complex on-chip functionality remains a long-standing challenge. Precise phase matching becomes instrumental to achieve efficient SHG and enable true cascading of nonlinear processes. We experimentally demonstrate phase matching in SHG is achievable in a plasmonic system between two orthogonal modes. Accurate tuning of plasmonic two-wire transmission-line (…

I have a lot of cool pictures to share from hikes and such, but first I have some stylesheets with cascading speculations to fight, I mean write. 😟
#technology #webdev #programming #life #nerd