Tootfinder

Cave of wonders.
2 Free wallpapers for you to use.
Also uploaded to my Ko-fi completely uncompressed for free here: #AIart

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Coherent transceiver architecture enabling data transmission and optical identification
Stella Civelli, Marco Secondini, Pantea Nadimi Goki, Luca Pot\`i
https://arxiv.org/abs/2404.05278

Coherent transceiver architecture enabling data transmission and optical identification
We propose a coherent transceiver architecture able to transmit information and enhance the security of the optical network by identifying other optical systems and subsystems. Simulations show that identification is obtained with sufficient reliability in standard operating conditions.

You Only Cache Once: Decoder-Decoder Architectures for Language Models
Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei
https://arxiv.org/abs/2405.05254

You Only Cache Once: Decoder-Decoder Architectures for Language Models
We introduce a decoder-decoder architecture, YOCO, for large language models, which only caches key-value pairs once. It consists of two components, i.e., a cross-decoder stacked upon a self-decoder. The self-decoder efficiently encodes global key-value (KV) caches that are reused by the cross-decoder via cross-attention. The overall model behaves like a decoder-only Transformer, although YOCO only caches once. The design substantially reduces GPU memory demands, yet retains global attention ca…

"So I don’t know exactly where the media industry went, and I don’t know how to fix it. But if you want a glimpse of how the business works now, you can’t do much better than this Road & Track story about Formula One racing by McMansion Hell architecture critic and cycling journalist Kate Wagner, which was published on Friday and then almost instantly unpublished for reasons that will soon become obvious." https://web.archive.org/web/20240301170542/https://www.roadandtrack.com/car-culture/a46975496/behind-f1-velvet-curtain/

You Only Cache Once: Decoder-Decoder Architectures for Language Models
Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei
https://arxiv.org/abs/2405.05254

You Only Cache Once: Decoder-Decoder Architectures for Language Models
We introduce a decoder-decoder architecture, YOCO, for large language models, which only caches key-value pairs once. It consists of two components, i.e., a cross-decoder stacked upon a self-decoder. The self-decoder efficiently encodes global key-value (KV) caches that are reused by the cross-decoder via cross-attention. The overall model behaves like a decoder-only Transformer, although YOCO only caches once. The design substantially reduces GPU memory demands, yet retains global attention ca…

I read 'Towards a National Data Architecture for Cultural Collections: Designing the Australian Cultural Data Engine' https://www.digitalhumanities.org/dhq/vol/18/2/000678/000678.html

This https://arxiv.org/abs/2405.01242 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
We propose TRAMBA, a hybrid transformer and Mamba architecture for acoustic and bone conduction speech enhancement, suitable for mobile and wearable platforms. Bone conduction speech enhancement has been impractical to adopt in mobile and wearable platforms for several reasons: (i) data collection is labor-intensive, resulting in scarcity; (ii) there exists a performance gap between state of-art models with memory footprints of hundreds of MBs and methods better suited for resource-constrained …

The ocean is already full of these wave gliders. I know somebody who has worked on them. They have been around for 15 years.
https://www.liquid-robotics.com/wave-glider/how-it-works/

The Wave Glider | How It Works
Take a closer look at our unmanned surface vehicle’s groundbreaking advancements in energy harvesting, propulsion, and payload and sensor architecture.

Deep dive on #Bluesky's architecture and its history. I have lots of opinions and conjectures but let’s let them finish telling their story first: https://newsletter.pragmaticengineer.c…

Building Bluesky: a Distributed Social Network (Real-World Engineering Challenges)
Bluesky is built by around 10 engineers, and has amassed 5 million users since publicly launching in February this year. A deep dive into novel design decisions, moving off AWS, and more.

This https://arxiv.org/abs/2310.03299 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dynamical Architectures of S-type Transiting Planets in Binaries I: Target Selection using Hipparcos and Gaia proper motion anomalies
The effect of stellar multiplicity on planetary architecture and orbital dynamics provides an important context for exoplanet demographics. We present a volume-limited catalog up to 300 pc of 66 stars hosting planets and planet candidates from Kepler, K2 and TESS with significant Hipparcos-Gaia proper motion anomalies, which indicate the presence of companions. We assess the reliability of each transiting planet candidate using ground-based follow-up observations, and find that the TESS Objects…

so apparently k3s was crashing badly, producing torrents of stacktraces where the only clue I found so far is “fatal error: invalid g status", which led me to an issue in the Go repo https://github.com/golang/go/issues/52560 that vaguely hints at memory corruption.
yay, I…

process crash in go runtime with "fatal error: invalid g status" · Issue #52560 · golang/go
What version of Go are you using (go version)? $ go version go version go1.17.2 linux/amd64 Does this issue reproduce with the latest release? What operating system and processor architecture are y...

As a gentleman of a certain age it's probably time I knew this
From: @…
https://flipboard.social/@sidewalksafari/…

A really nice summary of the architecture of Mastodon and of the benefits and challenges of federated social media at scale.
https://infosec.exchange/@mrazeeq/112113253763458259

OzMAC: An Energy-Efficient Sparsity-Exploiting Multiply-Accumulate-Unit Design for DL Inference
Harideep Nair, Prabhu Vellaisamy, Tsung-Han Lin, Perry Wang, Shawn Blanton, John Paul Shen
https://arxiv.org/abs/2402.19376

OzMAC: An Energy-Efficient Sparsity-Exploiting Multiply-Accumulate-Unit Design for DL Inference
General Matrix Multiply (GEMM) hardware, employing large arrays of multiply-accumulate (MAC) units, perform bulk of the computation in deep learning (DL). Recent trends have established 8-bit integer (INT8) as the most widely used precision for DL inference. This paper proposes a novel MAC design capable of dynamically exploiting bit sparsity (i.e., number of `0' bits within a binary value) in input data to achieve significant improvements on area, power and energy. The proposed architecture, c…

This https://arxiv.org/abs/1809.02467 has been replaced.
link: https://scholar.google.com/scholar?q=a

Design and testing of 3D-printed micro-architectured polymer materials exhibiting a negative Poisson's ratio
This work proposes the complete design cycle for several auxetic materials where the cycle consists of three steps (i) the design of the micro-architecture, (ii) the manufacturing of the material and (iii) the testing of the material. We use topology optimization via a level-set method and asymptotic homogenization to obtain periodic micro-architectured materials with a prescribed effective elasticity tensor and Poisson's ratio. The space of admissible micro-architectural shapes that carries or…

This https://arxiv.org/abs/2401.00096 has been replaced.
initial toot: https://mastoxiv.page/@ar…

A foundation model for atomistic materials chemistry
Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations of ab initio quality on unprecedented time and length scales. However, they are currently limited by: (i) the significant computational and human effort that must go into development and validation of potentials for each particular system of interest; and (ii) a general lack of transferability from one chemical system to the next. Here, using the state-of-the-art MACE architecture we intro…

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
Yueyuan Sui, Minghui Zhao, Junxi Xia, Xiaofan Jiang, Stephen Xia
https://arxiv.org/abs/2405.01242

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
We propose TRAMBA, a hybrid transformer and Mamba architecture for acoustic and bone conduction speech enhancement, suitable for mobile and wearable platforms. Bone conduction speech enhancement has been impractical to adopt in mobile and wearable platforms for several reasons: (i) data collection is labor-intensive, resulting in scarcity; (ii) there exists a performance gap between state of-art models with memory footprints of hundreds of MBs and methods better suited for resource-constrained …

Leveraging power of deep learning for fast and efficient elite pixel selection in time series SAR interferometry
Ashutosh Tiwari, Nitheshnirmal Sadhashivam, Leonard O. Ohenhen, Manoochehr Shirzaei
https://arxiv.org/abs/2402.17069

Leveraging power of deep learning for fast and efficient elite pixel selection in time series SAR interferometry
This work proposes an improved convolutional long short-term memory (ConvLSTM) based architecture for selection of elite pixels (i.e., less noisy) in time series interferometric synthetic aperture radar (TS-InSAR). Compared to previous version, the model can process InSAR stacks of variable time steps and select both persistent (PS) and distributed scatterers (DS). We trained the model on ~20,000 training images (interferograms), each of size 100 by 100 pixels, extracted from InSAR time series …

stealing this image. super useful. thank you @… https://dan.mastohon.com/@danhon/111903226826438493

Dan Hon (@danhon@dan.mastohon.com)
Attached: 1 image man I really hate Plex sometimes, they did all this stuff with upgrading their agent architecture and now the metadata for a bunch of my tv shows is completely broken

This https://arxiv.org/abs/2310.03299 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Dynamical Architectures of S-type Transiting Planets in Binaries I: Target Selection using Hipparcos and Gaia proper motion anomalies
The effect of stellar multiplicity on planetary architecture and orbital dynamics provides an important context for exoplanet demographics. We present a volume-limited catalog up to 300 pc of 66 stars hosting planets and planet candidates from Kepler, K2 and TESS with significant Hipparcos-Gaia proper motion anomalies, which indicate the presence of companions. We assess the reliability of each transiting planet candidate using ground-based follow-up observations, and find that the TESS Objects…

#Deutschland unter #Waffen
#Nazi
https://…

Entanglement Renormalization for Quantum Field Theories with Discrete Wavelet Transforms
Daniele S. M. Alves
https://arxiv.org/abs/2404.11715 https://

Entanglement Renormalization for Quantum Field Theories with Discrete Wavelet Transforms
We propose an adaptation of Entanglement Renormalization for quantum field theories that, through the use of discrete wavelet transforms, strongly parallels the tensor network architecture of the \emph{Multiscale Entanglement Renormalization Ansatz} (a.k.a. MERA). Our approach, called wMERA, has several advantages of over previous attempts to adapt MERA to continuum systems. In particular, (i) wMERA is formulated directly in position space, hence preserving the quasi-locality and sparsity of en…

Contrastive Quantization based Semantic Code for Generative Recommendation
Mengqun Jin, Zexuan Qiu, Jieming Zhu, Zhenhua Dong, Xiu Li
https://arxiv.org/abs/2404.14774

Contrastive Quantization based Semantic Code for Generative Recommendation
With the success of large language models, generative retrieval has emerged as a new retrieval technique for recommendation. It can be divided into two stages: the first stage involves constructing discrete Codes (i.e., codes), and the second stage involves decoding the code sequentially via the transformer architecture. Current methods often construct item semantic codes by reconstructing based quantization on item textual representation, but they fail to capture item discrepancy that is essen…

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
Yueyuan Sui, Minghui Zhao, Junxi Xia, Xiaofan Jiang, Stephen Xia
https://arxiv.org/abs/2405.01242

TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms
We propose TRAMBA, a hybrid transformer and Mamba architecture for acoustic and bone conduction speech enhancement, suitable for mobile and wearable platforms. Bone conduction speech enhancement has been impractical to adopt in mobile and wearable platforms for several reasons: (i) data collection is labor-intensive, resulting in scarcity; (ii) there exists a performance gap between state of-art models with memory footprints of hundreds of MBs and methods better suited for resource-constrained …

Self-adaptive, Requirements-driven Autoscaling of Microservices
Jo\~ao Paulo Karol Santos Nunes, Shiva Nejati, Mehrdad Sabetzadeh, Elisa Yumi Nakagawa
https://arxiv.org/abs/2403.08798

Self-adaptive, Requirements-driven Autoscaling of Microservices
Microservices architecture offers various benefits, including granularity, flexibility, and scalability. A crucial feature of this architecture is the ability to autoscale microservices, i.e., adjust the number of replicas and/or manage resources. Several autoscaling solutions already exist. Nonetheless, when employed for diverse microservices compositions, current solutions may exhibit suboptimal resource allocations, either exceeding the actual requirements or falling short. This can in turn …

This https://arxiv.org/abs/2403.17142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Approximation with Random Shallow ReLU Networks with Applications to Model Reference Adaptive Control
Neural networks are regularly employed in adaptive control of nonlinear systems and related methods of reinforcement learning. A common architecture uses a neural network with a single hidden layer (i.e. a shallow network), in which the weights and biases are fixed in advance and only the output layer is trained. While classical results show that there exist neural networks of this type that can approximate arbitrary continuous functions over bounded regions, they are non-constructive, and the …

A Digital Twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle
Mohamed AbdElSalam, Loai Ali, Saddek Bensalem, Weicheng He, Panagiotis Katsaros, Nikolaos Kekatos, Doron Peled, Anastasios Temperekidis, Changshun Wu
https://arxiv.org/abs/2402.09097

A Digital Twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle
In this paper, we present a novel digital twin prototype for a learning-enabled self-driving vehicle. The primary objective of this digital twin is to perform traffic sign recognition and lane keeping. The digital twin architecture relies on co-simulation and uses the Functional Mock-up Interface and SystemC Transaction Level Modeling standards. The digital twin consists of four clients, i) a vehicle model that is designed in Amesim tool, ii) an environment model developed in Prescan, iii) a la…

Designing high-fidelity two-qubit gates between fluxonium qubits
Emma L. Rosenfeld, Connor T. Hann, David I. Schuster, Matthew H. Matheny, Aashish A. Clerk
https://arxiv.org/abs/2403.07242

Designing high-fidelity two-qubit gates between fluxonium qubits
We take a bottom-up, first-principles approach to design a two-qubit gate between fluxonium qubits for minimal error, speed, and control simplicity. Our proposed architecture consists of two fluxoniums coupled via a linear resonator. Using a linear coupler introduces the possibility of material optimization for suppressing its loss, enables efficient driving of state-selective transitions through its large charge zero point fluctuation, reduces sensitivity to junction aging, and partially mitig…

O-RAN for Energy-Efficient Serving Cluster Formulation in User-Centric Cell-Free MMIMO
Marcin Hoffmann, Pawe{\l} Kryszkiewicz
https://arxiv.org/abs/2403.19449

O-RAN for Energy-Efficient Serving Cluster Formulation in User-Centric Cell-Free MMIMO
The 6G Massive Multiple-Input Multiple-Output (MMIMO) networks can follow the so-called User-Centric Cell-Free (UCCF) architecture, where a single user is served by multiple Access Points (APs) coordinated by the Central Processing Unit (CPU). In this paper, we propose how O-RAN functionalities, i.e., rApp-xApp pair, can be used for energy-efficient Serving Cluster Formulation (SCF). Simulation studies show up to 37\% gain in Energy Efficiency (EE) of the proposed solution over the state-of-the…

stealing this image. super useful. thank you @… https://dan.mastohon.com/@danhon/111903226826438493

Dan Hon (@danhon@dan.mastohon.com)
Attached: 1 image man I really hate Plex sometimes, they did all this stuff with upgrading their agent architecture and now the metadata for a bunch of my tv shows is completely broken

Multi-Agent Soft Actor-Critic with Global Loss for Autonomous Mobility-on-Demand Fleet Control
Zeno Woywood, Jasper I. Wiltfang, Julius Luy, Tobias Enders, Maximilian Schiffer
https://arxiv.org/abs/2404.06975

Multi-Agent Soft Actor-Critic with Global Loss for Autonomous Mobility-on-Demand Fleet Control
We study a sequential decision-making problem for a profit-maximizing operator of an Autonomous Mobility-on-Demand system. Optimizing a central operator's vehicle-to-request dispatching policy requires efficient and effective fleet control strategies. To this end, we employ a multi-agent Soft Actor-Critic algorithm combined with weighted bipartite matching. We propose a novel vehicle-based algorithm architecture and adapt the critic's loss function to appropriately consider global actions. Furt…

This https://arxiv.org/abs/2312.04631 has been replaced.
initial toot: https://mastoxiv.page/@a…

Hole Flying Qubits in Quantum Dot Arrays
Quantum information transfer is fundamental for scalable quantum computing in any potential platform and architecture. Hole spin qubits, owing to their intrinsic spin-orbit interaction (SOI), promise fast quantum operations which are fundamental for the implementation of quantum gates. Yet, the influence of SOI in quantum transfer protocols remains an open question. Here, we investigate hole flying qubits using shortcuts to adiabaticity protocols, i.e., the long-range transfer of hole spin stat…

An Open-Source Experimentation Framework for the Edge Cloud Continuum
Georgios Koukis, Sotiris Skaperas, Ioanna Angeliki Kapetanidou, Vassilis Tsaoussidis, Lefteris Mamatas
https://arxiv.org/abs/2403.10977

An Open-Source Experimentation Framework for the Edge Cloud Continuum
The CODECO Experimentation Framework is an open-source solution designed for the rapid experimentation of Kubernetes-based edge cloud deployments. It adopts a microservice-based architecture and introduces innovative abstractions for (i) the holistic deployment of Kubernetes clusters and associated applications, starting from the VM allocation level; (ii) declarative cross-layer experiment configuration; and (iii) automation features covering the entire experimental process, from the configurat…

Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks
Ammar Ahmed Pallikonda Latheef, Alberto Santamaria-Pang, Craig K Jones, Haris I Sair
https://arxiv.org/abs/2404.10031

Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks
Brain networks display a hierarchical organization, a complexity that poses a challenge for existing deep learning models, often structured as flat classifiers, leading to difficulties in interpretability and the 'black box' issue. To bridge this gap, we propose a novel architecture: a symbolic autoencoder informed by weak supervision and an Emergent Language (EL) framework. This model moves beyond traditional flat classifiers by producing hierarchical clusters and corresponding imagery, subseq…

This https://arxiv.org/abs/2401.09686 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement
Transformer architecture has enabled recent progress in speech enhancement. Since Transformers are position-agostic, positional encoding is the de facto standard component used to enable Transformers to distinguish the order of elements in a sequence. However, it remains unclear how positional encoding exactly impacts speech enhancement based on Transformer architectures. In this paper, we perform a comprehensive empirical study evaluating five positional encoding methods, i.e., Sinusoidal and …

Software in the natural world: A computational approach to emergence in complex multi-level systems
Fernando E. Rosas, Bernhard C. Geiger, Andrea I Luppi, Anil K. Seth, Daniel Polani, Michael Gastpar, Pedro A. M. Mediano
https://arxiv.org/abs/2402.09090

Software in the natural world: A computational approach to emergence in complex multi-level systems
Understanding the functional architecture of complex systems is crucial to illuminate their inner workings and enable effective methods for their prediction and control. Recent advances have introduced tools to characterise emergent macroscopic levels; however, while these approaches are successful in identifying when emergence takes place, they are limited in the extent they can determine how it does. Here we address this limitation by developing a computational approach to emergence, which ch…

Pseudo MIMO (pMIMO): An Energy and Spectral Efficient MIMO-OFDM System
Sen Wang, Tianxiong Wang, Shulun Zhao, Zhen Feng, Guangyi Liu, Chunfeng Cui, Chih-Lin I, Jiangzhou Wang
https://arxiv.org/abs/2404.06054

Pseudo MIMO (pMIMO): An Energy and Spectral Efficient MIMO-OFDM System
This article introduces an energy and spectral efficient multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) transmission scheme designed for the future sixth generation (6G) wireless communication networks. The approach involves connecting each receiving radio frequency (RF) chain with multiple antenna elements and conducting sample-level adjustments for receiving beamforming patterns. The proposed system architecture and the dedicated signal processing method…

This https://arxiv.org/abs/2312.04631 has been replaced.
initial toot: https://mastoxiv.page/@a…

Hole Flying Qubits in Quantum Dot Arrays
Quantum information transfer is fundamental for scalable quantum computing in any potential platform and architecture. Hole spin qubits, owing to their intrinsic spin-orbit interaction (SOI), promise fast quantum operations which are fundamental for the implementation of quantum gates. Yet, the influence of SOI in quantum transfer protocols remains an open question. Here, we investigate hole flying qubits using shortcuts to adiabaticity protocols, i.e., the long-range transfer of hole spin stat…

(Un)paired signal-to-signal translation with 1D conditional GANs
Eric Easthope
https://arxiv.org/abs/2403.04800 https://arxiv.org/pdf…

(Un)paired signal-to-signal translation with 1D conditional GANs
I show that a one-dimensional (1D) conditional generative adversarial network (cGAN) with an adversarial training architecture is capable of unpaired signal-to-signal ("sig2sig") translation. Using a simplified CycleGAN model with 1D layers and wider convolutional kernels, mirroring WaveGAN to reframe two-dimensional (2D) image generation as 1D audio generation, I show that recasting the 2D image-to-image translation task to a 1D signal-to-signal translation task with deep convolutional GANs is…