Tootfinder

UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning
Zihao Huang, Yu Bao, Qiyang Min, Siyan Chen, Ran Guo, Hongzhi Huang, Defa Zhu, Yutao Zeng, Banggu Wu, Xun Zhou, Siyuan Qiao
https://arxiv.org/abs/2508.18756

UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning
While Mixture of Experts (MoE) models achieve remarkable efficiency by activating only subsets of parameters, they suffer from high memory access costs during inference. Memory-layer architectures offer an appealing alternative with very few memory access, but previous attempts like UltraMem have only matched the performance of 2-expert MoE models, falling significantly short of state-of-the-art 8-expert configurations. We present UltraMemV2, a redesigned memory-layer architecture that closes t…

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimization
Benjamin Coriat, Eric Benhamou
https://arxiv.org/abs/2507.18560

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimization
This paper presents a novel hierarchical framework for portfolio optimization, integrating lightweight Large Language Models (LLMs) with Deep Reinforcement Learning (DRL) to combine sentiment signals from financial news with traditional market indicators. Our three-tier architecture employs base RL agents to process hybrid data, meta-agents to aggregate their decisions, and a super-agent to merge decisions based on market data and sentiment analysis. Evaluated on data from 2018 to 2024, after t…

[2025-09-24 Wed (UTC), 8 new articles found for cs.NI Networking and Internet Architecture]
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BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
Azhar Ikhtiarudin, Aditi Das, Param Thakkar, Akash Kundu
https://arxiv.org/abs/2507.12189

BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
We introduce BenchRL-QAS, a unified benchmarking framework for systematically evaluating reinforcement learning (RL) algorithms in quantum architecture search (QAS) across diverse variational quantum algorithm tasks and system sizes ranging from 2- to 8-qubit. Our study benchmarks nine RL agents including both value-based and policy-gradient methods on representative quantum problems such as variational quantum eigensolver, variational quantum state diagonalization, quantum classification, and …

Q&A with researcher Petter Törnberg on his pre-print study showing how social media's structural architecture creates problematic outcomes like echo chambers (Jennifer Ouellette/Ars Technica)
https://arstechnica.com/science/2025/08/study-social-medi…

Study: Social media probably can’t be fixed
“The [structural] mechanism producing these problematic outcomes is really robust and hard to resolve.”…

Spectrum of slip dynamics, scaling & statistical laws emerge from simplified model of fault and damage zone architecture
M. Almakari, N. Kheirdast, C. Villafuerte, M. Y. Thomas, P. Dubernet, J. Cheng, A. Gupta, P. Romanet, S. Chaillat, H. S. Bhat
https://arxiv.org/abs/2509.04909

Spectrum of slip dynamics, scaling & statistical laws emerge from simplified model of fault and damage zone architecture
Seismological and geodetic observations of a fault zone reveal a wide range of slip dynamics, scaling, and statistical laws. However, the underlying physical mechanisms remain unclear. In this study, we show that incorporating an off-fault damage zone-characterized by distributed fractures surrounding a main fault-can reproduce many key features observed in seismic and geodetic data. We model a 2D shear fault zone in which off-fault cracks follow power-law size and density distributions, and ar…

Implementation of a 8-bit Wallace Tree Multiplier
Ayan Biswas, Jimmy Jin
https://arxiv.org/abs/2509.09178 https://arxiv.org/pdf/2509.09178

Implementation of a 8-bit Wallace Tree Multiplier
Wallace tree multipliers are a parallel digital multiplier architecture designed to minimize the worst-case time complexity of the circuit depth relative to the input size [1]. In particular, it seeks to perform long multiplication in the binary sense, reducing as many partial products per stage as possible through full and half adders circuits, achieving O(log(n)) where n = bit length of input. This paper provides an overview of the design, progress and methodology in the final project of ECE …

Modeling electrothermal feedback of superconducting nanowire single photon detectors in SPICE
Hanson Nguyen, Alejandro Simon, Reed Foster, Karl K. Berggren
https://arxiv.org/abs/2508.02791

Modeling electrothermal feedback of superconducting nanowire single photon detectors in SPICE
Superconducting nanowire single-photon detectors (SNSPDs) exhibit complex switching behaviors due to electrothermal feedback during the detection process. Modeling and understanding these behaviors is integral for designing superconducting devices; however, many models often prioritize accuracy over computational speed and intuitive integration for circuit designers. Here, we build upon a growing architecture of SPICE tools for superconducting nanowire devices by capturing complex residual heat…

🏗️ The Architecture Beast:
• 1 trillion total parameters (32B activated per token) • 384 experts with 8 selected per token • 128K context window for handling massive codebases • Zero training instability across 15.5 trillion tokens • Built with the revolutionary MuonClip optimizer ⚡

Decentralised Multi-Manager Fund Framework
Arman Abgaryan, Utkarsh Sharma, Joshua Tobkin
https://arxiv.org/abs/2507.00978 https://arx…

Decentralised Multi-Manager Fund Framework
We introduce a decentralised, algorithmic framework for permissionless, multi-strategy capital allocation via tokenised, automated vaults. The system is designed to function analogously to a multi-strategy asset management company, but implemented entirely on-chain through a modular architecture comprising four interacting layers. The first, the capitalisation layer, composed of vaults that facilitate multi-asset deposits, tokenises investor participation, and specifies high level risk limits a…

[2025-07-16 Wed (UTC), 8 new articles found for cs.AR Hardware Architecture]
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End-to-End Large Portfolio Optimization for Variance Minimization with Neural Networks through Covariance Cleaning
Christian Bongiorno, Efstratios Manolakis, Rosario Nunzio Mantegna
https://arxiv.org/abs/2507.01918

End-to-End Large Portfolio Optimization for Variance Minimization with Neural Networks through Covariance Cleaning
We develop a rotation-invariant neural network that provides the global minimum-variance portfolio by jointly learning how to lag-transform historical returns and how to regularise both the eigenvalues and the marginal volatilities of large equity covariance matrices. This explicit mathematical mapping offers clear interpretability of each module's role, so the model cannot be regarded as a pure black-box. The architecture mirrors the analytical form of the global minimum-variance solution yet …

A small and interesting architecture for early fault-tolerant quantum computers
Jacob S. Nelson, Andrew J. Landahl, Andrew D. Baczewski
https://arxiv.org/abs/2507.20387 https://…

A small and interesting architecture for early fault-tolerant quantum computers
We present an architecture for early fault-tolerant quantum computers based on the smallest interesting colour code (Earl Campbell, 2016). It realizes a universal logical gate set consisting of single-qubit measurements and preparations in the X and Z bases, single- qubit Hadamard (H) gates, and three-qubit controlled-controlled-Z (CCZ) gates. State teleportations between [[4, 2, 2]] (2D) and [[8, 3, 2]] (3D) error-detecting color codes allow one to make use of the respective transversal H and …

Geological Everything Model 3D: A Promptable Foundation Model for Unified and Zero-Shot Subsurface Understanding
Yimin Dou, Xinming Wu, Nathan L Bangs, Harpreet Singh Sethi, Jintao Li, Hang Gao, Zhixiang Guo
https://arxiv.org/abs/2507.00419

Geological Everything Model 3D: A Promptable Foundation Model for Unified and Zero-Shot Subsurface Understanding
Understanding Earth's subsurface is critical for energy transition, natural hazard mitigation, and planetary science. Yet subsurface analysis remains fragmented, with separate models required for structural interpretation, stratigraphic analysis, geobody segmentation, and property modeling-each tightly coupled to specific data distributions and task formulations. We introduce the Geological Everything Model 3D (GEM), a unified generative architecture that reformulates all these tasks as prompt-…

[2025-09-15 Mon (UTC), 8 new articles found for cs.NI Networking and Internet Architecture]
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Spinwave Bandpass Filters for 6G Communication
Connor Devitt, Sudhanshu Tiwari, Bill Zivasatienraj, Sunil A. Bhave
https://arxiv.org/abs/2507.18931 https://

Spinwave Bandpass Filters for 6G Communication
Spinwave filters using single-crystal yttrium iron garnet are an attractive technology for integration in frequency adjustable or tunable communication systems. However, existing SW devices do not have sufficient bandwidth for future 5G and 6G communication systems, are too large, or have strong spurious passbands creating unintentional cross-channel interference. Leveraging modern micromachining fabrication methods capable of wafer-scale production, we report a SW ladder filter architecture re…

[2025-08-12 Tue (UTC), 8 new articles found for cs.AR Hardware Architecture]
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[2025-09-10 Wed (UTC), 8 new articles found for cs.NI Networking and Internet Architecture]
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[2025-09-04 Thu (UTC), 8 new articles found for cs.NI Networking and Internet Architecture]
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[2025-07-04 Fri (UTC), 8 new articles found for cs.NI Networking and Internet Architecture]
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