Systems & Networks · Computer Science & AI
Emerging Technologies
The newest papers in Emerging Technologies that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
204 papers, from 4 September 2026 to 5 November 2026: 204 arXiv preprints.
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Newest papers, page 3
Networked Humanoid Intelligence: Communication, Coordination, Collaboration, and Social Interaction
Humanoid robots are moving from laboratory platforms toward connected fleets that share workspaces, infrastructure, tasks, and knowledge with other robots and humans.Intellectual Property Protection of Hyperdimensional Computing Classifiers: Black-Box Ownership Verification via Model Watermarking
Hyperdimensional computing (HDC) offers efficient learning and inference for resource-constrained systems, yet ownership verification of its models remains underexplored.XL MIMO Extreme Learning Machines: Wave-Domain Inference with Stacked Metasurfaces
The recently envisioned goal-oriented communications paradigm requires machine learning inference to be performed directly on wirelessly transferred data, by splitting neural network computations…Do Bio-Inspired Algorithms Save Energy in Data Centres? Separating Server Packing from Migration Search in Virtual Machine Consolidation
Energy-efficient virtual machine (VM) consolidation matters as data centre electricity demand rises.Matter that learns what matters
Can a material learn what deserves its attention?The German Tank Problem & Navigating by Scent
A robot searching for the source of an odor must eventually answer a notably hard question: have I arrived?CSI-TextBench: A Dataset and Benchmark for Language-Grounded Ambient Sensing Perception
Indoor context deciphered by ambient sensing underpins many applications, from assisted living to smart buildings, yet remains weakly connected to the language-aligned paradigm of modern multimodal…Optimizing Physical Neural Networks through Device Variable Selection
Physical neural networks (PNNs) leverage device physics in electronics, optics, and related domains to enable energy-efficient neural networks.Securing Edge & Physical AI: Post-Quantum IoT Blockchain for Mission-Critical Cyber-Physical Agents
Distributed Cyber-Physical Systems (CPS) and Edge AI networks increasingly depend on public-key authentication and key-establishment mechanisms that are vulnerable to cryptographically relevant…Hardware-Friendly Estimation of LCU-Based Expectation Values via Quantum-to-Classical Workload Shifting
Estimating the expectation value of an observable $O$ for a quantum state evolved under a general, possibly non-unitary, operator $A$ is a fundamental task in quantum simulation, chemistry, and…A Tutorial on Physics Constrained Machine Learning for Hybrid Modeling, Optimization, and Control
Physics-constrained machine learning (PCML) integrates domain knowledge, first-principles, and physical constraints into AI/ML models.Benchmarking Classical and Quantum Machine Learning for Intrusion Detection Across Multiple Datasets
Intrusion detection is examined through a comparative benchmark of classical and quantum machine learning models on three datasets: NSL-KDD, UNSW-NB15, and MQTTEEB-D2025.Terra-Fi: Decoupling Sensing and Wireless Depths for Sustainable Deep Underground Monitoring
Wireless underground sensor networks (WUSNs) enable in-situ monitoring of subsurface processes and buried assets to deliver substantial social and economic benefits across diverse verticals.NN-Based Transistor Modeling for Ultra-Fast SPICE Simulation and Standard Cell Library Characterization
Neural network (NN)-based transistor models have proven to be a promising solution to accelerate device modeling.Beyond Accuracy: Disentangling Decomposition from Typed-State Quality Assurance in Multi-Agent LLM Pipelines
Multi-agent LLM pipelines are often credited with gains in software engineering tasks, but it is rarely clear whether a gain stems from the typed contract between agents or from the specialized…First hardware demonstration of a continuous-state probabilistic computer with programmable energy-defined sampling
Probabilistic computing has proved useful for combinatorial optimization, but conventional implementations rely on binary stochastic units and sigmoid-based updates.Finite Systems in the Space of Projective Measurements
We investigate the dynamics of two-level systems using the quasidistribution $Q$ function projected onto the space of collective measurements.Not All Retained Clients Are Equal: Client Selection for Federated Unlearning
Federated unlearning (FU) aims to remove a designated target client's influence from a trained model without the prohibitive cost of retraining from scratch.A Topology-Aware Quantum-Classical Framework for Multi-Target Active Debris Removal using Gaussian Boson Sampling
The continued growth of orbital debris threatens the safety and sustainability of near-Earth space, making Active Debris Removal (ADR) an important mitigation strategy.Entangled Futures: Quantum Computing's Potential and Challenges in Computer Science
Quantum computing represents a fundamental shift in computation, promising to solve problems currently intractable for classical computers.