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.
Get the few papers worth your time in Emerging Technologies every morning.
Follow Emerging Technologies and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 8
Probabilistic Algorithms for Ising Machines from Optimization to Generative AI
Ising machines have emerged as promising hardware accelerators for intractable optimization and sampling problems, yet their practical impact increasingly hinges on the co-design of algorithms and…Evaluating Biomedical Reranking for LLM-Based Question Answering over Longitudinal Clinical Notes
Patient-specific clinical question answering requires locating the right evidence within long, heterogeneous longitudinal clinical records in which relevant facts may be scattered across encounters…Generalised Bit-Vector Abstractions for Formal Verification of Quantum Error-Detection and Entanglement Circuits over {H,X,C-NOT}: CSS Constructions, Soundness, and Mutation-Based Validation
Formal verification of quantum circuits becomes difficult as circuit size grows because exhaustive reasoning over the Hilbert space is computationally expensive.Exact Diagonal Completion on Reachable Subspaces: Application to QAOA Placement
Unused encoding states offer opportunities to simplify quantum circuits.Motzkin-Straus Optimization on an Entropy-Computing Platform
We introduce a framework for combinatorial optimization using sum-constrained continuous quadratic programs solvable by QCi's Dirac-3S photonic entropy computer.AIR-LLM: Broadcasting AI Weights over Radio for Memory-Free Edge LLM Inference via RF Computing
Next-generation large language models (LLMs) are expanding from the cloud to ubiquitous edge devices.Beyond Feasibility: Finite-Depth Accessibility in Constrained QAOA
Constraint-preserving mixers keep QAOA within a feasible subspace, but feasibility and global mixer connectivity do not determine which feasible configurations are available to a particular shallow…Learning and Predicting Patent Technology Reuse Trajectories from Emergence-Time Signals
Forecasting how a newly emerged patent technology will be reused is central to technology intelligence, but reuse-pattern labels do not exist in advance: they must be constructed from the…DraftTrace: A Multi-View Analytics Environment for AI-Integrated Writing
Generative AI has changed how students produce writing assignments.Physical Muon: Orthogonalization as an Equilibrium Computation
Physical neural networks and analog in-memory computing could reduce the energy cost of neural network training.Who Gets a Token, and What Does It Carry? Unequal Name Support and Concept Access in Large Language Models
Names are personal identifiers, but they also carry social meaning and are widely used to evaluate how language models treat different people.DPS: Dual-Mode Precision LLM Serving with Semi-Unified Memory
Existing LLM serving systems virtualize and optimize KV-cache memory, but treat model-weight memory as fixed throughout execution.P2P: Cross-View Population Denoising for Unpaired Single-Cell Perturbation Response Prediction
AIVC (AI Virtual Cell) is a learned simulator of cellular behavior across conditions.Recent Advances in Agentic Agri-Robotic Phenotyping: A Perspective Review from Fragmented Multimodal Sensing to Unified PhenoAgent Intelligence
This review examines the evolution of plant phenotyping from conventional manual trait measurement to high-throughput, robotic, and artificial intelligence-driven crop monitoring.Mirror-Score: Calibrated, Inference-only Scoring Exposes the Limits of Sequence-compatibility Ranking in D-peptide Design
D-peptides combine protease resistance with high target specificity, but computational design of D-peptide binders remains immature.AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search
Open-world aerial object-goal search is a foundational yet challenging task, requiring aerial agents to autonomously explore large-scale, unstructured three-dimensional environments and reach target…Encoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs
Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task.CineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles
Large language models are increasingly evaluated in specialized domains such as law, medicine, software engineering, and cybersecurity, yet film remains comparatively underexplored despite requiring…VehDyn: A Driving World Model Benchmark for Vehicle Dynamics
Video world models are emerging as data engines, action planners, and generative simulators for autonomous driving, but existing benchmarks primarily assess visual fidelity and coarse physical…Fewer Qubits, Better Choices: Coupling-Aware Sub-QUBO Selection for Quantum-Assisted Traffic Zone Partitioning
Near-term quantum optimizers accommodate roughly a hundred binary variables, requiring large Quadratic Unconstrained Binary Optimization problems to be decomposed into hardware-sized subproblems…