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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Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI
Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor.Risk-Aware World Modeling with Flow-Guided Occupancy Evolution for Selective Trajectory Planning in Automated Driving
Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory.The Uneven Impact of Generative AI on Student Learning: Examining the Roles of Reliance, Evaluation Literacy, and Course Policy in AI-related Courses
Generative artificial intelligence (GenAI) is changing how students learn, yet the roles of course context, cognitive reliance, evaluation literacy, and early reliance remain underexplored.Radio-Frequency Convolutional Neural Networks
Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalability, and data privacy, but these devices rarely…A Memristive Synapse for Online STDP Learning and Inference in SNNs
This work presents a fully analog memristive synaptic circuit for online spike-timing-dependent plasticity (STDP) learning in spiking neural networks (SNNs).A Game-Theoretic Framework for Incentive-Compatible AI training Under Renewable-Energy Constraints
As artificial intelligence systems increasingly rely on distributed and collaborative training, the energy footprint of these processes becomes a shared responsibility.More Than Just Access: Generative AI as Communication Intermediary for Blind and Low-Vision Users
Generative AI (GenAI) tools are increasingly woven into how blind and low-vision (BLV) people communicate, not only with digital information, but with the physical world and with other people.Proportional-Fair Resource Allocation and Dual-Threshold Early-Exit Inference for Secure Cooperative Multi-Layer Edge Intelligence
This paper proposes FREDI (Fair Resource Allocation for Edge Dual-Threshold Inference), a secure wireless edge-intelligence framework for event-triggered inference in a cooperative user equipment…Scaled Hippocampus-inspired Neural Networks on Neuromorphic Memristive Hardware
The hippocampus, a key brain region for learning and memory, exhibits rich structural diversity, sparse communication, and robust dynamics with incredible energy efficiency.TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps
Cloud-hosted large language models (LLMs) are increasingly used for root cause analysis (RCA) in AIOps pipelines, but they introduce data privacy risk, network latency, and per-query cost that scale…But How Would AI Agents Run a Town's Economy?
We placed 100 memory-equipped large language model (LLM) agents in charge of a closed, money-conserving spatial economy on real Pokhara Lakeside geography (earning wages, running businesses, setting…Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditions
Verification and validation (V&V) of classification models is crucial to enable a wide range of sensor processing applications.Generative Replay Mitigates Sample Starvation in Quantum Architecture Search
Reinforcement learning (RL) can automate quantum architecture search, but its scalability is limited when useful circuit trajectories become rare in the rapidly expanding search space.A Time-Based Readout for Vector-Matrix Multiplication in Fully Analog Memristive SNNs
Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data movement between memory and processing units.Feasibility and Memory Mechanisms of Chern-Simons Context Reservoir Computation
We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a benefit beyond simpler mechanisms.The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoption
This study evaluates Vibe Coding, an emerging AI-led conversational programming paradigm that enables developers to generate software through natural-language interaction with large language models.Fidelity-Aware Scheduling of Quantum Circuits on Multi-QPU Systems
High Performance Computing-Quantum Computing (HPCQC) platforms expose multiple Quantum Processing Units (QPUs) that may differ in size, topology, native gates, and noise characteristics.Fractional-order hardware for neuromorphic computing: Is the order really the problem?
Does a neuromorphic system need a true power-law memory kernel, and if so, can anyone build one?Vision: Data-Centric Anchoring for Robust and Interpretable Agentic AI
Agentic AI systems built on large language models fail in two persistent ways that scaling does not fix: they break under distribution shift, and they cannot explain the decisions they make.OntoKG-EQ: A provenance-grounded, competency-question-governed knowledge graph for auditable analyst querying
Analysts in emerging equity markets keep answering the same questions.