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Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 44
MatMoE: Matryoshka Mixture-of-Experts with Dynamic Mixed-Precision Quantization for Efficient Inference
Mixture-of-Experts (MoE) architecture has been widely adopted in large language models (LLMs) since it reduces the computational cost through sparse expert activation.SMART-AIMC: Sensitivity-Aware Mixed ADC Resolution with Fine-Grained Tunability for Analog In-Memory Computing
Analog In-Memory Computing (IMC) is a promising paradigm for accelerating GEMM-based AI workloads by executing computations directly within the memory array in the analog domain.CST: Lightweight Risk Triage with Source-Grounded Evidence for Web Discussions
Web communities rely on moderators to catch harmful messages such as insults, hate speech, and scams, but no one can read every message.Route-Guided CBF-QP Repair for Safe Vision-Language-Action Models
Vision-language-action (VLA) models can generate task-oriented robot actions, but they do not guarantee safe execution in obstacle-rich manipulation scenes.Delivered, Not Used: Evaluating Agent Memory at Its Point of Use
Task success, retrieval quality, and cost do not show whether an LLM agent used a delivered memory or what followed from that use.MAC-Bench: Benchmarking Multi-Agent Collaboration via Interconnected Tasks
Large language model (LLM)-based multi-agent systems (MAS) tackle challenging tasks by dividing work among agents and coordinating their contributions toward shared objectives.Robust EEG-based Emotion Recognition from Coarse Trial-level Labels under Intra-trial Affective Variability
EEG-based emotion recognition has become an active research area in brain-computer interfaces.Evolving Memory, Learning to Meta-Control: Test-Time Adaptation for Experience-augmented LLM Agents
Self-evolving agents accumulate experience from task streams, but existing frameworks typically rely on fixed pipelines to retrieve and utilize this experience, neglecting when and how to deploy it.Silent Reward and Environment Defects in EV Charging Simulation Benchmarks: A Diagnostic Checklist
Reinforcement-learning (RL) benchmarks built on microscopic traffic simulators such as SUMO are increasingly used to compare agent architectures for electric vehicle (EV) charging assignment.MemRole: From Memories to Decisions for Long-Horizon Reasoning in Role-Playing Agents
LLM-based role-playing agents are fluent at imitating a character's style, yet struggle to make role-consistent decisions over long narrative horizons.Control Barrier Functions for Safety-Aware Latent-Space Motion Planning
Latent-space path planning (LSPP) compresses the configuration space of a robotic manipulator into a compact, differentiable manifold learned by a variational autoencoder, enabling fast…CoGSeq-LTV: Scalable Missing-Aware Graph-Sequence Modeling for Multi-Business Transaction Analytics
Large-scale super-apps generate heterogeneous transaction logs in which users interact with multiple businesses, item identifiers are only partially available, and future value targets are sparse…LegoEnv: Self-Evolving Agentic Environments via Modular Recombination
LLM agents learn by interacting with environments, yet existing environments are designed for specific tasks and fail to generalize to new ones.NEIGHBOR: Aligning Service Behaviour and Evidence Use in an LLM Agent for Community Resident Services
Residents who contact a community service desk about a repair or a service charge need answers they can act on, with facts that hold for their case and commitments the desk can keep.Self-Evolving Agentic Workflows via Semantic Decomposition of Complex Tasks
Agentic workflows organize complex tasks into reusable procedures.MEX: The Musical Expectation Benchmark Suite
We propose the Musical Expectation (MEX) benchmark suite for perceptually validating computational models of musical expectation, i.e., models that estimate music information dynamics (MID) measures…OpenNWM: A Generalist Navigation World Model with Latent Action Pretraining
Navigation world models predict future observations conditioned on navigation actions to support planning, but their generalization across real-world environments remains constrained by the limited…FADE: A Flow-Based Approach for Multichannel Tail Estimation
Ultra-Reliable Low-Latency Communication (URLLC) is vulnerable to rare low-received-power events, and the spatial-diversity benefits of multiple receivers can be significantly reduced when they…Privacy-Preserving ECG-HRV Emotion Classification for Mood Swing Detection using Federated Learning on Constrained Edge Devices
This paper presents a privacy-preserving mood monitoring framework that classifies emotional states from ECG-derived heart rate variability (HRV) features.Quantizing Recurrent Language Models Is Easier Than You Think
Linear recurrences are becoming an increasingly common building block in large language models, replacing the growing KV cache of softmax attention with a fixed-size recurrent state that enables…