AI & Machine Learning · Computer Science & AI
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 88
What the Primary Lund Plane Omits: A Model-Stitching Diagnosis of a Jet-Tagger Representation Gap
Lund-plane and Particle Transformer (ParT) jet taggers can differ in performance because one representation is weaker, or because a weaker downstream computation reads an adequate one.Generative Replay for Equilibrium Propagation: Toward Edge-Friendly Continual Learning in Hopfield Networks
Equilibrium Propagation (EqProp) offers a biologically grounded and hardware-aligned alternative to backpropagation for training Hopfield Networks.Beyond Parameter Protection: Fisher-Shaped EWC for Replay-Free Continual Learning
In replay-free continual learning, Elastic Weight Consolidation (EWC) uses Fisher information matrix (FIM) to protect acquired knowledge by penalizing changes to historically important parameters.GCSR-OCC: Geometry Calibration and Semantic Routing for Open-Vocabulary Occupancy Prediction
Open-vocabulary 3D occupancy prediction represents scene geometry and semantics in a unified voxel grid, enabling recognition beyond predefined categories.WorkFactory: Turning Professional Intents into Executable Work for Scalable Agent Training
Scaling supervised fine-tuning for working agents requires not only broad coverage of professional tasks, but also expert demonstrations that faithfully carry out professional workflows to completion.LiveSearch: Questions as Executable Verifier Code for a Live Benchmark of Professional-Source Financial Search Agents
In finance, the answer that matters is usually the current one: prices, rates, and disclosures hold only as of a given day, so retrieving up-to-date facts is a core capability of a financial agent.Rènyi-Regularized Flow-Based Variational Inference for Bayesian Calibration
Variational inference with normalizing flows provides a flexible posterior approximation for Bayesian model calibration, but struggles when the posterior has several modes separated by regions of…MLE-World: Predicting Machine Learning Experiment Outcomes with a Learned World Model
AI research agents can propose, execute, and improve programs that solve machine learning tasks.Action-Value Calibration via Continuation Sharing for Long-Horizon Agentic Reinforcement Learning
Reinforcement learning for long-horizon agents relies on feedback from sequences of interactions, making credit assignment to individual actions difficult.Does Your Generalist Skill Optimizer Really Incentivize Agentic Tasks? Rethinking Skill Optimization via Bipartite Attribution
Skill optimizers adapt an agent to long-horizon tasks, such as repairing a terminal environment, by rewriting its skill, a natural-language procedure in its context, and keeping the edits that raise…Retrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution
Vision-Language-Action (VLA) policies demonstrate remarkable semantic generalization, yet remain highly vulnerable to out-of-distribution (OOD) visual shifts during execution.Spine: Compiling Subtask Trees into Structured Context for Long-Horizon Coding Agents
Long-horizon coding tasks contain nested subtasks.GraphRAGProv: GraphRAG Meets How-Provenance
GraphRAG systems often use knowledge graphs to retrieve relevant context for an LLM that produces the final answer.When Is a Relation Worth Trusting? Manipulation Costs, Exposure, and the Trust Trap in Multi-Relational Graph Learning
Multi-relational graph detectors learn from clean data how much to trust each relation, but an adversary pays a different price to manipulate each relation and each action; taking such costs as…Grounding LLM Agents in Business Processes: Process-Aware Knowledge Graphs for Reliable Multi-Step Service Invocation
Large language model (LLM) agents that call enterprise APIs must select the correct endpoints, follow process order, use valid payload keys, and choose coded values from predefined lists.TCM-DiagCommit: A TCM-SD-Derived Benchmark for Evidence-Conditioned Syndrome Selection and Commitment
Traditional Chinese Medicine (TCM) syndrome differentiation is usually evaluated as static final-label selection over complete clinical records.Aligning Large Language Models for Safety in African Languages: A Case Study of Hausa
Safety alignment research for large language models (LLMs) remains concentrated on high-resource languages, leaving open how existing alignment methods perform in low-resource, culturally distinct…Where Should the Evaluation Budget Go in LLM-Driven Agent Scaffold Evolution?
Large language model (LLM)-driven agent scaffold evolution improves agent workflows through iterative candidate generation and evaluation.RPSD: Retrieval-Privileged On-Policy Self-Distillation with Optimal Transport
Sequential recommendation predicts a user's next interaction from historical behavior.A Lightweight Attention-Based CNN with Saliency-Map Interpretability for Skin Cancer Detection
Skin cancer is among the most prevalent and life threatening forms of cancer worldwide.