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.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence 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 45
A Compute Center Anyone Can Join: A Peer-to-Peer System for AI Inference
Today, most people obtain AI inference by buying it from a small number of organizations that run large data centers, while many GPUs owned by individuals and small institutions sit idle for much of…Fairness-Aware Design for Contextual Experiments: Guaranteeing Reliability and Equity in Heterogeneous Subgroups
Experimental design is critical for evidence-based decision-making in healthcare, marketing, and public policy.Rethinking Model Aggregation for Federated Learning with Domain Skew: A Knowledge-Preserving Perspective
Domain skew challenges federated learning by requiring a shared model to accommodate distinct visual distributions.Systematic Evaluation of Robustness in Fine-tuned Models
Our study systematically evaluates the robustness of fine-tuned pre-trained models across different datasets and attack types, aiming to provide insights for researchers in selecting pre-trained…Does reflective LLM feedback survive a wet-lab-scale label budget?
Can reflective language-model feedback improve a biological predictor when each cycle buys only one plate of labels?Who Asks, Who Answers: Linear Attention Builds the Query in Hybrid Language Models
Hybrid language models interleave linear-attention layers with a small number of softmax-attention layers.Machine Learning Beyond Statistical Consistency for Hybrid AI
We propose a new definition of machine learning, according to which a machine learns a function when it computes the function successfully, that is, when the value it returns for each input has a…AgenticMobility: An Open-Source Platform for Multi-AI-Agent Mobility Dynamics
Understanding mobility dynamics and the effects of urban transportation management policies requires examining how individual travel decisions, traffic conditions, and policy interventions influence…Is Your Long-Horizon Benchmark Really Deep? Measuring and Synthesizing Depth in Terminal Tasks
Long-horizon terminal tasks are used to evaluate and train agents.RECEIPT: Measuring and Repairing the Return Assumption of LLM Agents in Web Service Operations
LLM agents operate Web infrastructure from the command line and rely on a return assumption, namely that each tool call returns within a bounded time and with its requested action finished.Geometric Morphology Learning: Empowering Foundation Models from Structure to Spacetime Intelligence
Geometry is the very form that connects space, time, and matter, serving as the fundamental fabric of the physical world, from continuous fields to discrete structures.TriPhysBench: Evaluating Physical Intelligence for Embodied Agents
Embodied agents need physical intelligence to understand their surroundings through physical perception, physical knowledge retrieval, and physical reasoning.VLSplat: Vision-Language Guided Object-Centric 3D Gaussian Splatting via Scene Graph
Learning semantic representations for 3D Gaussian Splatting has recently emerged as a promising direction for 3D scene understanding.Beyond Multimodal Emotion Conflict: Temporal Context-Aware Hidden Emotion Detection with Multimodal Large Language Models
Multimodal emotion recognition commonly combines textual, acoustic, and visual signals to infer affective states.Hippocampal consolidation without replay in fully fine-tuned networks
Networks that keep learning overwrite what they know.Step-Zero Attack: Agent Safety Before Observability
Existing attacks and defenses for coding agents act once content enters the model context: injected text persuades the model, and guards inspect what the model reads.OC-OPD: Observation-coordinated Supervision for On-Policy Distillation
Reverse and forward Kullback--Leibler (KL) divergences provide complementary supervision in on-policy distillation: reverse KL refines the student's active token rankings, and forward KL allocates…Launder-Bench: Can Repository-Level Agentic Code Laundering Be Detected?
Coding agents can now rewrite repository-scale codebases while preserving tested behavior, creating a new challenge for plagiarism detection, license auditing, and software provenance.Better Answers, Weaker Evidence Control: Evidence Bypass in On-Policy Distillation
On-policy distillation (OPD) can improve answer accuracy while weakening responsiveness to supporting evidence.Knowledge-Guided Floodwater Level Reasoning for Cloud-Edge Collaborative Monitoring
Frequent urban floodwater poses a serious threat to the safety and efficiency of intelligent transportation systems.