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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 38
MCP Tool Poisoning in Agentic AI Frameworks: A Cross-Framework Measurement Study
The Model Context Protocol (MCP) lets agentic AI frameworks connect language models to external tool providers, but it carries attacker-controlled content (tool descriptions, schema fields, and…PlantVLM-Edge: Quantized Vision-Language Models for On-Device Crop Health Diagnosis
Timely and accurate crop health diagnosis is essential for sustainable agricultural production, yet accurate diagnosis often requires expert knowledge that is not readily available.Sonar-MoE: In-Backward Expert Updates for Memory-Efficient Mixture-of-Experts Training
Most parameters of a Mixture-of-Experts (MoE) model belong to its experts, and standard training keeps every expert gradient in GPU memory until the optimizer step.FedReady: Bounded Agents for Federation Formation
Federated learning (FL) runtimes standardize aggregation and deployment, but each new study still requires federation formation: selecting task-eligible sites and preparing their local data and task…Evaluating Uncertainty Calibration in Probabilistic Time Series Foundation Models
Time series foundation models (TSFMs) are increasingly used for probabilistic forecasting across diverse domains, yet the reliability of their uncertainty estimates remains poorly understood.Spacetime Emergence in the Memory of a Learning Agent
We show that the causal structure of spacetime can emerge within the memory of a learning agent performing a quantum information task.Four Bridges: Measuring Deception Propensity in a Multi-Agent Game
AI agents are increasingly deployed in settings where they interact and coordinate with other agents, yet honesty is mostly measured in single-turn, single-agent benchmarks that pressure the model…DiabAgent: Toward Agentic Physiological Control
As pretraining scales, medical language models have advanced rapidly in clinical question answering.Tracing the Scientific Discovery Capacity of LLMs to Their Training Data
Large language models (LLMs) show growing promise for scientific discovery, yet basic questions remain about what enables reliable discovery.Strategist: Evolving Reasoning with Agents
A model is only half of an AI agent system.D&A: Decoupling Description and Assessment Enables VLMs as Zero-Shot Robotic Reward Models
Vision-Language Models (VLMs) hold promise for zero-shot video task-progress estimation in robot learning, yet existing frameworks frequently suffer from confirmation bias, hallucinating progress in…WebHarbor: Docking Real Websites for Evolving GUI Agent Environments
GUI web agents require realistic and interactive environments that remain stable during both evaluation and training.From Natural Language to Exact Cover: A Neuro-Symbolic Approach to Zebra Puzzles
Chain-of-Thought (CoT) generation has substantially improved the performance of Large Language Models (LLMs) on complex reasoning tasks, including code generation, data analysis, and exam-style…Pixel-UMI: Learning Environment-Aware Whole-Body Manipulation from Sensorized Human Demonstrations
Sensorized human demonstrations offer scalable data for mobile manipulation, but embodiment differences complicate policy learning.Pixel: A Co-Designed Full-Stack Robot System for Learning General-Purpose Mobile Manipulation
General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning.Reasoning is topologically simple
We formulate and investigate the hypothesis that reasoning text has simpler co-occurrence topology than non-reasoning text, and that higher-quality reasoning has simpler co-occurrence topology than…EvoMemState: Evolving Memory State for Personal Agents
Long-term memory enables large language model (LLM) agents to provide continuous personalized assistance by retaining user information across interactions.Enhancing Stock Market Information Retrieval with Retrieval-Augmented Generation
Natural Language Processing (NLP) has been widely applied in financial domains, enabling automated analysis and retrieval of stock market information.LoRA-Patch: Defending Against Backdoored LoRA Adapters via Directional Steering
Third-party LoRA adapters introduce serious backdoor risks: malicious adapters can maintain normal task performance while embedding hidden, trigger-activated behaviors, making them difficult to…The Web Doesn't Sit Still: Adversarial Self-Evolving Attacks on Search Agents
Large Language Models (LLMs) have shown promise for empowering search agents to tackle complex information-seeking tasks.