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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 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 206
TRACER: A Multimodal Harness for Patient Care in Hospitals
Continuous video and clinical records provide complementary information for understanding how patient behavior evolves over a hospital stay.TRACER: Trajectory-Aware Tool Retrieval for LLM Agents
Modern agents select tools from registries, but exposing entire registries incurs high token costs and can impair selection as they grow.Auditing Escalation Reliability in Healthcare LLM Agents: A Perturbation-Controlled Benchmark of Workflow-State Failures
Trustworthy biomedical AI requires reliable action selection when evidence is missing, stale, conflicting, or late, not only accurate answers on static inputs.Diviner: Agentic RCA with Human-Governed Adaptation for Large-Scale Infrastructure
Root-cause analysis (RCA) in large-scale distributed systems is challenging because a single symptom can cross service, data, configuration, compute, and organizational boundaries.Mallea: Building, Steering, and Memorizing Worlds with Coding Agent
Code world models represent world dynamics through explicit state and executable rules.The Density of Thought: Predicting and Steering Reasoning in Large Language Models
We investigate whether variation in information density across chain-of-thought (CoT) reasoning steps predicts answer correctness and can serve as a controllable inference-time target.Bias Control and Injection for Multi-Agent Aggregation
Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision should be trusted?Money-Mule Detection as a Relational Learning Problem: A Study on the RBIH NFPC Dataset
Money-mule networks move criminal funds through many small transfers, each of which looks ordinary on its own.Loud and Clear: Making Visual Evidence Count in Multimodal Document RAG
Multimodal document retrieval-augmented generation (RAG) has focused largely on retrieval, yet its answers depend on how well a vision-language model reads the retrieved pages.Constrained Multi-Agent Reinforcement Learning in Imagination
Predicting cost in a multi-agent world model moves most constrained policy updates into imagination: the stronger model-free baseline needs $10$ to $20$ times CA-MAMBA's interactions on the median…DocPilot: Interactive Agent Orchestration and Training for Long Visual Document Understanding
Multimodal long-document question answering requires models to seek sparse evidence across pages and modalities, understand heterogeneous document content, and reason over the collected evidence.Does On-Policy Distillation Need to Complete Every Rollout?
On-policy distillation (OPD) transfers teacher knowledge to a student through feedback on student-generated rollouts, but generating complete rollouts and computing per-token teacher feedback are…Quantum Versus Classical Machine Learning for Neuropsychiatric Disorders: A Feature-Matched Multi-Cohort Evaluation
Resting-state functional connectivity is widely used in machine learning-based classification of neuropsychiatric disorders.ARGUS: An Agenda-Driven Framework for Reliable User Simulation
High-fidelity user simulators are essential for evaluating and training agents in interactive environments.FedSkillGit: Federated Skill Evolution via Version Control
Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience.Hierarchical Graph Convolutional Network Approach for Detecting Low-Quality Documents
Consistency within a document is a crucial feature indicative of its quality.LTM: Latent Transition Based In-Context Memory for Vision-Language-Action Models
Robotic manipulation often requires remembering interactions that are no longer visible.ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases
With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has significantly increased.Memorilla: Latent Semantic Memory for LLMs
Memory enables large language models (LLMs) to use information beyond their parameters, such as past user conversations, long documents, or an agent's earlier actions.PriorityFEC: Deadline-Aware Streaming FEC for KV-Cache Handoff in Edge Multi-Agent Systems
Multi-agent large language model (LLM) systems are increasingly deployed at the edge to support complex tasks that require collaboration and information exchange among multiple agents.