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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 46
MUPA${}^2$S: Multimodal Unified Perception with Asymmetric Attention for Stress Assessment
Stress is a leading contributor to long-term physical and mental health decline.Beyond Prompt Injection: The Tool Update Gap in LLM Agent Security
Large language model based agents increasingly rely on external tools to invoke services and interact with web resources.Opening the Black Box of Neural Auction Mechanisms
Neural auction design has emerged as a powerful paradigm within automated mechanism design for modern Web platforms.SurgStream: A Workflow-Anchored Proactive Streaming Framework and Benchmark for Real-Time Surgical Video Understanding
Surgical video understanding is essential for intraoperative assistance such as workflow monitoring, instrument preparation and procedural documentation.RubricWorld: World Model-Guided Rubric Optimization for LLM Graders
Rubric optimization improves LLM grading by revising scoring instructions while keeping the grader's parameters fixed.Safety4DM: A Vision-Language Framework for Risk-Aware Dynamic Maps in Vehicle-Road-Cloud Collaborative Driving
Dynamic map (DM) is a core information infrastructure for vehicle-road-cloud (VRC) cooperative autonomous driving.TrackMem: Tracking Evolving Beliefs in Long-Horizon Financial Dialogue
Memory systems for LLM agents are evaluated mostly on social dialogue, where facts accumulate and rarely change, so remembering reduces largely to finding the turn in which something was said.To Align Long, Plan Short: Simulating Diverse Profile-Aligned Students by Realizing Short-Term Plans in Long-Horizon Learning Environments
Simulated students offer a scalable way to test learning platforms and AI tutors before deployment with real students and to augment scarce data for studying learning at scale.Scaling Makes It Possible: How Large Models Master Impossible Languages
While language models (LMs) excel in natural language tasks, their ability to learn impossible languages--those that violate the structural, cognitive, or logical constraints that make human…ClickSight: An LLM Framework for Interpreting Student Clickstreams Through Learning Strategies
Digital learning environments produce rich clickstream data that can reveal how students approach learning tasks, yet interpreting these fine-grained traces often requires substantial expert effort.Reconstruction as Spatial Evaluation: Diagnosing Cross-View Spatial Intelligence in Large Vision-Language Models
The spatial intelligence of large vision-language models (LVLMs) requires the ability to combine local visual observations into a geometrically consistent representation of the physical world.LARK: Lean-Assisted Reasoning for LLM-Generated GPU Kernels
Efficient GPU kernels are typically low-level and hardware-specific, and LLM agents can now generate them faster than experts can verify.Query-efficient scan-and-search watermark localization
Recently, the detection of AI-generated content has been of particular importance in various fields of our society.Beliefs in feedback: Factored representations of interacting agents in transformers
Complex systems, from ecosystems to brains, are usually modeled as modular components coupled through feedback rather than as indivisible wholes.Do Embodied VLMs Actually Use Their Scene-Graph Memory?
Embodied agents that answer questions about their route need a memory of what they saw, and scene graphs are a natural form for it.State-Aware Virtual Patient Simulation for Training Psychiatrists in Challenging Clinical Scenarios
Psychiatrists must be prepared to manage patients exhibiting challenging psychological states, including suicidal ideation, hallucinations, and other high-risk behaviors.SWE-Trail: History-Guided Trajectory Collection for Coding Agent Training
Coding agents solve repository issues through long sequences of exploration, editing, and validation.Decoupled Predictive Decision Making: A Shared Conditional Predictor for Agents
Agent decisions depend on empirical relationships that deployment observations reveal and task descriptions alone may leave unresolved.Scene-Adaptive Readout and Decoding in Diffusion Driving VLAs
Diffusion driving vision-language-action models repeatedly execute the backbone at every denoising stage, incurring substantial inference cost, while it remains unclear whether all scenes require…ParetoSaddler: Pareto-Guided Optimization of Agent Harnesses for Quality and Cost
Harness optimization can substantially improve LLM agents without modifying model weights, but existing methods primarily optimize response quality.