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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 65
DeCoRL: Decomposed Consistency Reinforcement Learning for Multi-Image Composition
Multi-image composition (MICo) is a critical yet challenging capability for large-scale image editing models, where consistency degrades rapidly as the number of reference images increases.LLM-Assisted Optimization for Simulation-Based Redesign
Engineering design frequently involves redesigning a prior solution to adapt to changes in context, such as material prices or system requirements.MemSteer: Turning User Histories into Supervision for Agent Memory Optimization
An effective agent memory system should adapt to a user's history and task requirements.WorldFlow: Joint Video and 3D Motion Prediction via Large-Scale Pretraining
Predicting future physical states stands as a central challenge in embodied intelligence.What Does "Now" Mean to Your Computer-Use Agent? Stale Screenshots, Page Loads, and Which Check to Run Before a Click
Computer-use agents plan on a screenshot for several seconds and then click at a position on the screen; if the page has changed in the meantime, the click lands on an unintended element.There Is No Free Lunch in RLVR: Every pass@1 Gain Has a pass@k Price
Reinforcement learning with verifiable rewards (RLVR) makes a language model solve more problems on the first try and fewer when given many tries: it raises pass@1 while the base model overtakes it…Proving and Improving the Platonic Representation Hypothesis with JEPAs
Whether models trained on different modalities converge to the same representation of the world is central to AI.Learning to Bound: Monotonic, Calibrated Neural Upper Bounds for MPE Inference
Probabilistic graphical models (PGMs) compactly encode structured joint distributions, but Most Probable Explanation (MPE), which finds the highest-probability assignment to unobserved variables…Telling Is Not Seeing: Textual Personas Rarely Make Vision-Language Models Answer Like the People They Describe
Vision-language models (VLMs) are increasingly prompted with personas, such as "You have low vision", to stand in for people in user studies.RetroChessBench: A Benchmark for Reconstructing and Proving Chess Histories
Frontier language models such as GPT 6 Astra have contributed to research mathematics, demonstrating substantial reasoning capabilities.CoToan: Executable Rules and a Representation Contract for Reproducible Game AI Evaluation
Game AI results are comparable only when different implementations expose the same decision problem.Semantic Mismapping in Generalized Category Discovery: Evaluation and Mitigation
Generalized Category Discovery (GCD) aims to perform old-category recognition and novel-category discovery in the same unlabeled set.Before the Next Rollout: Diagnosing Skill Utility Shifts from Policy Updates
Skill-evolution methods typically analyze execution trajectories to guide agent skill refinement.Cord: Confidence-Anchored Order Residual Decoding for Masked Diffusion Language Models
The decoding order of masked diffusion language models (dLLMs) can substantially affect generation quality, yet common decoders typically apply the same reveal rule throughout generation.What Makes Medical Examination Items Difficult? Using Large Language Models to Explore Patterns Associated With Empirical Item Difficulty
Research on medical item difficulty has largely focused on prediction rather than on identifying interpretable patterns associated with empirical difficulty.AgentDecept: Benchmarking Deceptive Behavior in Tool-Using LLM Agents under Pressure
LLM agents increasingly carry out multi-turn tasks across everyday applications, yet users often see only the agent's report rather than the observations, API calls, and state changes behind it.Learning to Formulate: Agentic Hardware-Software Co-Design of AI Infrastructure through Progressive Optimization and Verification
AI infrastructure, the chips and software that train and serve AI models, is designed in layers.UMI-Live for In-The-Wild Bimanual Robotics Data Collection
Universal Manipulation Interface (UMI) devices allow human experts to demonstrate tasks for robot learning without teleoperating physical robots.OPERA: OPamp Design by an Expert-Taught Reasoning Agent, from Specifications to Layout
Analog flows from specifications to a signed-off layout rarely run without manual iteration.SymKL: A Unified Representation-Space Measure of Signal Degradation
Quantifying degradation between a pristine signal and its degraded observation is fundamental to signal processing, yet existing full-reference measures are inherently modality-specific.