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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 84
Less is more: learning what to profile for GPU kernel optimization
Large language models have recently shown strong potential for automatically optimizing GPU kernels, yet their effectiveness depends critically on the hardware information available to the kernel…Follow the Herd: A Data-Driven Approach for Actionable Recourse
As machine learning systems make increasingly greater decisions about people's lives, it is critical to provide users with actionable recourse about how they can achieve their desired outcomes.MM-Net: A Multimodal Multi-Task Network for Sleep Staging and Sleep Apnea Assessment After Ischemic Stroke
Automated polysomnography after ischemic stroke is challenging because of altered sleep-related neural activity and concurrent respiratory disturbances.Benchmarking LLM Agents for Behaviorally Adequate Test Generation from Software Requirements
As large language model agents increasingly compile natural-language requirements into repository-level code, requirement-to-test generation grows in importance to provide validation constraints (or…InfraDev: Can Coding Agents Develop AI Infrastructure, and How Can We Tell?
Coding agents are beginning to develop the production-grade AI infrastructure that trains and serves large models, yet existing benchmarks cover only single kernels or single-GPU tasks, and grade…Learning to Formalize: Bridging Open-Ended Workloads and Fast Decision Models
Decision models offer fast choices over sup- plied alternatives, while general-purpose large language models interpret open-ended tasks through flexible generation and reasoning at the cost of…Balanced State Subspaces for Mamba-2 State Compression
Mamba-2 compresses all context into a fixed-size recurrent state that dominates decoding memory and bandwidth.Dream-COP: Guiding Algorithm Discovery for Combinatorial Optimization Problems in an Experience World
Large language models (LLMs) enable algorithm discovery for combinatorial optimization problems (COPs) through iterative program generation and evaluation.God Does Not Play Dice: Enforcing Batch Invariance in Agentic Kernel Generation
Large language model (LLM) serving systems dynamically batch user requests for GPU execution, so the same request may be processed alongside different requests across runs.Adapting Video Models for Robot Control via Motion-guided Asymmetric Prediction
World Action Models (WAMs) leverage pretrained video generative models for robotic control by jointly predicting future visual observations and actions.Polarity--Time Interaction and Multi-Level Reliability for Event-Based Spacecraft Pose Estimation
Sparse event responses produce uneven keypoint errors whose effects on spacecraft pose depend on correspondence geometry and the reliability of successive observations.The uneven rise of AI-generated web content
In less than five years, generative artificial intelligence (AI) has dramatically reshaped the public-facing web.Tap2Listen: Instant Target Switching for Streaming Audio-Visual Speaker Extraction
Streaming audio-visual target speaker extraction (AV-TSE) uses a target speaker's face to extract the speaker's speech from an input audio mixture in real time.Remembering Is Not Enough: Refining Memories and Learning When to Use Them in Multi-Agent Systems
Memory helps LLM-based multi-agent systems reuse experience, but stored advice can be flawed or applied in the wrong situation.The View from Nowhere: Population-Centered Agent Evolution
Self-improving AI systems can revise the designs that govern their own behavior.A Quantitative Approach to Asch Conformity in Frontier Large Language Models
The Asch conformity experiment has recently gained considerable attention as a way of measuring conformity in large language models (LLMs).Look Only When Needed: Certificate-Guided Visual Routing for Efficient Diffusion VLMs
Diffusion vision-language models (DVLMs) process their entire input at every denoising step.Learning Where to Trust: Reliability-Guided Expert Routing and Velocity Gating for 3D Deformable Registration
Deformable image registration relies on accurate anatomical correspondences.Atom as an Agent: Emergent Order by Collective Predictive Coding
What is the intrinsic reason of emergence of macroscopic order parameter out of microscopic systems?Specialization, Diversity, and Scaling in Child-Scale Language Models
Modern language models are trained on far more language than children experience, but we know much less about learning from small, naturalistic datasets.