AI & Machine Learning · Computer Science & AI
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 200
GLOBE: Evolving Structured Agentic Memory for E-commerce Product Optimization in Generative Search
Optimizing product listings for generative search requires language agents not only to rewrite effectively but also to continually self-improve by retaining successful strategies across diverse…Neural Expansion: A Unified Mechanism for How Deep Neural Networks Generalize
Deep neural networks demonstrate remarkable generalization despite being highly over-parameterized, challenging traditional statistical learning theories.Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability
Understanding and simulating how subjective cognition and mental states emerge, evolve, and shape behavior is essential for advancing artificial intelligence toward deeper social cognition and…LLM-Assisted Bi-Approximate CHC Solving
Constrained Horn clause (CHC) solvers often struggle to discover deep counterexamples whose derivations may require extensive rule unfolding.DrugHarness: An Evolvable Agent Harness for Computational Drug Discovery
Computational drug discovery requires agents to compose scientific operations and adapt to changing evidence and constraints.FuTransformer: FP8 prefill and INT4 decode for Llama-style inference on Hopper
Transformer prefill reuses weights across tokens and is dominated by matrix multiplication and activation data movement; single-token decode has limited reuse and is dominated by weight and KV-cache…Beyond SAEs: Consistent Concept Discovery with Sparse Coding
Sparse autoencoders (SAEs) explain foundation model representations by decomposing activations into sparse combinations of learned dictionary atoms.Self-Building Labs
Self-driving laboratories (SDLs) accelerate scientific discovery by automating experimental execution and optimization.AI-Driven Reproducibility and Analytical Robustness in Scientific Discovery
Reproducible and analytically robust research findings are essential to scientific progress, but evaluating these properties typically requires costly manual effort.Behavioral Couplings: From Formation to Behavioral Emergence in Language Models
Fine-tuning large language models (LLMs) can induce behaviors beyond those explicitly targeted.Rethinking the design space of Vanilla Pixel Diffusion Transformers
Pixel-space diffusion models have recently re-emerged as a compelling alternative to latent diffusion, avoiding the lossy latent bottleneck and separately trained autoencoder.Analysis of Binary O-type Star Systems Using Recurrent Neural Networks
This work presents an initial analysis of the estimation of effective temperature and surface gravity for simulated O-type binary systems using a recurrent neural network.Unified Multiparadigm Fusion Intelligence for Rare Disease Diagnosis
Rare diseases (RDs) affect an estimated 300 million people globally, leaving patients to navigate a protracted diagnostic odyssey constrained by clinical scarcity and fragmented medical knowledge.LLM Evolution in a Simple Simulated Market
Arguments that AI systems will evolve in harmful ways are largely made in the abstract.Client-Aware Security Adaptive Early Exit Vision Transformers for Heterogeneous Federated Learning
Federated learning (FL) trains a shared model across data-owning clients without centralizing raw data, but client data difficulty and compute budgets can differ.The Window Is in the Reasoning: When LLM Agents Decide to Follow Prompt Injections
LLM agents that read untrusted content can be hijacked by prompt injections.LogicVal:A Logic-Formalized Benchmark for Constraint Satisfaction in Text-to-Image Generation
Text-to-Image (T2I) generative models have made significant progress in producing high-fidelity images from natural-language prompts.Red-Teaming Multi-Agent Attacks for Loss-of-Control Risks
AI agents are growing more capable and persistent, and are being deployed in ever larger numbers.World of SWECraft: Agent Collaboration at Scale via Simulated Software Worlds
As teams of AI agents take on larger projects and long-standing open problems, agent collaboration offers another dimension for scaling inference-time compute.OR-License: Evaluating LLM Agents as Real-World Operations Research Practitioners
Can large language model (LLM) agents deliver expert-level operations research (OR) solutions directly from original client materials, without prior expert reformulation?