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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 55
QUAL: Quantile Alignment Improves Zero-Shot Time-Series Foundation Models
Time-series foundation models (TSFMs) provide zero-shot forecasts for unseen series, but their accuracy varies across datasets.MUON-RT Reusing the Teacher's Trajectory for Momentum-Free Muon for LLM Self-Distillation
Self-distillation methods for large language models with an exponential moving average (EMA) teacher already retain a history of student updates.Differential rank preservation manifold learning
Manifold learning methods like t-SNE and UMAP preserve local neighborhoods, but they do not preserve the ranking of the neighbors inside them.Calibration of Large Model Quantization based on HiFloat4 Format
Quantization of Large Language Models (LLMs) has become increasingly important for reducing the computational costs and resource requirements for practical deployment.Predicting Human-Gain Curves under Local Proxy Optimization from Repeated Ratings
Optimizing a proxy objective can improve human-perceived quality, but the resulting gain can vary with optimization strength.Confident Fools or Careful Searchers? A Behavioural Study of When LLMs Search Beyond Their Static Internal Memory
Agentic LLM assistants must repeatedly decide whether to answer from memory or to call a tool such as web search.When Should AI Agents Ask? Clarification Requests Under Limited Human Attention
AI agents increasingly carry out delegated tasks in parallel, with one person overseeing several of them at once.One Verdict Is Not Enough: Regression Testing Learned World Models and Their Test Harnesses
Learned world models ship as software components whose model versions, preprocessing, and test harnesses change between releases.When Disclosure Is Compulsory: Evaluating Ride-Hailing Rebalancing Policies with Self-Interested LLM Driver Agents
The EU Platform Work Directive, to be transposed by December 2026, requires ride-hailing platforms to state in plain language the main parameters of their automated decisions and how a worker's…Counterfactual Pairwise Augmentation Improves Small Pointwise LLM Judges
Agentic systems increasingly gate individual steps with a pointwise judge that scores a response against a criterion.Lineage Is Memory: Parent Inheritance and Feedback Disclosure in Short-Budget LLM-Guided Optimization
Iterative language-model optimizers refine prompts and programs by evaluating a candidate, showing a proposer model a sample of failing cases, and keeping revisions that improve performance.Lifelong Learning of Scheduling Rules with Surrogate-assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling
Genetic programming (GP) has been widely used to learn scheduling rules for dynamic flexible job shop scheduling (DFJSS).ARK: Avoiding Routing Collisions for KV Cache Transfer in Disaggregated LLM Inference
Disaggregated LLM inference separates the prefill and decode phases across GPU pools, generating massive KV-cache transfers.FrontierMat: Benchmarking Language Models at the Frontier of Materials R&D
To accelerate materials discovery, language models must be able to address problems at the research frontier.LLM Detoxification via Transition-Aware Reward-Guided Representation Sampling
Large Language Models (LLMs) can generate toxic content, motivating effective test-time detoxification.ROSTrans: Empirically Benchmarking LLMs for ROS1-to-ROS2 Migration
Although large language models have shown strong capabilities in domain-specific code generation, their performance in robotics software development, especially for the Robot Operating System (ROS)…ImplicitHop: Evaluating knowledge integration across context and memory
The ability to integrate new information and deduce its consequences is central to learning, understanding, and reasoning in large language models (LLMs).Context as Infrastructure: Knowledge Compilation for Retrieval in Agentic Systems with Harnesses
Retrieval-augmented generation is becoming agentic.Researcher-in-the-Loop Evolutionary Discovery of Entanglement-Assisted Quantum Code Families
LLM-guided program evolution can produce mathematical constructions, but validity, generality, and reproducibility require distinct evidence.Beyond CLIP: Calibrated (Few-Shot) Defect Detection With System One Decision Models
Cameras and vision sensors are widely used for product and process inspection in manufacturing environments.