AI & Machine Learning · Computer Science & AI
Machine Learning
The newest papers in Machine Learning 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 5 November 2026: 5,000 arXiv preprints.
Get the few papers worth your time in Machine Learning every morning.
Follow Machine Learning and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 56
Trouble With Time: Compile Timestamps and First-Seen Date Regression in EMBER2024
Reliable first-seen dates are important for constructing temporal malware evaluation splits, but this information often comes from external services that are not equally accessible to all researchers.Forecasting Visitor Demand from Open AI-Camera Counts and Weather: Lessons from Japan for Saudi Heritage Sites
Small heritage and nature sites need a few days' notice of busy days to plan staff, overflow parking and shuttles, but most have neither sensors nor forecasting expertise.Self-Normalized Inference from Riemannian Stochastic Gradient Paths
Riemannian stochastic gradient paths estimate constrained parameters, but confidence regions usually require estimating the Hessian and gradient-noise covariance.pico-WAM: Evaluating Counterfactual Prediction and Planning Error in a Compact World Action Model
When a World Action Model fails at control, is the bottleneck proposal generation or trajectory scoring?ParaBlock++: Communication-Computation Parallel Blockwise Hierarchical Federated Learning
In the emerging 6G paradigm, where AI-driven services operate over decentralized and resource-constrained infrastructures, the convergence of distributed learning algorithms remains a significant…Entropy-Regularized Reinforcement Learning for the Regime-Switching Consumption-Investment Problem
This paper establishes an entropy-regularized reinforcement learning (ERRL) framework for the continuous-time consumption-investment problem under a regime-switching market model with general…How Close to the Theme? Similarity-Label Conditioning for Game Music Generation
Composers develop music from an original idea, controlling how similar each new section is to it, from near repetition to new material.Infinite Worlds from One Example: What Local Generators Must Share
Seeded noise lets games generate any region of an unbounded world on demand.Adaptive Land Units from Earth Embeddings
Modeling land use starts with a choice of spatial units, typically a regular grid of pixels whose resolution is set by the spatial detail the process requires and, often more critically, by the…Efficient Conformal Calibration for Paired Recommendation Decisions
Risk control can suppress useful changes to a frozen recommendation rule.Robust Reward Machine Learning and Execution in Noisy Environments
Reward machines (RMs) represent non-Markovian reward functions as finite-state machines over high-level propositional events.On Sparse Graph Limits for Neural Combinatorial Optimization
Graph neural networks are often trained on small graphs and deployed on larger ones, raising the question of which graph information must be preserved for combinatorial optimization values to…Synergetic Autonomous Intelligence: Three Axioms for Recursive Semi-Closed Learning
We introduce Synergetic Autonomous Intelligence (SAI), a theory and design program for learning systems that form, preserve, revise, and compose relations while continuing to learn.Change the Funnel, Not Who May Submit: Engineering Peer Review for the Flood
Every reviewer knows the feeling: more papers each cycle, three full reviews for each of them, and a suspicion that near the accept line the outcome is luck.Multi-Turn Semantic Caching for Low-Cost LLM Serving
Semantic caching lowers the cost of serving large language models (LLMs) by reusing stored responses for similar requests.VeilFL: Two-Stage Accountability for Anonymous Federated Learning
Anonymous credentials can hide which registered client participates in federated learning, but their unlinkability also makes repeated misconduct difficult to associate.Scute: Exact Batched Serving for PEFT Adapters Beyond LoRA
Existing serving systems for large language models batch requests for many different LoRA adapters on one GPU.Mitigating Catastrophic Forgetting in Task-Free Federated Continual Forecasting via Two-Tier Replay under Concept Drift
Federated time-series forecasting is increasingly important in applications where temporal data are distributed across privacy-sensitive clients, such as environmental monitoring, smart cities, and…Digital Twin-Assisted Fast Beam Alignment for mmWave MIMO Networks
Millimeter-wave (mmWave) communication relies on directional beam sweeping for initial access, which incurs substantial latency and signaling overhead as antenna arrays grow large and deployments…Zero-Gated Cross-Attention
Injecting non-text modalities into frozen language models often introduces early optimization instability, making it difficult to separate architectural gains from transient training dynamics.