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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.
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Newest papers, page 160
The Data Differentiator Framework (DDF): Quantifying Marginal Data Value with Information-Theoretic and Game-Theoretic Measures in an Agentic Evaluation Pipeline (SDSAE)
In data-rich enterprises the hard question is not whether a candidate dataset is good in isolation, but whether it adds information beyond what the organization already holds, and whether that…Auditing Conformal Prediction for Language Models Under Inference-Time Model Shift
Conformal prediction (CP) for language models is typically evaluated under a matched protocol, in which calibration and deployment use the same post-training inference configuration, such as…Multi-Objective Protein Optimization via Modular Diffusion Steering
Protein engineering often requires improving several properties simultaneously, motivating the search for high-performing sequences that represent useful fitness tradeoffs.Is 2:4 Sparsity Still Worth It? Semi-Structured Sparsity versus Quantization in LLM Inference
NVIDIA tensor cores have supported 2:4 semi-structured sparsity since Ampere, and the pattern composes with quantization.Online Open-World Wafer Defect Discovery using Hyperdimensional Computing
Conventional wafer defect analysis relies on offline, closed-world classifiers that fail to detect novel, unseen defect signatures emerging during continuous semiconductor manufacturing.HyperDrone: Simulation-to-Reality Transfer at Millions of Frames per Second
We present HyperDrone, an extremely fast quadrotor simulator focused on high-performance batch rendering that is more than 20x faster than existing state-of-the-art batch quadrotor simulators.Transformers as Generic Deep Neural Networks: Exact Compilation, the Cost of Removing Activation-Activation Products, and Multi-Agent Attention Clustering
Transformers are deployed as a special model class.Can Quantum Layers offer Performance and Security Advantages in Vision-Language Models?
As quantum computing moves from the noisy intermediate-scale quantum (NISQ) era toward early fault-tolerant quantum computing (EFTQC), quantum-enhanced AI is shifting from a conceptual idea to…Unit-Aware Differentially Private Quantum Machine Learning for Clinical and Wearable Health Data
Clinical registries and wearable sensors support early health-risk assessment, yet models trained on these records may leak sensitive information when released.From Weather to Enhanced Weathering: Weather Foundation Models for Carbon Dioxide Removal at Operational Scale
Enhanced Rock Weathering (ERW) is a carbon removal solution with the potential to remove gigatons of CO$_2$ per year, but quantifying that removal today requires dense soil sampling and laboratory…How Does Orthogonalization Adapt to the Neural Network Hessian Structure? A Gradient Self Outer-Product Analysis at Initialization
Muon orthogonalizes a weight matrix's momentum before each step, and on neural networks this simple preconditioner beats AdamW in a wide range of tasks.SSMCGM-Stream: A Streaming State-Space Model for Personalized Diabetes Management
Continuous glucose monitoring supports diabetes management but requires forecasting models that are accurate, interpretable, and efficient enough for real-time deployment.Is In-Context Reinforcement Learning A Posterior Sampler? An Empirical Study
In-context reinforcement learning (ICRL) exploits the impressive in-context learning ability of large language models to zero-shot generalize to new, unseen tasks at inference time without any…From Common Information to Canonical Correlation Analysis and Beyond: Bridging Information Theory, Signal Processing, and Machine Learning
Many problems in signal processing, machine learning, and neuroimaging provide several jointly observed measurements of one process, each mixing a component common to all of them with a component…Attention-based Classification for Indirect Prompt Injection
Indirect prompt injection (IPI) attacks, in which adversarial instructions are embedded in external data processed by a language model, pose a significant threat to the integrity of deployed LLM…AgentPolicyForge: From Executable Environments to Policy Benchmarks and Adaptive Guards
Customized agent deployments define policies over tools, resources, and execution conditions.Doob-Based Generative Policy Optimization
Diffusion and flow models provide expressive policy classes for robotic and sequential decision-making systems.The Optimal Sampler for Diverse TSP Solutions: Characterization, Limits, and Learning
We address the Diverse Traveling Salesman Problem (D-TSP) that seeks a set of $k$ distinct TSP tours.Rethinking Time Series Tokenization from a Frequency Perspective
Tokenization that partitions time series into subsequences has become a foundational paradigm in modern time series modeling.FlashNext-RL: A System Optimization Study for Long-Horizon Agentic RL of Qwen3.8-Flash-Next
Long-horizon agentic reinforcement learning (RL) requires both efficient rollout generation and training on long sequences.