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The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 181
Prototype-Guided Optimization of Quantum Data Embeddings with Linear Cost
In supervised quantum machine learning with classical data, classification performance critically depends on the geometry induced by quantum data embedding.Cross-Dimension and Cross-Modality Relational Tensor Representation Learning for Multimodal Health Data Modeling
Multimodal health data integrate information from heterogeneous clinical sources, creating substantial opportunities for data-driven decision support.Margin-Based Generalization for Quantum Machine Learning with Classical Data Encoding
Understanding generalization is essential for assessing the practical viability of quantum machine learning.Transport What Shares the Conduction Pathway: Normal-Anchored SPD Geometric Transport for Source-Free Patient Adaptation of Holter and Patch ECG
Electrocardiogram (ECG) beat classifiers lose accuracy on new patients and devices, and source-free adaptation methods that assume class-balanced target batches fail on real recordings, whose…Transformers as Adaptive Kernel Learners across Tasks for In-Context Learning
Transformers have emerged as a dominant architecture in modern machine learning, with in-context learning (ICL) enabling models to adapt to new tasks by conditioning on prompts, without any…Near-Optimal Regret for Semi-Bandit Learning of Monotone Stochastic Problems
We consider the task of learning an (approximately) optimal policy for stochastic optimization problems where the true distributions are unknown.Generative Retrieval for Reverse Target Fishing with a Proteome-Scale Benchmark
Reverse target fishing identifies protein targets for a query molecule and is central to drug discovery and repurposing.Measuring Empowerment from Offline Data for Intrinsically Motivated Exploration
Large, unlabeled datasets of prior experience have become increasingly available for agentic tasks in domains such as robotics and coding.Private Evaluation of High-Dimensional Functions
We study differentially private black-box evaluation of arbitrary high-dimensional functions.Write Once, Check Many: Reusable Ledgers for Post-Hoc Policy Compliance Auditing of Agent Trajectories
Auditing LLM agents against policies is critical to ensure safety but requires rereading long trajectories once per policy.VBO-MI: A Differentiable Black-Box Optimization Framework via Variational Mutual Information Estimation
Many real-world tasks require optimizing expensive black-box functions accessible only through noisy evaluations, a setting commonly addressed with Bayesian optimization.CoTs remain monitorable when being unfaithful requires computation: Replicating and Extending the Necessity Effect Across Eleven Models
While a LLM's chain of thought (CoT) is a promising approach to interpreting model outputs, prior work shows CoT's content does not always accurately reflect the reasoning process.TideKV: Delayed KV Eviction via Layer-Wise Chunked Prefill for Memory-Efficient Long-Context LLM Inference
Long-context large language model (LLM) inference is important for modern intelligent applications but remains constrained by peak memory during prompt prefill.HiPPO Functional Memory: Coordinate-Queryable Attention for Irregular Time Series
Irregular time series require models to answer temporal queries at arbitrary coordinates, yet existing approaches typically retain observation-dependent representations that must be repeatedly…BEM: Learning Bregman Divergences for Concept Erasure in Flow Matching Models
Concept erasure removes harmful, private, or copyrighted concepts from text-to-image models while preserving their other abilities.Denoising Implicit Variational Inference
Semi-implicit variational inference (SIVI) expands the representational capacity of variational families, but optimizing the Evidence Lower Bound (ELBO) remains challenging because the marginal…What "Form'' of Uncertainty Does Conformal Prediction Quantify?
Conformal prediction (CP) is a post-hoc calibration method that returns prediction sets with distribution-free coverage guarantees, and the size of the output set is often interpreted as a notion of…TopoCompile: Molecular Generation with Exact Global Count Constraints
Molecular generation designs novel molecules with desired structures and properties.ProbePO: Sparse Probes, Redistributed Credit for Critic-Free LLM Reinforcement Learning
Reinforcement learning from verifiable rewards assigns one terminal reward to an entire reasoning trajectory, obscuring how individual reasoning steps contributed to the outcome.Reconstruction of Unobserved Core Electron Density in Tokamak Plasmas with a Neural Operator Transport Surrogate and Uncertainty Quantification
Real-time control of tokamak plasmas requires the electron density profile.