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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 8
Dynamic Optimistic Constrained OCO with Memory via Delay Equivalence
Online Convex Optimization with memory and time-varying constraints (COCO-M) is a recently-introduced framework that captures the dynamics of stateful online learning and non-stochastic control with…Measured Coupling for Parallel Decoding in Diffusion Language Models
Diffusion language models can write many tokens per step, but must choose which tokens are safe to commit together.RM-VLM: From Natural-Language Task Descriptions to Vision-Grounded Reward Machines
Reward machines (RMs) have been proposed as a reward formulation in reinforcement learning (RL) to capture non-Markovian tasks where credit assignment depends on history.Interpretable many-body interaction laws for collective motion from few trajectories
Models of collective motion usually reduce social interactions to pairwise forces, despite empirical evidence for many-body effects.Benchmarking Large Language Models on Heterogeneous Cognitive and Biomedical Knowledge Graphs: The Role of Graph Grounding in Multi-Hop Reasoning and Hallucination Mitigation
Large language models (LLMs) are increasingly used in biomedical and cognitive neuroscience, but their ability to reason reliably over heterogeneous knowledge graphs (KGs) remains unclear.Discovering Learning Rules that Shape Others
In general-sum games, self-interested learners can reach outcomes that are poor for everyone, which has motivated methods that shape the opponent's learning.4D Point Splatting for mmWave Radar Micro-Doppler Differentiable Rendering
Millimeter-wave radar resolves the micrometer displacements of a moving body as micro-Doppler, enabling gait, gesture, activity, pose and vital-sign sensing.USB Gym: A Gymnasium Testbed for Closed-Loop Ultrasound View Matching
Background and Objective: Our main goal is ultrasound guidance: moving a probe until its image matches a target view.Unifying Central Flow, Rod Flow, and the Edge Coupling
At the edge of stability, the iterates of gradient descent oscillate along the sharp directions of the Hessian.StrataFlux: Memory-Hierarchy-Native Low-Bit LLM Inference
Quantization reduces the memory and bandwidth demands of large language model (LLM) inference but can degrade accuracy; offloading higher-precision data can instead stall generation.SHORE: Stability-Hybrid On-Policy Reinforcement Learning for Online Bin Packing
Online 3D bin packing with a processing buffer requires choosing which box to pack, its orientation, and its placement while keeping the stack stable under unknown future arrivals.Muir: Linear Attention with Sensitivity-Allocated Gating and Matched-Filter Readout
Linear attention compresses context into a fixed-size key-value state for linear-time training and constant-memory inference.Module-Aware Optimization for Graph Neural Networks
Different optimizers impose different geometries on parameter updates.Hybrid Machine Learning for Imbalanced Landing-Phase Safety Event Prediction from Flight Data
Landing-phase safety-event prediction requires the detection of rare abnormal approaches within strongly imbalanced multivariate flight data.Synthesis of Ovarian Cancer Multi-Omics Datasets: A Biology-Informed Evaluation Framework
Paired multi-omic cancer cohorts are costly to assemble and difficult to share, motivating synthetic cohorts as a complementary resource.StepBack: Step-Level Error-Localized Resampling for Efficient Test-Time Reasoning
Self-consistency (SC) is a widely used decoding strategy for improving chain-of-thought reasoning, but it requires sampling many complete reasoning trajectories with a preset budget.Social Humanoid: Socially Responsive Human-Humanoid Interaction
Humanoid robots are typically trained as solitary agents, leaving them unable to coordinate physically with human partners who naturally anticipate and adjust to one another.Conformal Prediction for Time-Dependent PDEs
Uncertainty quantification is crucial in scientific machine learning, where models inform safety-critical tasks such as flood forecasting, financial risk management, and thermal control in machines.Spectral and Subspace Dynamics of LoRA in Supervised Fine-Tuning and Reinforcement Learning
Low-rank adaptation (LoRA) is commonly used in both supervised fine-tuning (SFT) and reinforcement learning (RL), often under similar optimizer settings.On the limitations of molecular representations
Molecular representations such as fingerprints and learned embeddings play a central role in cheminformatics and small-molecule machine learning.