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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 245
Code-Interactive Visual Reasoning for Financial Candlestick Understanding
Financial candlestick understanding requires locating visual elements, aligning them across trading dates and panels, and combining observations through numerical and financial reasoning.HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning
Electroencephalography (EEG) representation learning is challenged by noisy signals, inter-subject variability, and heterogeneous electrode montages in different datasets and recording settings.JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image
We study forecasting rigid-body motion from a single image: generating diverse and physically plausible future trajectories for arbitrary points in a scene, without building rigidity into the…Prorsa: Unleashing the Potential of Prefill-Decode Disaggregation in Agentic Reinforcement Learning
Agentic reinforcement learning (RL) is commonly used to enhance the capabilities of large language models (LLMs) in solving complex multi-turn tasks.Towards Modality-Agnostic Seizure Classification: A Unified Deep Learning Framework for Heterogeneous EEG and Intracranial EEG Signals
Seizure prediction and detection, essential for clinical treatment of epilepsy, remain the crucial task of this neurological disease.DEFlow: Deep Equilibrium Flow Maximum-Entropy Reinforcement Learning
Expressive flow policies can represent multiple high-value actions, but sampling them with few integration steps while retaining tractable action densities remains challenging.DR-APO: Decoupled-Representation Advantage-Guided Policy Optimization from Continuous Control to Embodied Navigation
Policy representations in reinforcement learning have expanded beyond Gaussian policies to diffusion and flow-matching based generative policies.Integrating Feature Understandability into Feature Selection for Human-Centred Tabular Explanations
Existing human-centred XAI research predominantly evaluates explanations after they have been generated.AeroChem: Closed-loop Physics-Informed State Space Modeling for Long-term Chemically-Reactive Air Quality Forecasting--Extended Version
Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions underlying secondary pollutant formation.ACED: Reference-Anchored Aggregation of Natural-Language and Executable Evidence for Mathematical Reasoning
Natural-language self-consistency and executable programs provide complementary test-time evidence for mathematical reasoning, yet either channel may support the same semantic error.Learning Deployable Causal Action Geometry under Temporal Non-Stationarity
Learning a response law for continuous decisions from observational time series is central to many real-world decision systems, yet temporal non-stationarity poses a fundamental challenge: as…Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting
Recovering divergence-free velocity fields from sparse and corrupted observations requires reconciling physical consistency, expressive representations, and robustness to missing data.IND-Eval: Aligning Evaluation and Simulation for Industrial Time Series Foundation Models
We introduce IND-Eval, a public benchmark that organizes industrial time series across domains into source-specific forecasting tasks.Counting with Attention and LayerNorm: Norm Scaling and Representation Geometry
Counting is a simple task on which transformers can nevertheless fail at long sequence lengths.Guidance Without Labels: Flow Matching from Coupled Gaussian Mixtures
Flow matching models are typically trained to transport a Gaussian source to the data distribution, with source and target samples paired independently.RFWeave: Learning Wireless Propagation Across Scenes and Transceiver Configurations
Wireless propagation modeling is foundational to the evaluation and design of modern communication systems.Compression Through Time: An Interplay of Separability, Stationarity and Capacity
Information-theoretic and geometric compression have been widely studied as possible explanations for generalization.Making LoRA Identifiable: Orthogonal Alignment for Continual Learning
There is growing interest in applying Parameter-Efficient Fine-Tuning (PEFT) to Continual Learning, as it enables faster training, mitigates catastrophic forgetting, and facilitates better…Amortized Variational Inference of Latent Intensities from Replicated Point Patterns
Bayesian inference for latent point process intensities often relies on per-dataset sampling or optimization, making repeated inference computationally expensive.Spectral Costs of Multinomial and Residual Resampling in High-Dimensional Particle Ensembles: A Free-Probability Analysis
Resampling is the standard remedy against weight degeneracy in particle filters, yet its effect on the spectrum of the particle second-moment matrix is poorly understood.