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Machine Learning
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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 117
StateWise: Teaching Language Models to Track and Obey Evolving Constraints in Multi-Turn Dialogue
Users of conversational assistants rarely state all requirements up front: they add constraints, amend them, withdraw them, digress, and return.CFL-aware edge design for graph neural solvers of hyperbolic transport
Hyperbolic partial differential equations (PDEs) transport information at finite speed along characteristics, often producing shocks and discontinuities that are challenging to capture numerically.An actively trained neural operator for near-explicit atmospheric chemistry
Earth-system models simplify atmospheric chemistry into condensed mechanisms, because near-explicit mechanisms such as the Master Chemical Mechanism (MCM) are too costly to solve in every grid cell.TriageRAG: Failure-Aware Self-Training for Adapting Retrieval-Augmented Language Models to Specialized Domains
Retrieval-augmented generation (RAG) lets large language models (LLMs) answer knowledge-intensive questions from retrieved evidence, but adapting a general-purpose RAG system to a specialized domain…The Geometry of Limits in ReLU Function Spaces
We study the geometry and closure of spaces of functions realized by ReLU neural networks of fixed architecture.Greedy Orthogonal Polynomial Manifolds with Lipschitz Control for Dimensionality Reduction and Reduced Modeling
Polynomial manifolds provide nonlinear low-dimensional representations through polynomial decoders.Unlocking the Specialization Capability of PPG Foundation Models for Wearable Signals through Structured Pruning and Adaptive Fine-Tuning
Photoplethysmography (PPG) plays a central role in wearable health monitoring and clinical decision support.One Scan is Enough: Demonstration-Free Adaptation for Language-Guided Navigation
Deploying a language-guided navigation policy in a new building usually means watching it fail.ProMo3D: Probing Motion Cues in Frozen 3D Foundation Models
Feed-forward 3D foundation models have recently reshaped multi-view reconstruction, yet dynamic 4D understanding still often relies on large-scale motion supervision or hand-crafted…Rectified Language Flow
Continuous-state flow and diffusion models offer a promising approach to fast, parallel language generation, but matching the generation quality of autoregressive models remains challenging.Memory or a Clock? Auditing a Memory Advantage in XLand-MiniGrid with Seeds, Maps and Evaluation Noise Apart
On a partially observable XLand-MiniGrid task, an LSTM agent beats a memory-free MLP by 25 percentage points.Learning What to Share: Expert Specialization for Time-Series Forecasting
A central challenge in multivariate forecasting is deciding what to share across channels and where to specialize.Reactive Optimizers
We study a reactive optimizer that uses a pretrained language-model agent to inspect training dynamics and rewrite executable optimizer code during a single training run.EEGBiFormer: Real-Time EEG Attention Classification via Hybrid CNN-Transformer with EEG-Informed Auditory Protocol Validation
Sustained attention is critical for academic performance, yet existing auditory support tools are static and not grounded in real-time neural evidence.Hessian-Similar Optimization with Capped Participation: Lower Bounds and Virtual Masters
What is the round complexity of Hessian-similar optimization when each round can contact at most $s$ of $m$ clients?EdgeDeID: A 0.6B Clinical De-identifier Trained Without Real Patient Data
De-identifying clinical notes with a hosted language model discloses the information the step is meant to protect.Sliding Networks: A Family of Residual Structures Preserving Feature Learning and Feature Diversity
Deep learning models tend to perform best at large widths and depths.Grounding on Request: Learning Modality Control in Vision-Language Models
When an image and its caption disagree, can a user reliably control which one a vision-language model (VLM) follows?Approximate Universal Prediction under Interaction
Bayesian mixtures, and Solomonoff induction in particular, provide an idealized model of prediction learned by minimizing population log loss, and they underlie universal agents such as AIXI.Build, Don't Play: Self-Improving LLM Research Agents Develop a Hearthstone Battlegrounds AI That Rivals Top Players
Can LLM agents carry a hard real-world problem from raw data to a system that holds its own against people?