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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 206
Baselines and Score Centering in Policy Gradient Estimation
Reinforcement learning has become a widely used approach to post-training large language models.Librarian Agents: Training LLMs to Curate Long-Context Workspaces that Anticipate Future Queries
Reasoning over long document contexts remains a challenge for large language models (LLMs).Asking Smarter Questions: Targeted Active Preference Learning for Underspecified Rewards
Reward learning typically assumes the human's input covers everything that matters for the task.Learning Rational Strategies for Temporal Objectives in Multi-Agent Systems
We study rational synthesis for stochastic multi-agent systems with unknown dynamics, where each agent is equipped with its own probabilistic temporal objective specified using Probabilistic Linear…CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty
Large language models (LLMs) are becoming prevalent in scenarios where honesty is critical.Towards Continual Learning: Mitigating Forgetting With Subspace Tuning
Large language models (LLMs) acquire new skills through fine-tuning, but it can destroy capabilities they already have: catastrophic forgetting remains a central obstacle to continual learning in…Backward Compatibility in Zero-Bit Neural Audio Watermarking
Neural watermarking systems are typically trained as tightly coupled embedder-detector pairs and implicitly assume static deployment.Knowledge That Is Linear Before Fine-Tuning Generalizes After It
Not all facts a language model can recall support further learning equally well.Learning to Steer LLM Agents and Multi-Agent Systems
Large language model (LLM)-based agents and multi-agent systems increasingly tackle complex tasks through long-horizon tool use and inter-agent collaboration.Twice Upon a Time: Complementary Representations for Time-Series Reasoning
Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what information should their time-series…Robust Reinforcement Learning for Dynamic Treatment Regimes under Model and Measurement Uncertainty
We develop a robust reinforcement learning (RL) framework for learning adaptive treatment policies that generalize across patients and remain reliable under errors in the measured biomarker and…Lean Graph Search for Formal Theorem Proving
Retrieving relevant lemmas is crucial for formal theorem proving, enabling provers to build machine-checkable proofs from established mathematical results.GeoState: Learning View-Decoupled Geometry States for 3D World Modeling
Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometric priors.MLExpert: Towards a Generalist Agentic Model for Autonomous Machine Learning Engineering
Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI4AI) as a pathway toward…Rethinking Routing Exploration in Modern Mixture-of-Experts
Mixture-of-experts (MoE) models have become an important approach for scaling model parameters.PathFM: Fast Generative Forecasting of Multivariate Trajectories
Time series foundation models are becoming increasingly popular for general-purpose forecasting.LIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
Personalization is essential for general-purpose robots to transition into household environments and achieve true practicality.CGDT-CESN: Correlation-Guided and Dynamics-Trained Clustered Echo State Network for Multivariate Time-Series Prediction
Accurate prediction of multivariate time series requires models that simultaneously capture variable-specific dynamics and cross-variable interactions.GPU-Accelerated Robust MA--RIS Pre-Optimization for Communication and Target Illumination
Movable antennas (MAs) and reconfigurable intelligent surfaces (RISs) offer strong spatial control for integrated sensing and communication (ISAC), but repeatedly adapting MA positions and RIS…An Adaptive-Horizon Graph Neural Operator for coupled surrogate morphodynamic modelling
Morphodynamic simulations require repeated coupling between hydrodynamic solvers, sediment transport modules, and bed updating.