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Local Ai

Language Models Need Sleep

DGX agent

arXiv:2605.26099v1 Announce Type: cross Abstract: Transformer-based large language models are increasingly used for long-horizon tasks; however, their attention mechanism scales poorly with context le

local-aiarxiv-cs-ai

26 May 2026

Applications

Language Movement Primitives: Grounding Language Models in Robot Motion

DGX agent

arXiv:2602.02839v3 Announce Type: replace Abstract: Enabling robots to perform novel manipulation tasks from natural language instructions remains a fundamental challenge in robotics, despite signific

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Language Models Need Sleep

Language Movement Primitives: Grounding Language Models in Robot Motion

LAPLEX: The FFT of Learnable Laplace Kernels

Large Language Model Selection with Limited Annotations

Latent Q-Barrier Shielding for Safe In-Context Reinforcement Learning

Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning

Lattice theory and algebraic models for deep convolutional learning based on mathematical morphology

LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition

Lean Formalization of Generalization Error Bound by Rademacher Complexity and Dudley's Entropy Integral

Learning Concepts, Not Tokens: Self-Supervised Semantic Alignment for Language Models

Learning dynamical systems with biochemically informed neural ordinary differential equations

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

Learning High-Frequency Continuous Action Chunks in Latent Space

Learning in Low-Dimensional Subspaces: Orthogonal Bottlenecks for Reinforcement Learning

Learning Laplacian Eigenspace with Mass-Aware Neural Operators on Point Clouds

Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction

Learning, locomotion, and navigation of soft synthetic snakes in three-dimensional, heterogeneous environments

Learning manifold diffusion semigroups from graph transition matrices

Learning Permutation from Structure Without Supervision

Learning Protein Structure-Function Relationships through Knowledge-guided Representation Decomposition

Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

Learning Sparse Compositional Functions with Norm-Constrained Neural Networks

Learning to Reason Efficiently with A* Post-Training

Learning to Route Languages for Multilingual Policy Optimization

Learning to Search and Searching to Learn for Generalization in Planning

Learning to Trust: Bayesian Adaptation to Varying Suggester Reliability in Sequential Decision Making

Learning Transferable Motor Skills for Geometry-Aware Robotic Surface Tasks

Learning Treatment Effects during Resource Allocation via Priority-Queue Randomization

LECTOR: Joint Optimization of Scientific Reasoning Graphs and Introduction Generation

Length Generalization with Log-Depth Recurrent Units

LETS Forecast: Learning Embedology for Time Series Forecasting

Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems

Leveraging pretrained RGB denoisers for hyperspectral image restoration

Leveraging Spreading Activation for Improved Document Retrieval in Knowledge-Graph-Based RAG Systems

LGMT: Logic-Grounded Metamorphic Testing for Evaluating the Reasoning Reliability of LLMs

LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

Lidar Scan Registration Robust to Extreme Motions

Lifted Schrodinger Bridges for Gaussian Mixture Endpoints: Projection Gaps and Path-Space Obstructions

LipoAgent: Coordinating Fine-Tuned LLM Agents for Safer Lipid Design

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

Llamion Technical Report

LLM Agent Based Renewable Energy Forecasting Using Edge and IoT Data A Review of Solar Wind Weather and Grid Aware Decision Support

LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers

LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs

LLM-SAA: LLM-persona Generated Distributions for Decision-making

LLMs Show No Signs Of Individuated Metacognition

LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots

Lngram: N-gram Conditional Memory in Latent Space