3/25/2026
Symbolic Graph Networks for Robust PDE Discovery from Noisy Sparse Data
Symbolic Graph Networks framework for discovering PDEs from noisy, sparse observational data using machine learning instead of numerical differentiation.
3/25/2026
Learning When to Act: Interval-Aware Reinforcement Learning with Predictive Temporal Structure
Reinforcement learning approach for learning optimal decision timing in continuous environments using predictive temporal signals.
3/25/2026
Neural Structure Embedding for Symbolic Regression via Continuous Structure Search and Coefficient Optimization
Symbolic regression framework using continuous structure search and neural embeddings for interpretable equation discovery.
3/25/2026
Model Predictive Control with Differentiable World Models for Offline Reinforcement Learning
Offline reinforcement learning with model predictive control using differentiable world models for inference adaptation.
3/25/2026
SkillRouter: Retrieve-and-Rerank Skill Selection for LLM Agents at Scale
Skill retrieval and ranking system for LLM agents selecting relevant tools from thousands of overlapping options at scale.
3/25/2026
A Theoretical Framework for Energy-Aware Gradient Pruning in Federated Learning
Energy-aware gradient pruning framework for federated learning accounting for hardware transmission costs.
3/25/2026
Multimodal Training to Unimodal Deployment: Leveraging Unstructured Data During Training to Optimize Structured Data Only Deployment
Multimodal training framework leveraging unstructured clinical notes to improve structured EHR data deployment.
3/25/2026
MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data
Computational framework for inferring stochastic cellular trajectories from single-cell and spatial transcriptomics data.
3/25/2026
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks
Foundation model for time-series in-context learning using quantile-regression T5 with instruction conditioning.
3/25/2026
Precision-Varying Prediction (PVP): Robustifying ASR systems against adversarial attacks
Adversarial robustness technique for ASR systems using precision-varying inference to defend against attacks.
3/25/2026
Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
Causal discovery method for chain-reaction systems using interventional data to identify cascade-like causal structures.
3/25/2026
Transfer learning via interpolating structures
Transfer learning approach for structural health monitoring using intermediate structures to bridge disparate datasets.
3/25/2026
Generalizing Dynamics Modeling More Easily from Representation Perspective
Neural dynamics modeling from latent space representations for complex systems like climate and fluid dynamics.
3/25/2026
Bounding Box Anomaly Scoring for simple and efficient Out-of-Distribution detection
Post-hoc out-of-distribution detection using bounding box anomaly scoring in neural network feature spaces.
3/25/2026
Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography
Deep learning method for analyzing unordered biomedical tabular data using vision architectures and spatial cartography.
3/25/2026
Coordinate Encoding on Linear Grids for Physics-Informed Neural Networks
Proposes coordinate encoding on linear grids to improve physics-informed neural networks for solving PDEs.
3/25/2026
Non-Adversarial Imitation Learning Provably Free of Compounding Errors: The Role of Bellman Constraints
Analyzes non-adversarial Q-based imitation learning with Bellman constraints, showing IQ-Learn doesn't outperform behavioral cloning as believed.
3/25/2026
Double Coupling Architecture and Training Method for Optimization Problems of Differential Algebraic Equations with Parameters
Dual physics-informed neural network architecture for multi-task optimization of differential algebraic equations with parameters.
3/25/2026
Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication
Personalized federated learning framework for analyzing brain signals in BCI-enabled immersive communication systems.
3/25/2026
Multitask-Informed Prior for In-Context Learning on Tabular Data: Application to Steel Property Prediction
Applies multitask-informed in-context learning to tabular data for predicting steel properties during hot rolling manufacturing.
3/25/2026
From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips
Studies robustness of logic and lookup-based neural networks to hardware bit-flip errors, comparing to precision reduction approaches.
3/25/2026
Caterpillar of Thoughts: The Optimal Test-Time Algorithm for Large Language Models
Theoretical framework for optimal test-time computation strategies in LLMs, modeling sampling, chain-of-thought, and backtracking with computation budgets.
3/25/2026
Transformers Trained via Gradient Descent Can Provably Learn a Class of Teacher Models
Theoretical analysis proving transformers can learn a class of teacher models including convolutional and attention-based architectures via gradient descent.
3/25/2026
Universal and efficient graph neural networks with dynamic attention for machine learning interatomic potentials
Graph neural network with dynamic attention for computing interatomic potentials efficiently in molecular dynamics simulations.
3/25/2026
Towards The Implicit Bias on Multiclass Separable Data Under Norm Constraints
Studies implicit bias of gradient-based algorithms on multiclass separable data using normalized steepest descent framework.
3/25/2026
The Coordinate System Problem in Persistent Structural Memory for Neural Architectures
Introduces dual-view pheromone pathway network architecture investigating requirements for persistent structural memory in neural networks.
3/25/2026
Confidence Calibration under Ambiguous Ground Truth
Addresses confidence calibration when annotators disagree, showing structural failures of standard calibration methods on majority-voted labels.
3/25/2026
TreeTeaming: Autonomous Red-Teaming of Vision-Language Models via Hierarchical Strategy Exploration
Automated red-teaming framework using hierarchical strategy exploration to discover vulnerabilities in vision-language models.
3/25/2026
Balancing Safety and Efficiency in Aircraft Health Diagnosis: A Task Decomposition Framework with Heterogeneous Long-Micro Scale Cascading and Knowledge Distillation-based Interpretability
Task decomposition framework for aircraft health diagnosis using hierarchical cascading and knowledge distillation for interpretability.
3/25/2026
Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics
Proposes identifiable variational dynamic factor model for learning latent factors from time series with theoretical identifiability guarantees.
3/25/2026
VLGOR: Visual-Language Knowledge Guided Offline Reinforcement Learning for Generalizable Agents
Combines vision, language, and offline RL to train generalizable agents that understand environmental dynamics and task instructions.
3/25/2026
Weak-PDE-Net: Discovering Open-Form PDEs via Differentiable Symbolic Networks and Weak Formulation
Framework for discovering partial differential equations from sparse noisy data using differentiable symbolic networks and weak formulation.
3/25/2026
Asymptotic Learning Curves for Diffusion Models with Random Features Score and Manifold Data
Theoretical analysis of denoising score matching for diffusion models on low-dimensional manifolds using random feature neural networks.
3/25/2026
Can Graph Foundation Models Generalize Over Architecture?
Studies whether graph foundation models can generalize across different GNN architectures and graph characteristics, revealing limitations in current approaches.
3/25/2026
Robustness Quantification and Uncertainty Quantification: Comparing Two Methods for Assessing the Reliability of Classifier Predictions
Compares robustness quantification and uncertainty quantification methods for assessing classifier prediction reliability under distribution shift.
3/25/2026
A Sobering Look at Tabular Data Generation via Probabilistic Circuits
Critical analysis of tabular data generation via probabilistic circuits, questioning progress claims and evaluation protocols in current benchmarks.
3/25/2026
Assessing the Robustness of Climate Foundation Models under No-Analog Distribution Shifts
Evaluates robustness of climate foundation models under out-of-distribution shifts from unprecedented climate states.
3/25/2026
Generalization Bounds for Physics-Informed Neural Networks for the Incompressible Navier-Stokes Equations
Theoretical generalization bounds for physics-informed neural networks solving incompressible Navier-Stokes equations.
3/25/2026
MsFormer: Enabling Robust Predictive Maintenance Services for Industrial Devices
MsFormer transformer-based framework for predictive maintenance in industrial IoT environments with complex sensor data dependencies.
3/25/2026
Policy-based Tuning of Autoregressive Image Models with Instance- and Distribution-Level Rewards
Reinforcement learning approach for training autoregressive image models with policy-based tuning optimizing quality and diversity simultaneously.
3/25/2026
SpecXMaster Technical Report
AI system for automated spectroscopy interpretation in scientific discovery, reducing human bias in spectral analysis.
3/25/2026
Polaris: A G\"odel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair
Polaris framework enabling self-improving agents for small language models through policy repair via experience abstraction and code modifications.
3/25/2026
A Bayesian Learning Approach for Drone Coverage Network: A Case Study on Cardiac Arrest in Scotland
Bayesian learning framework for designing drone-assisted AED delivery networks in emergency medical services.
3/25/2026
DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models
Adaptive prompt routing mechanism for selecting appropriate LLM or generative model based on input prompts, balancing fidelity and diversity.
3/25/2026
A Schr\"odinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
Mathematical framework for solving high-dimensional stochastic optimal control problems with long horizons using Schrödinger eigenfunction methods.
3/25/2026
Sparser, Faster, Lighter Transformer Language Models
Sparse packing format and CUDA kernels leveraging unstructured sparsity in LLM feedforward layers to reduce computational costs and model size.
3/25/2026
A One-Inclusion Graph Approach to Multi-Group Learning
Tight upper bounds on sample complexity for multi-group learning using one-inclusion graph prediction strategy and bipartite matching.
3/25/2026
General Machine Learning: Theory for Learning Under Variable Regimes
Foundational theoretical framework for learning under regime variation where learner, memory state, and evaluation conditions evolve over time.
3/25/2026
GEM: Guided Expectation-Maximization for Behavior-Normalized Candidate Action Selection in Offline RL
Offline reinforcement learning method using guided expectation-maximization for action selection from multimodal action distributions in fixed datasets.
3/25/2026
Neural ODE and SDE Models for Adaptation and Planning in Model-Based Reinforcement Learning
Model-based reinforcement learning using neural ODEs and SDEs to capture stochastic dynamics in fully and partially observed environments.