3/17/2026
Few Batches or Little Memory, But Not Both: Simultaneous Space and Adaptivity Constraints in Stochastic Bandits
Analysis of space and adaptivity constraints in stochastic multi-armed bandits with memory limitations.
3/17/2026
Manifold-Orthogonal Dual-spectrum Extrapolation for Parameterized Physics-Informed Neural Networks
Manifold-orthogonal extrapolation method for physics-informed neural networks handling out-of-distribution regimes.
3/17/2026
Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning
Dynamic curriculum learning approach using gradient-based difficulty estimation for adaptive example ordering.
3/17/2026
Greedy Information Projection for LLM Data Selection
GIP framework for selecting training examples for LLM fine-tuning by maximizing mutual information with task-specific signals.
3/17/2026
IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring
IGU-LoRA: adaptive rank allocation for parameter-efficient fine-tuning of LLMs using integrated gradients and uncertainty scoring.
3/17/2026
Computation and Communication Efficient Federated Unlearning via On-server Gradient Conflict Mitigation and Expression
Federated unlearning framework reducing computation and communication costs via gradient conflict mitigation.
3/17/2026
Node Role-Guided LLMs for Dynamic Graph Clustering
LLM-guided approach for interpretable dynamic graph clustering with semantic explanations of cluster formation and evolution.
3/17/2026
Prototypical Exemplar Condensation for Memory-efficient Online Continual Learning
Memory-efficient continual learning using prototypical exemplar condensation to reduce stored samples per class.
3/17/2026
Collapse or Preserve: Data-Dependent Temporal Aggregation for Spiking Neural Network Acceleration
Temporal Aggregated Convolution method for efficient spiking neural network acceleration on SIMD hardware.
3/17/2026
Exploring the Dimensions of a Variational Neuron
EVE: variational neuron with explicit prior and posterior for probabilistic computation at unit level.
3/17/2026
Fronto-parietal and fronto-temporal EEG coherence as predictive neuromarkers of transcutaneous auricular vagus nerve stimulation response in treatment-resistant schizophrenia: A machine learning study
Machine learning model using EEG data to predict treatment response for schizophrenia using vagus nerve stimulation.
3/17/2026
OrigamiBench: An Interactive Environment to Synthesize Flat-Foldable Origamis
Benchmark for training AI systems to plan and act in physical world with understanding of causal mechanisms and constraints.
3/17/2026
On Interpolation Formulas Describing Neural Network Generalization
Theoretical analysis extending Domingos interpolation formula to stochastic gradient descent, characterizing neural network generalization as kernel machines.
3/17/2026
Scribe Verification in Chinese manuscripts using Siamese, Triplet, and Vision Transformer Neural Networks
Deep metric learning approach (Siamese, Triplet, Vision Transformer) for identifying scribes in Chinese manuscript calligraphy datasets.
3/17/2026
UVLM: A Universal Vision-Language Model Loader for Reproducible Multimodal Benchmarking
UVLM: unified framework for loading and benchmarking multiple vision-language models with standardized interface in Colab environment.
3/17/2026
Robust Self-Training with Closed-loop Label Correction for Learning from Noisy Labels
Self-training framework with label correction for handling noisy data in neural network training using bilevel optimization techniques.
3/17/2026
Distributed Acoustic Sensing for Urban Traffic Monitoring: Spatio-Temporal Attention in Recurrent Neural Networks
Uses recurrent neural networks with spatio-temporal attention for traffic monitoring from acoustic fiber-optic sensors. Application-focused, limited AI interest.
3/17/2026
FedPBS: Proximal-Balanced Scaling Federated Learning Model for Robust Personalized Training for Non-IID Data
FedPBS: federated learning algorithm addressing statistical heterogeneity and non-IID data for distributed ML training with privacy preservation.
3/17/2026
Close to Reality: Interpretable and Feasible Data Augmentation for Imbalanced Learning
Interpretable data augmentation for imbalanced learning that generates realistic, feasible samples with transparent procedures and adjustability.
3/17/2026
True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity
Method for training 4-bit quantized CNNs on standard CPUs with PyTorch achieving full-precision accuracy parity for cost-effective deep learning.
3/17/2026
Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications
CONSERVAttack method for testing high energy physics ML applications against physically motivated systematic uncertainties and adversarial robustness.
3/17/2026
Chunk-Guided Q-Learning
Chunk-Guided Q-Learning algorithm for offline reinforcement learning balancing bootstrapping error and policy flexibility over long horizons.
3/17/2026
Aumann-SHAP: The Geometry of Counterfactual Interaction Explanations in Machine Learning
Aumann-SHAP framework for interaction-aware counterfactual explanations decomposing model transitions using cooperative game theory.
3/17/2026
Benchmarking Open-Source PPG Foundation Models for Biological Age Prediction
Benchmarking open-source PPG foundation models for biological age prediction, comparing task-specific vs general-purpose models across populations.
3/17/2026
Gated Graph Attention Networks for Predicting Duration of Large Scale Power Outages Induced by Natural Disasters
Gated graph attention networks for predicting duration of large-scale power outages induced by natural disasters.
3/17/2026
Enhancing Mental Health Classification with Layer-Attentive Residuals and Contrastive Feature Learning
Layer-attentive residuals and contrastive feature learning for mental health classification with overlapping diagnostic categories.
3/17/2026
Bootstrapped Physically-Primed Neural Networks for Robust T2 Distribution Estimation in Low-SNR Pancreatic MRI
Bootstrap-based neural network inference framework for robust T2 relaxation distribution estimation in low-SNR pancreatic MRI imaging.
3/17/2026
Understanding the Emergence of Seemingly Useless Features in Next-Token Predictors
Analysis of redundant features emerging in Transformer next-token predictors, identifying gradient components responsible for seemingly useless feature computation.
3/17/2026
Not All Latent Spaces Are Flat: Hyperbolic Concept Control
Hyperbolic control mechanism using parallel transport to steer text-to-image models away from unsafe content generation.
3/17/2026
ST-ResGAT: Explainable Spatio-Temporal Graph Neural Network for Road Condition Prediction and Priority-Driven Maintenance
ST-ResGAT spatio-temporal graph neural network for road pavement deterioration forecasting and predictive maintenance decision-support.
3/17/2026
SVD Contextual Sparsity Predictors for Fast LLM Inference
Framework for accelerating LLM inference using contextual sparsity predictors for ReGLU-based feed-forward networks with minimal accuracy loss.
3/17/2026
Multifidelity Surrogate Modeling of Depressurized Loss of Forced Cooling in High-temperature Gas Reactors
Multifidelity surrogate modeling combining high and low-resolution simulations for nuclear reactor CFD analysis parameter exploration.
3/17/2026
Align Forward, Adapt Backward: Closing the Discretization Gap in Logic Gate Networks
Analysis of training-inference mismatch in neural networks with soft vs hard selection, using logic gate networks as test case.
3/17/2026
TACTIC for Navigating the Unknown: Tabular Anomaly deteCTion via In-Context inference
TACTIC method for tabular anomaly detection using in-context learning with foundation models, advancing unsupervised learning for anomaly detection tasks.
3/17/2026
Hybrid Intent-Aware Personalization with Machine Learning and RAG-Enabled Large Language Models for Financial Services Marketing
Hybrid architecture combining classical ML for customer segmentation with RAG-enabled LLMs for personalized financial services marketing content generation.
3/17/2026
Balancing Multimodal Domain Generalization via Gradient Modulation and Projection
Gradient modulation and projection techniques balance optimization across modalities in multimodal domain generalization tasks.
3/17/2026
Artificial intelligence-enabled single-lead ECG for non-invasive hyperkalemia detection: development, multicenter validation, and proof-of-concept deployment
Pocket-K AI-ECG system using ECGFounder foundation model for non-invasive hyperkalemia detection with handheld deployment.
3/17/2026
Interleaved Resampling and Refitting: Data and Compute-Efficient Evaluation of Black-Box Predictors
Efficient procedure for evaluating excess risk of empirical risk minimization using black-box access with minimal data and compute.
3/17/2026
Self-Indexing KVCache: Predicting Sparse Attention from Compressed Keys
Self-Indexing KVCache predicts sparse attention from compressed keys to reduce KV cache bottleneck in long-context LLM inference.
3/17/2026
Domain-Skewed Federated Learning with Feature Decoupling and Calibration
Addresses domain skew in federated learning through feature decoupling and calibration across distributed clients with diverse data.
3/17/2026
GoldenStart: Q-Guided Priors and Entropy Control for Distilling Flow Policies
GoldenStart improves flow-matching RL policies via Q-guided priors and entropy control for faster inference and better exploration.
3/17/2026
Sampling Boltzmann distributions via normalizing flow approximation of transport maps
Mathematical foundation for sampling Boltzmann distributions via normalizing flows, proving existence of transport map approximations.
3/17/2026
Learning in Function Spaces: An Unified Functional Analytic View of Supervised and Unsupervised Learning
Unified functional analytic framework interpreting supervised and unsupervised learning as variational optimization over function spaces.
3/17/2026
High-Fidelity Compression of Seismic Velocity Models via SIREN Auto-Decoders
SIREN auto-decoder framework for high-fidelity compression of seismic velocity models using implicit neural representations.
3/17/2026
Enhancing LLM Training via Spectral Clipping
Spectral clipping optimization technique for LLM training that addresses spectral norm instability and gradient noise issues in standard optimizers.
3/17/2026
Structure-Dependent Regret and Constraint Violation Bounds for Online Convex Optimization with Time-Varying Constraints
Theoretical analysis of online convex optimization with time-varying constraints, providing regret and constraint violation bounds.
3/17/2026
ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation
ECG-Reasoning-Benchmark evaluates step-by-step clinical reasoning in multimodal LLMs for ECG interpretation across 6,400+ samples.
3/17/2026
Localizing and Editing Knowledge in Large Audio-Language Models
Methods for localizing and editing knowledge in large audio-language models, addressing factual errors across acoustic and language modules.
3/17/2026
Refold: Refining Protein Inverse Folding with Efficient Structural Matching and Fusion
Refold refines protein inverse folding by combining template-based methods with structural matching and fusion for amino acid sequence design.
3/17/2026
Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces
DeLL framework addresses catastrophic forgetting in autonomous driving via Dirichlet process mixture models and front-door causal adjustment.