3/30/2026
KMM-CP: Practical Conformal Prediction under Covariate Shift via Selective Kernel Mean Matching
Conformal prediction method for uncertainty quantification under covariate shift using selective kernel mean matching.
3/30/2026
Interpretable long-term traffic modelling on national road networks using theory-informed deep learning
Theory-informed deep learning model for long-term traffic forecasting balancing interpretability and predictive accuracy.
3/30/2026
Neuro-Symbolic Process Anomaly Detection
Neuro-symbolic approach combining neural networks and domain knowledge for process anomaly detection from event logs.
3/30/2026
Automatic feature identification in least-squares policy iteration using the Koopman operator framework
Koopman autoencoder-based least-squares policy iteration algorithm enabling automatic feature learning in reinforcement learning.
3/30/2026
A Boltzmann-machine-enhanced Transformer For DNA Sequence Classification
Transformer enhanced with Boltzmann machines for DNA sequence classification to uncover latent interactions and higher-order dependencies.
3/30/2026
Shapley meets Rawls: an integrated framework for measuring and explaining unfairness
Framework using Shapley values to measure and explain unfairness in machine learning models under group fairness criteria with inference methods.
3/30/2026
SPECTRA: An Efficient Spectral-Informed Neural Network for Sensor-Based Activity Recognition
SPECTRA: spectral-informed neural network for sensor-based activity recognition optimized for edge deployment with low latency and privacy.
3/30/2026
EcoFair: Trustworthy and Energy-Aware Routing for Privacy-Preserving Vertically Partitioned Medical Inference
EcoFair: privacy-preserving medical inference framework with lightweight routing for vertically partitioned data and modality-specific embeddings.
3/30/2026
Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory
Theoretical analysis of spectral optimizers like Muon in language model training, studying capacity scaling through linear associative memory framework.
3/30/2026
Machine Unlearning under Retain-Forget Entanglement
Machine unlearning framework addressing retain-forget entanglement where retained samples unintentionally affected by forgetting correlated features.
3/30/2026
The Climber's Grip -- Personalized Deep Learning Models for Fear and Muscle Activity in Climbing
Deep learning models for fear and muscle activity correlation in climbing sports using psychophysiological data. Niche domain application.
3/30/2026
Evaluating Interactive 2D Visualization as a Sample Selection Strategy for Biomedical Time-Series Data Annotation
Study comparing sample selection methods (random, farthest-first, interactive visualization) for annotation of biomedical time-series data with real annotators.
3/30/2026
PQuantML: A Tool for End-to-End Hardware-aware Model Compression
PQuantML: open-source hardware-aware neural network compression library for pruning and quantization with unified interface for latency-constrained deployment.
3/30/2026
Characterization and forecasting of national-scale solar power ramp events
Machine learning approach to forecasting solar power ramp events for grid stability. Energy domain application.
3/30/2026
Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders
Quantum-inspired anomaly detection using hardware-aware tensor networks for particle collider physics, deployable on classical hardware.
3/30/2026
Benchmarking Tabular Foundation Models for Conditional Density Estimation in Regression
Systematic evaluation of tabular foundation models like TabPFN and TabICL for conditional density estimation in regression tasks with heteroscedasticity.
3/30/2026
Context-specific Credibility-aware Multimodal Fusion with Conditional Probabilistic Circuits
C²MF: context-specific credibility-aware multimodal fusion framework using probabilistic circuits to handle conflicting modalities and situational reliability changes.
3/30/2026
Automatic Laplace Collapsed Sampling: Scalable Marginalisation of Latent Parameters via Automatic Differentiation
Framework for marginalizing latent parameters in Bayesian models via automatic differentiation combined with nested sampling.
3/30/2026
An LP-based Sampling Policy for Multi-Armed Bandits with Side-Observations and Stochastic Availability
LP-based sampling policy for multi-armed bandits with network-enabled side-observations and stochastic action availability.
3/30/2026
A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems
Lightweight self-adaptive ML framework for DC arc-fault detection in photovoltaic systems addressing hardware heterogeneity and environmental noise.
3/30/2026
KANEL: Kolmogorov-Arnold Network Ensemble Learning Enables Early Hit Enrichment in High-Throughput Virtual Screening
Kolmogorov-Arnold Network ensemble learning for early hit enrichment in virtual screening with improved positive predictive value metrics.
3/30/2026
A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning
Method for automatic timestep selection in Diffusion Transformers to improve efficiency of discriminative representation learning.
3/30/2026
SAHMM-VAE: A Source-Wise Adaptive Hidden Markov Prior Variational Autoencoder for Unsupervised Blind Source Separation
Variational autoencoder with adaptive Hidden Markov priors for unsupervised blind source separation with source-specific temporal modeling.
3/30/2026
A Judge Agent Closes the Reliability Gap in AI-Generated Scientific Simulation
Judge Agent system using automated mathematical validation to reduce silent failures in LLM-generated scientific simulation code from 42% to 1.5%.
3/30/2026
Vision Transformers and Graph Neural Networks for Charged Particle Tracking in the ATLAS Muon Spectrometer
Vision Transformers and GNNs for charged particle track reconstruction in ATLAS muon spectrometer under high luminosity conditions.
3/30/2026
Beyond identifiability: Learning causal representations with few environments and finite samples
Theoretical guarantees for learning causal representations from limited environments and finite samples.
3/30/2026
Do All Vision Transformers Need Registers? A Cross-Architectural Reassessment
Study evaluating whether Vision Transformer architectures universally require register tokens to eliminate attention map artifacts.
3/30/2026
ExVerus: Verus Proof Repair via Counterexample Reasoning
LLM framework for formal proof repair using counterexample-guided reasoning and behavioral feedback to improve automated verification.
3/30/2026
Doctorina MedBench: End-to-End Evaluation of Agent-Based Medical AI
Comprehensive evaluation framework for agent-based medical AI systems via multi-step clinical dialogue simulation with realistic physician-patient interactions.
3/30/2026
A Neural Score-Based Particle Method for the Vlasov-Maxwell-Landau System
Neural score-based particle method for simulating collisional plasma kinetics in the Vlasov-Maxwell-Landau system.
3/30/2026
Speech-Synchronized Whiteboard Generation via VLM-Driven Structured Drawing Representations
Dataset and VLM method for generating whiteboard animations synchronized with speech narration across STEM domains using structured drawing representations.
3/30/2026
Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned
Real-world evaluation of visual navigation foundation models on robot navigation, testing generalization and providing trajectory quality metrics.
3/30/2026
Collision-Aware Vision-Language Learning for End-to-End Driving with Multimodal Infraction Datasets
Vision-language learning approach for end-to-end autonomous driving using multimodal datasets and collision-aware representation learning.
3/30/2026
Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
Optimization framework for robust decisions when predictions lack calibrated error bounds, combining robust and regret formulations.
3/30/2026
A Priori Sampling of Transition States with Guided Diffusion
Method using guided diffusion to sample transition states on potential energy surfaces for chemical reaction and conformational change prediction.
3/30/2026
Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression
Theoretical analysis of rank selection for low-rank tensor regression with applications to neural network compression and model optimization.
3/30/2026
MUST: Modality-Specific Representation-Aware Transformer for Diffusion-Enhanced Survival Prediction with Missing Modality
Transformer model for survival prediction from incomplete multimodal medical data using modality-specific representation learning and diffusion.
3/30/2026
CD-Buffer: Complementary Dual-Buffer Framework for Test-Time Adaptation in Adverse Weather Object Detection
Test-time adaptation framework combining subtractive and additive approaches for object detection under adverse weather domain shifts.
3/30/2026
A Human-Inspired Decoupled Architecture for Efficient Audio Representation Learning
Decoupled audio transformer architecture inspired by human cognition for efficient self-supervised learning on resource-constrained devices.
3/30/2026
Finding Distributed Object-Centric Properties in Self-Supervised Transformers
Analysis of object discovery in self-supervised Vision Transformers, showing how [CLS] token attention maps contain spurious activations affecting localization.
3/30/2026
Dual-Stage Invariant Continual Learning under Extreme Visual Sparsity
Continual learning method for object detection under extreme visual sparsity conditions using dual-stage invariant learning.
3/30/2026
On associative neural networks for sparse patterns with huge capacities
Higher-order associative memory models combining exponential interactions with sparse pattern storage for improved storage capacity.
3/30/2026
Privacy-Accuracy Trade-offs in High-Dimensional LASSO under Perturbation Mechanisms
Analysis of privacy-accuracy trade-offs in high-dimensional sparse linear regression using differential privacy mechanisms and approximate message passing.
3/30/2026
Distilling Conversations: Abstract Compression of Conversational Audio Context for LLM-based ASR
Method for compressing conversational audio context in LLM-based speech recognition systems, studying multimodal context from prior turns for improved ASR.
3/30/2026
ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature Extraction
Mixed-resolution vision transformer with adaptive token allocation for efficient dense feature extraction using coarse-to-fine processing.
3/30/2026
GLASS: Geometry-aware Local Alignment and Structure Synchronization Network for 2D-3D Registration
Vision network for 2D-3D image-to-point-cloud registration using geometry-aware local alignment and structural synchronization.
3/30/2026
Preference-Aligned LoRA Merging: Preserving Subspace Coverage and Addressing Directional Anisotropy
Approach for merging multiple LoRA modules while preserving subspace coverage and addressing directional anisotropy to maintain task representation in general-purpose systems.
3/30/2026
Semi-structured multi-state delinquency model for mortgage default
Semi-structured discrete-time model combining additive predictors with neural networks for mortgage delinquency analysis and default prediction.
3/30/2026
SALMUBench: A Benchmark for Sensitive Association-Level Multimodal Unlearning
Benchmark for evaluating machine unlearning in multimodal models like CLIP, introducing SALMUBench with 60K persona-attribute associations for fine-grained forgetting evaluation.
3/30/2026
Label-Free Cross-Task LoRA Merging with Null-Space Compression
Method for merging independently fine-tuned LoRA adapters across heterogeneous tasks using null-space compression, addressing classification-regression task combinations.