2/16/2026
Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
Concept-grounded transparent domain adaptation for clinical event prediction on electronic health records.
2/16/2026
Fractional Order Federated Learning for Battery Electric Vehicle Energy Consumption Modeling
Fractional-order federated learning for battery electric vehicle energy consumption modeling.
2/16/2026
VI-CuRL: Stabilizing Verifier-Independent RL Reasoning via Confidence-Guided Variance Reduction
Verifier-independent RL method for LLM reasoning without external verifiers using confidence-guided variance reduction.
2/16/2026
Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
Analysis of catastrophic forgetting in mixture-of-experts transformers with multi-head attention.
2/16/2026
Vehicle behaviour estimation for abnormal event detection using distributed fiber optic sensing
Traffic anomaly detection using distributed fiber-optic sensing for lane behavior monitoring.
2/16/2026
Power Interpretable Causal ODE Networks: A Unified Model for Explainable Anomaly Detection and Root Cause Analysis in Power Systems
Causal ODE networks for explainable anomaly detection and root cause analysis in power grids.
2/16/2026
RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
RelBench v2 benchmark for relational deep learning on database-like data at scale.
2/16/2026
Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
Temporal graph neural networks optimized for continuous prediction on dynamic graphs.
2/16/2026
Efficient Personalized Federated PCA with Manifold Optimization for IoT Anomaly Detection
Federated PCA with personalization and manifold optimization for anomaly detection in IoT networks.
2/16/2026
Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps
SDM proposes principled sampling design for diffusion models using adaptive solvers and Wasserstein-bounded timesteps.
2/16/2026
Dual-Granularity Contrastive Reward via Generated Episodic Guidance for Efficient Embodied RL
Dual-granularity contrastive reward framework using generated episodic guidance for sample-efficient embodied reinforcement learning.
2/16/2026
Uncovering spatial tissue domains and cell types in spatial omics through cross-scale profiling of cellular and genomic interactions
Spatial transcriptomics analysis method for identifying tissue domains and cell types from cross-scale cellular interactions.
2/16/2026
SLA2: Sparse-Linear Attention with Learnable Routing and QAT
SLA2 improves sparse-linear attention for diffusion models with learnable routing and quantization-aware training.
2/16/2026
Trust the uncertain teacher: distilling dark knowledge via calibrated uncertainty
Knowledge distillation via calibrated uncertainty preserves dark knowledge from teachers trained with uncertainty-aware losses.
2/16/2026
Leverage-Weighted Conformal Prediction
Leverage-weighted conformal prediction method for adaptive prediction intervals using statistical leverage without auxiliary models.
2/16/2026
SWING: Unlocking Implicit Graph Representations for Graph Random Features
SWING algorithms for computing graph random features on implicit graph representations defined by feature vector functions.
2/16/2026
QTabGAN: A Hybrid Quantum-Classical GAN for Tabular Data Synthesis
Hybrid quantum-classical GAN framework for synthesizing tabular data with heterogeneous features under privacy constraints.
2/16/2026
Physics-Informed Laplace Neural Operator for Solving Partial Differential Equations
Physics-informed Laplace neural operator for solving PDEs, improving generalization in small-data and out-of-distribution regimes.
2/16/2026
Mixture of Predefined Experts: Maximizing Data Usage on Vertical Federated Learning
Split-MoPE addresses sample misalignment in vertical federated learning using mixture of experts specialized for partial data.
2/16/2026
ADEPT: RL-Aligned Agentic Decoding of Emotion via Evidence Probing Tools -- From Consensus Learning to Ambiguity-Driven Emotion Reasoning
ADEPT framework combines speech LLMs with evidence probing tools via RL-aligned agentic decoding for interpretable emotion reasoning.
2/16/2026
Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification
Adaptive structured pruning method for compressing deep learning time series classifiers without manual hyperparameter tuning.
2/16/2026
Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs
Control-theoretic framework addressing stability issues in LLM-based time series forecasting through closed-loop feedback instead of naive autoregressive generation.
2/16/2026
Can Neural Networks Provide Latent Embeddings for Telemetry-Aware Greedy Routing?
Placer applies message passing neural networks to network routing, improving explainability of ML-based telemetry-aware routing decisions.
2/16/2026
GRAIL: Geometry-Aware Retrieval-Augmented Inference with LLMs over Hyperbolic Representations of Patient Trajectories
GRAIL uses retrieval-augmented inference with hyperbolic geometry to improve LLM predictions of clinical events from patient trajectories.
2/16/2026
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
FLAC proposes a likelihood-free reinforcement learning framework using kinetic energy regularization for diffusion and flow matching policies.
2/16/2026
TRACE: Temporal Reasoning via Agentic Context Evolution for Streaming Electronic Health Records (EHRs)
TRACE applies agentic context evolution to LLMs for temporal reasoning over streaming electronic health records, improving clinical prediction without fine-tuning.
2/16/2026
Amortized Reasoning Tree Search: Decoupling Proposal and Decision in Large Language Models
Amortized Reasoning Tree Search decouples proposal and decision-making in LLMs for enhanced reasoning without suppressing valid paths.
2/16/2026
X-VORTEX: Spatio-Temporal Contrastive Learning for Wake Vortex Trajectory Forecasting
Contrastive learning approach for forecasting aircraft wake vortex trajectories from sparse LiDAR measurements.
2/16/2026
Transporting Task Vectors across Different Architectures without Training
Theseus: training-free method for transferring task-specific model updates across different neural network architectures.
2/16/2026
Ca-MCF: Category-level Multi-label Causal Feature selection
Category-level causal feature selection method for multi-label classification using fine-grained causal mechanisms.
2/16/2026
Extending confidence calibration to generalised measures of variation
Variation Calibration Error metric extending Expected Calibration Error for assessing classifier confidence calibration.
2/16/2026
Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
Variational autoencoder ensemble method for anomaly detection in streaming data with concept drift adaptation.
2/16/2026
MAUNet-Light: A Concise MAUNet Architecture for Bias Correction and Downscaling of Precipitation Estimates
MAUNet neural architecture for bias correction and downscaling of satellite and climate model precipitation data.
2/16/2026
Uncertainty in Federated Granger Causality: From Origins to Systemic Consequences
Federated Granger Causality framework for causal inference from distributed time-series data with uncertainty quantification.
2/16/2026
Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation (ACAM-J) using 7T fMRI
Machine learning classification of meditation states using fMRI brain imaging data and regional homogeneity analysis.
2/16/2026
Probabilistic Wind Power Forecasting with Tree-Based Machine Learning and Weather Ensembles
Wind power forecasting using gradient boosting trees and weather ensemble forecasts for probabilistic day-ahead predictions.
2/16/2026
Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery
Symbolic regression method incorporating scientific priors to prevent pseudo-equations and ensure consistency with physical principles.
2/16/2026
Resource-Efficient Gesture Recognition through Convexified Attention
Lightweight gesture recognition for wearable e-textile interfaces using convexified attention mechanism with minimal parameters.
2/16/2026
Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL
Hierarchical RL approach for dynamically learning temperature sampling policies in LLMs from internal states and task rewards.
2/16/2026
TCRL: Temporal-Coupled Adversarial Training for Robust Constrained Reinforcement Learning in Worst-Case Scenarios
Adversarial training method for robust constrained reinforcement learning against temporally coupled perturbations in safety-critical domains.
2/16/2026
GPTZero: Robust Detection of LLM-Generated Texts
Detection system for distinguishing AI-generated from human-authored text to prevent misinformation and content fraud.
2/16/2026
Geometric Manifold Rectification for Imbalanced Learning
Geometric approach to imbalanced classification addressing topological intrusion of majority class into minority manifold.
2/16/2026
Quantization-Aware Collaborative Inference for Large Embodied AI Models
Quantization-aware collaborative inference framework for deploying large embodied AI models on resource-limited agents.
2/16/2026
Diverging Flows: Detecting Extrapolations in Conditional Generation
Detection method for identifying when flow matching models extrapolate beyond training data in conditional generation tasks.
2/16/2026
Backdoor Attacks on Contrastive Continual Learning for IoT Systems
Security analysis of backdoor attacks targeting contrastive continual learning systems in IoT environments.
2/16/2026
Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning
Memory-efficient structured backpropagation for on-device LLM fine-tuning balancing gradient accuracy and memory constraints on mobile.
2/16/2026
LCSB: Layer-Cyclic Selective Backpropagation for Memory-Efficient On-Device LLM Fine-Tuning
Memory-efficient fine-tuning technique for LLMs on mobile devices via layer-cyclic selective backpropagation, reducing gradient computation.
2/16/2026
Unified Multi-Domain Graph Pre-training for Homogeneous and Heterogeneous Graphs via Domain-Specific Expert Encoding
Pre-training framework using domain-specific expert encoding for unified modeling of homogeneous and heterogeneous graphs.
2/16/2026
R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training
Solution to diversity collapse in self-play LLM training where challenger-solver loops degrade over iterations despite initial gains.
2/16/2026
Which Algorithms Can Graph Neural Networks Learn?
Study on which discrete algorithms graph neural networks can learn, advancing understanding of neural algorithmic reasoning capabilities.