2/19/2026
Far Out: Evaluating Language Models on Slang in Australian and Indian English
Evaluation of slang comprehension in state-of-the-art LLMs for Indian and Australian English varieties.
2/19/2026
SecCodeBench-V2 Technical Report
SecCodeBench-V2: benchmark of 98 scenarios evaluating LLM code generation security across 5 languages and 22 CWE categories.
2/19/2026
STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens
STAPO method stabilizing RL fine-tuning for LLMs by controlling rare spurious token gradients to prevent training collapse.
2/19/2026
A Content-Based Framework for Cybersecurity Refusal Decisions in Large Language Models
Content-based framework for consistent refusal decisions in LLM-based cybersecurity agents avoiding over-restriction and brittleness.
2/19/2026
A Koopman-Bayesian Framework for High-Fidelity, Perceptually Optimized Haptic Surgical Simulation
Koopman-Bayesian framework combining nonlinear dynamics and haptic rendering for surgical simulation.
2/19/2026
Memes-as-Replies: Can Models Select Humorous Manga Panel Responses?
Benchmark for selecting humorous manga panel responses in conversations using contextual meme understanding.
2/19/2026
BamaER: A Behavior-Aware Memory-Augmented Model for Exercise Recommendation
ML model for personalized exercise recommendation using behavior-aware memory augmentation for student learning.
2/19/2026
Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
Distributed physics-informed neural networks framework using domain decomposition for faster flow reconstruction from sparse velocity measurements.
2/19/2026
Adaptive Semi-Supervised Training of P300 ERP-BCI Speller System with Minimum Calibration Effort
Adaptive semi-supervised training method for P300 brain-computer interface speller with reduced calibration effort.
2/19/2026
R$^2$Energy: A Large-Scale Benchmark for Robust Renewable Energy Forecasting under Diverse and Extreme Conditions
R²Energy benchmark for evaluating deep learning models on renewable energy forecasting under extreme weather conditions.
2/19/2026
B-DENSE: Branching For Dense Ensemble Network Learning
B-DENSE proposes branching approach to improve diffusion model inference speed while preserving structural information from intermediate trajectory steps.
2/19/2026
Fast Online Learning with Gaussian Prior-Driven Hierarchical Unimodal Thompson Sampling
Multi-armed bandit algorithm using Thompson sampling with Gaussian priors for clustered arm problems in communications and portfolio management.
2/19/2026
Verifier-Constrained Flow Expansion for Discovery Beyond the Data
Flow model expansion method using verifier constraints for scientific discovery beyond training data distribution in molecular design space.
2/19/2026
Anatomy of Capability Emergence: Scale-Invariant Representation Collapse and Top-Down Reorganization in Neural Networks
Mechanistic study of capability emergence tracking geometric measures across model scales, revealing scale-invariant representation collapse during training.
2/19/2026
MolCrystalFlow: Molecular Crystal Structure Prediction via Flow Matching
Flow-matching generative model for predicting molecular crystal structures with periodic arrangements handling large molecules and complex interactions.
2/19/2026
AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
Carbon-aware evaluation metric for AI models that incorporates energy consumption and carbon emissions alongside traditional performance benchmarks.
2/19/2026
MoE-Spec: Expert Budgeting for Efficient Speculative Decoding
Expert budgeting optimization for efficient speculative decoding in Mixture-of-Experts LLMs to reduce memory pressure and maintain speedup.
2/19/2026
Multi-Objective Alignment of Language Models for Personalized Psychotherapy
Multi-objective alignment method for LLMs in psychotherapy applications balancing patient preferences with clinical safety using preference rankings.
2/19/2026
Extracting and Analyzing Rail Crossing Behavior Signatures from Videos using Tensor Methods
Multi-view tensor decomposition framework to extract and analyze driver behavior patterns at railway crossings across temporal phases.
2/19/2026
Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training
Theoretical analysis of generative AI robustness under data contamination from AI-generated content in recursive training, with guarantees on model survival.
2/19/2026
Omni-iEEG: A Large-Scale, Comprehensive iEEG Dataset and Benchmark for Epilepsy Research
Large-scale intracranial EEG dataset and benchmark for epilepsy research with automated seizure localization to reduce manual clinical review burden.
2/19/2026
Axle Sensor Fusion for Online Continual Wheel Fault Detection in Wayside Railway Monitoring
Continual learning approach for wheel fault detection in railway systems using semantic-aware sensor fusion for online predictive maintenance.
2/19/2026
Feature-based morphological analysis of shape graph data
Computational pipeline for statistical analysis of shape graph datasets using feature extraction to capture both connectivity and geometric variations.
2/19/2026
On the Power of Source Screening for Learning Shared Feature Extractors
Investigation of source screening for learning shared feature extractors across heterogeneous data sources to filter low-quality or irrelevant data.
2/19/2026
Investigating GNN Convergence on Large Randomly Generated Graphs with Realistic Node Feature Correlations
Analysis of graph neural network convergence on large random graphs with correlated node features to assess GNN expressiveness in realistic settings.
2/19/2026
ASPEN: Spectral-Temporal Fusion for Cross-Subject Brain Decoding
Study on cross-subject generalization in EEG-based brain-computer interfaces using spectral versus temporal representations for neural signal analysis.
2/19/2026
Differentially Private Non-convex Distributionally Robust Optimization
Distributionally robust optimization method combining differential privacy with worst-case loss minimization for handling distribution shifts and adversarial perturbations.
2/19/2026
HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents
Hierarchical reinforcement learning framework for training LLM agents on long-horizon tasks with sparse rewards using explicit credit assignment across action hierarchies.
2/19/2026
Muon with Spectral Guidance: Efficient Optimization for Scientific Machine Learning
Optimization method using orthogonalized updates for physics-informed neural networks and neural operators to handle ill-conditioned gradients and multi-scale behavior.
2/19/2026
Discrete Stochastic Localization for Non-autoregressive Generation
Non-autoregressive generation using masked diffusion language models with remasking samplers to reduce decoding latency while addressing error accumulation in iterative refinement.
2/19/2026
Towards Secure and Scalable Energy Theft Detection: A Federated Learning Approach for Resource-Constrained Smart Meters
Federated learning approach for energy theft detection in resource-constrained smart meters with privacy preservation.
2/19/2026
Deep TPC: Temporal-Prior Conditioning for Time Series Forecasting
Temporal-Prior Conditioning method for time series forecasting with LLMs, treating time as first-class modality across model depths.
2/19/2026
Rethinking Input Domains in Physics-Informed Neural Networks via Geometric Compactification Mappings
Physics-informed neural networks using geometric compactification mappings to address multi-scale PDEs and gradient stiffness issues.
2/19/2026
Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning
Graphon-based mean-field method for multi-agent reinforcement learning with heterogeneous agents and computational efficiency improvements.
2/19/2026
ModalImmune: Immunity Driven Unlearning via Self Destructive Training
ModalImmune framework for multimodal robustness via intentional modality collapse during training to handle missing input channels.
2/19/2026
Training-Free Adaptation of Diffusion Models via Doob's $h$-Transform
Training-free adaptation method for diffusion models using Doob's h-transform without additional training or differentiability assumptions.
2/19/2026
Linked Data Classification using Neurochaos Learning
Neurochaos Learning applied to linked data classification, demonstrating small-sample learning and low compute requirements on graph-structured data.
2/19/2026
Geometric Neural Operators via Lie Group-Constrained Latent Dynamics
Neural operators for PDEs using Lie group-constrained latent dynamics to improve stability in multi-layer iteration and long-horizon rollout.
2/19/2026
Graph neural network for colliding particles with an application to sea ice floe modeling
Graph neural network approach for sea ice modeling using collision physics in one-dimensional framework.
2/19/2026
UCTECG-Net: Uncertainty-aware Convolution Transformer ECG Network for Arrhythmia Detection
Uncertainty-aware hybrid CNN-Transformer architecture for ECG arrhythmia detection with reliability quantification.
2/19/2026
Bayesian Quadrature: Gaussian Processes for Integration
Comprehensive survey of Bayesian quadrature as probabilistic approach to numerical integration and uncertainty quantification.
2/19/2026
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
Lightweight MLP-Mixer model with random attention for multiscale long-term time series forecasting.
2/19/2026
Amortized Predictability-aware Training Framework for Time Series Forecasting and Classification
Amortized training framework addressing low-predictability samples in time series forecasting and classification.
2/19/2026
Factored Latent Action World Models
Factored latent action world models learning from action-free video for scalable controllable video generation.
2/19/2026
Regret and Sample Complexity of Online Q-Learning via Concentration of Stochastic Approximation with Time-Inhomogeneous Markov Chains
High-probability regret bounds for online Q-learning in infinite-horizon MDPs without optimism or bonus terms.
2/19/2026
Fast KV Compaction via Attention Matching
KV cache compaction method via attention matching to reduce memory overhead for long-context LLM inference.
2/19/2026
A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks
Graph meta-network architecture for weight-space models to predict neural network accuracy on Kolmogorov-Arnold networks.
2/19/2026
Guide-Guard: Off-Target Predicting in CRISPR Applications
Machine learning approach to predict off-target behavior in CRISPR genome editing applications.
2/19/2026
HAWX: A Hardware-Aware FrameWork for Fast and Scalable ApproXimation of DNNs
Hardware-aware framework for DNN approximation using multi-level sensitivity scoring and heterogeneous approximation blocks.
2/19/2026
The Implicit Bias of Adam and Muon on Smooth Homogeneous Neural Networks
Theoretical analysis of implicit bias in momentum-based optimizers (Adam, Muon, MomentumGD) on homogeneous neural networks.